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1
Qi, Lihua, Dongqiu Xing, Rui Wang, and Jingna Cui. "Research on the operational regional coverage of satellite and spacecraft tracking and controlling." MATEC Web of Conferences 309 (2020): 01005. http://dx.doi.org/10.1051/matecconf/202030901005.
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In view of the problem of building ground stations for tracking and controlling of satellites and spacecraft, considering the fixed angle between the orbit of the satellite or spacecraft and the equatorial surface of the earth, and the difference of longitude between the two circles in succession of the satellite or spacecraft caused by the rotation of the earth, the operation area of the satellite or spacecraft was calculated by using the method of spherical projection of satellite orbit rotation, taking the earth as the reference system. The minimum number of ground stations needed for satellite tracking and controlling was calculated in three cases, by using the mathematical model of sphere ring area and honeycomb coverage. This model was validated by the launch and operation data of Shenzhou 7.
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Vahid oğlu Nasiyev, Müslim. "Research and application of satellite communication networks as an alternative to modern communication systems." SCIENTIFIC WORK 68, no. 07 (July 22, 2021): 78–83. http://dx.doi.org/10.36719/2663-4619/68/78-83.
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Research work has been devoted to show how satellite technology can meet a variety of human needs and the ultimate measure of its effectiveness. Communication satellites, whether in geostationary Earth orbit (GEO) or non GEO, provide an effective platform to relay radio signals between points on the ground. The users who employ these signals enjoy a broad spectrum of telecommunication services on the ground, at sea, and in the air. In recent years, such systems have become practical to the point where a typical household can have its own satellite dish. That dish can receive a broad range of television programming and provide broadband access to the Internet. Key words: satellite, antenna, Earth orbit (GEO), transponder, VHF, frequency modulation (FM)10.36719/2663-4619/68/78-83 Müslim Vahid oğlu Nasiyev Azərbaycan Texniki Universiteti magistrant mnesiyev@gmail.com MÜASİR RABİTƏ SİSTEMLƏRİNƏ ALTERNATİV OLARAQ, PEYK RABİTƏ ŞƏBƏKƏLƏRİNİN ARAŞDIRILMASI VƏ TƏTBİQİ Açar sözlər: Peyk, antena, yer orbiti (GEO), transponder, VHF, tezlik modulyasiyası (FM) Research and application of satellite communication networks as an alternative to modern communication systems Summary Research work has been devoted to show how satellite technology can meet a variety of human needs and the ultimate measure of its effectiveness. Communication satellites, whether in geostationary Earth orbit (GEO) or non GEO, provide an effective platform to relay radio signals between points on the ground. The users who employ these signals enjoy a broad spectrum of telecommunication services on the ground, at sea, and in the air. In recent years, such systems have become practical to the point where a typical household can have its own satellite dish. That dish can receive a broad range of television programming and provide broadband access to the Internet. Key words: satellite, antenna, Earth orbit (GEO), transponder, VHF, frequency modulation (FM)
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Caizzone, Stefano, Miriam Schönfeldt, Wahid Elmarissi, and Mihaela-Simona Circiu. "Antennas as Precise Sensors for GNSS Reference Stations and High-Performance PNT Applications on Earth and in Space." Sensors 21, no. 12 (June 18, 2021): 4192. http://dx.doi.org/10.3390/s21124192.
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Satellite navigation is more and more important in a plethora of very different application fields, ranging from bank transactions to shipping, from autonomous driving to aerial applications, such as commercial avionics as well as unmanned aerial vehicles (UAVs). In very precise positioning, navigation, and timing (PNT) applications, such as in reference stations and precise timing stations, it is important to characterize all errors present in the system in order to account possibly for them or calibrate them out. Antennas play an important role in this respect: they are indeed the “sensor” that capture the signal in space from global navigation satellite systems (GNSS) and thereby strongly contribute to the overall achievable performance. This paper reviews the currently available antenna technologies, targeting specifically reference stations as well as precise GNSS antennas for space applications, and, after introducing performance indicators, summarizes the currently achievable performance. Finally, open research issues are identified, and possible approaches to solve them are discussed.
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Ильченко, Михаил Ефимович, Теодор Николаевич Нарытник, Борис Михайлович Рассамакин, Владимир Ильич Присяжный, and Сергей Владимирович Капштык. "СОЗДАНИЕ АРХИТЕКТУРЫ «РАСПРЕДЕЛЕННОГО СПУТНИКА» ДЛЯ НИЗКООРБИТАЛЬНЫХ ИНФОРМАЦИОННО-ТЕЛЕКОММУНИКАЦИОННЫХ СИСТЕМ НА ОСНОВЕ ГРУППИРОВКИ МИКРО- И НАНОСПУТНИКОВ." Aerospace technic and technology, no. 2 (April 26, 2018): 33–43. http://dx.doi.org/10.32620/aktt.2018.2.05.
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Presented are the results of an analysis of the growing interest in the use of low Earth orbits (up to 1500 km high) for the introduction and development of the Internet of things (Internet of Things - IoT). Industrial Internet of things (Industrial Internet of Things-IIoT). Internet of things for remote areas (Remote Internet of Things - RioT, for the purposes of scientific research and economic use of natural resources, control of the development and operation of infrastructure projects, the operation of territorially distributed industrial production, transport infrastructure. Factors significantly limiting the further introduction of micro and nano satellites are given. The authors proposed to resolve this contradiction on the basis of the developed concept of creating the architecture of a "distributed satellite". As an example, the article considers possible applications of the distributed satellite architecture in two segments of the space information systems market: remote sensing of the Earth and telecommunication systems. The application of the "distributed satellite" in radar systems with synthesized aperture (SAR-system) was considered taking into account the requirements of the operators of satellite SAR-systems and consumers of their information. It is shown. that the use of the "distributed satellite" architecture in SAR-systems also makes it possible to realize the technology of multi-static radar with a "soft" interference base (from 200 m to 1 km). The scheme of organization and interaction of the "distributed satellite" in the satellite-transmitter on the platform of the micro satellite, which is the core of the satellite cluster, and several satellites-receivers on the cube-sat platform is presented. The functions performed by the satellite-transmitter, the inter-satellite radio link and the satellite-receiver are considered in detail. The work of the "distributed satellite" is illustrated by the presented structural diagram of the SAR-system for remote sensing of the Earth, a version of the architecture of the low-orbit satellite communication system and the scheme for constructing a satellite system for the provision of IoT services. In conclusion, it is noted that the architecture of the "distributed satellite" makes it possible to effectively use satellites of the class of micro/nano satellite (cube-sat) to create complex space-based information and telecommunication systems
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Babuscia, Alessandra. "Telecommunication Systems for Small Satellites Operating at High Frequencies: A Review." Information 11, no. 5 (May 8, 2020): 258. http://dx.doi.org/10.3390/info11050258.
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Small Satellites and in particular CubeSats are becoming extremely popular platforms with which to perform space research. They allow for rapid prototyping with considerable cost savings with respect to traditional missions. However, as small satellite missions become more ambitious in terms of destinations to reach (from Low Earth Orbit to interplanetary) and in terms of the amount of data to transmit, new technologies need to be developed to provide adequate telecommunication support. This paper aims to review the telecommunication systems that have been developed at the Jet Propulsion Laboratory for some of the most recent CubeSat missions operating at different frequency bands: ASTERIA (S-Band), MarCO (X-Band and UHF) and ISARA (Ka-Band and UHF). For each of these missions: the telecommunication challenges and requirements are listed; the final system design is presented; the characteristics of the different hardware components are shown; and the lessons learned through operations are discussed.
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Lv, Yifei, Tao Geng, Qile Zhao, Xin Xie, Feng Zhang, and Xing Wang. "Evaluation of BDS-3 Orbit Determination Strategies Using Ground-Tracking and Inter-Satellite Link Observation." Remote Sensing 12, no. 16 (August 17, 2020): 2647. http://dx.doi.org/10.3390/rs12162647.
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Dual one-way inter-satellite link (ISL) pseudoranges of BDS-3 satellites can be introduced as an additional measurement along with L-band pseudoranges and phases to improve the accuracy of precise orbit determination (POD). In the existing research, although the clock-free or geometry-free ISL observables are derived from the raw two one-way pseudoranges, only the clock-free observables are adopted for the ISL joint POD (Joint 1 POD) without considering the geometric-free observables. An improved joint (Joint 2 POD) strategy making full use of the clock-free and geometry-free observables is applied in this contribution. The orbits of ground-only POD, ISL-only POD, Joint 1 POD, and Joint 2 POD are comprehensively compared by the orbit overlapping differences, the Satellite Laser Ranging (SLR) residuals, and the characteristics of the satellite clock offsets estimated simultaneously. The comparisons prove that the performance of the Joint 2 POD strategy is better than that of the other three POD strategies regardless of the types of satellites. Moreover, this paper discusses ISL’s contribution to the station selection strategy in terms of the number and distribution. The experimental results show that, when there are more than 20 stations, each additional 10 stations contributes to a maximum of 7.5%, 3.9%, and 2.8% improvement on MEO, IGSO, and GEO satellites 3D accuracy, respectively. When the number of stations reaches 50, the precise orbits achieve similar accuracy to the results using 80 stations. In addition, after adding ISL data, the orbits estimated using 10 regional stations and 10 global stations are greatly improved, and the accuracy between them is only 0.9 cm in 3D errors.
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Jamei, Mozhdeh, Mohammad Mousavi Baygi, Ebrahim Asadi Oskouei, and Ernesto Lopez-Baeza. "Validation of the SMOS Level 1C Brightness Temperature and Level 2 Soil Moisture Data over the West and Southwest of Iran." Remote Sensing 12, no. 17 (August 31, 2020): 2819. http://dx.doi.org/10.3390/rs12172819.
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The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission with the MIRAS (Microwave Imaging Radiometer using Aperture Synthesis) L-band radiometer provides global soil moisture (SM) data. SM data and products from remote sensing are relatively new, but they are providing significant observations for weather forecasting, water resources management, agriculture, land surface, and climate models assessment, etc. However, the accuracy of satellite measurements is still subject to error from the retrieval algorithms and vegetation cover. Therefore, the validation of satellite measurements is crucial to understand the quality of retrieval products. The objectives of this study, precisely framed within this mission, are (i) validation of the SMOS Level 1C Brightness Temperature (TBSMOS) products in comparison with simulated products from the L-MEB model (TBL-MEB) and (ii) validation of the SMOS Level 2 SM (SMSMOS) products against ground-based measurements at 10 significant Iranian agrometeorological stations. The validations were performed for the period of January 2012 to May 2015 over the Southwest and West of Iran. The results of the validation analysis showed an RMSE ranging between 9 to 13 K and a strong correlation (R = 0.61–0.84) between TBSMOS and TBL-MEB at all stations. The bias values (0.1 to 7.5 K) showed a slight overestimation for TBSMOS at most of the stations. The results of SMSMOS validation indicated a high agreement (RMSE = 0.046–0.079 m3 m−3 and R = 0.65–0.84) between the satellite SM and in situ measurements over all the stations. The findings of this research indicated that SMSMOS shows high accuracy and agreement with in situ measurements which validate its potential. Due to the limitation of SM measurements in Iran, the SMOS products can be used in different scientific and practical applications at different Iranian study areas.
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Martin, Maria, Darren Ghent, Ana Pires, Frank-Michael Göttsche, Jan Cermak, and John Remedios. "Comprehensive In Situ Validation of Five Satellite Land Surface Temperature Data Sets over Multiple Stations and Years." Remote Sensing 11, no. 5 (February 26, 2019): 479. http://dx.doi.org/10.3390/rs11050479.
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Global land surface temperature (LST) data derived from satellite-based infrared radiance measurements are highly valuable for various applications in climate research. While in situ validation of satellite LST data sets is a challenging task, it is needed to obtain quantitative information on their accuracy. In the standardised approach to multi-sensor validation presented here for the first time, LST data sets obtained with state-of-the-art retrieval algorithms from several sensors (AATSR, GOES, MODIS, and SEVIRI) are matched spatially and temporally with multiple years of in situ data from globally distributed stations representing various land cover types in a consistent manner. Commonality of treatment is essential for the approach: all satellite data sets are projected to the same spatial grid, and transformed into a common harmonized format, thereby allowing comparison with in situ data to be undertaken with the same methodology and data processing. The large data base of standardised satellite LST provided by the European Space Agency’s GlobTemperature project makes previously difficult to perform LST studies and applications more feasible and easier to implement. The satellite data sets are validated over either three or ten years, depending on data availability. Average accuracies over the whole time span are generally within ±2.0 K during night, and within ± 4.0 K during day. Time series analyses over individual stations reveal seasonal cycles. They stem, depending on the station, from surface anisotropy, topography, or heterogeneous land cover. The results demonstrate the maturity of the LST products, but also highlight the need to carefully consider their temporal and spatial properties when using them for scientific purposes.
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Samad, Md Abdus, Feyisa Debo Diba, and Dong-You Choi. "A Survey of Rain Fade Models for Earth–Space Telecommunication Links—Taxonomy, Methods, and Comparative Study." Remote Sensing 13, no. 10 (May 18, 2021): 1965. http://dx.doi.org/10.3390/rs13101965.
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Satellite communication is a promising transmission technique to implement 5G and beyond networks. Attenuation due to rain begins at a frequency of 10 GHz in temperate regions. However, some research indicates that such attenuation effects start from 5–7 GHz, especially in tropical regions. Therefore, modeling rain attenuation is significant for propagating electromagnetic waves to achieve the required quality of service. In this survey, different slant link rain attenuation prediction models have been examined, classified, and analyzed, and various features like improvements, drawbacks, and particular aspects of these models have been tabulated. This survey provides various techniques for obtaining input data sets, including rain height, efficient trajectory length measurement techniques, and rainfall rate conversion procedures. No survey of the Earth–space link models for rain attenuation is available to the best of our knowledge. In this study, 23 rain attenuation models have been investigated. For easy readability and conciseness, the details of each model have not been included. The comparative analysis will assist in propagation modeling and planning the link budget of slant links.
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Li, Ying, Yunbin Yuan, and Xiaoming Wang. "Assessments of the Retrieval of Atmospheric Profiles from GNSS Radio Occultation Data in Moist Tropospheric Conditions Using Radiosonde Data." Remote Sensing 12, no. 17 (August 22, 2020): 2717. http://dx.doi.org/10.3390/rs12172717.
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The Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieved temperature and specific humidity profiles can be widely used for weather and climate studies in troposphere. However, some aspects, such as the influences of background data on these retrieved moist profiles have not been discussed yet. This research evaluates RO retrieved temperature and specific humidity profiles from Wegener Center for Climate and Global Change (WEGC), Radio Occultation Meteorology Satellite Application Facility (ROM SAF) and University Corporation for Atmospheric Research (UCAR) Boulder RO processing centers by comparing with measurements from 10 selected Integrated Global Radiosonde Archive (IGRA) radiosonde stations in different latitudinal bands over 2007 to 2010. The background profiles used for producing their moist profiles are also compared with radiosonde. We found that RO retrieved temperature profiles from all centers agree well with radiosonde. Mean differences at polar, mid-latitudinal and tropical stations are varying within ±0.2 K, ±0.5 K and from −1 to 0.2 K, respectively, with standard deviations varying from 1 to 2 K for most pressure levels. The differences between RO retrieved and their background temperature profiles for WEGC are varying within ±0.5 K at altitudes above 300 hPa, and the differences for ROM SAF are within ±0.2 K, and that for UCAR are within 0.5 K at altitudes below 300 hPa. Both RO retrieved and background specific humidity above 600 hPa are found to have large positive differences (up to 40%) against most radiosonde measurements. Discrepancies of moist profiles among the three centers are overall minor at altitudes above 300 hPa for temperature and at altitudes above 700 hPa for specific humidity. Specific humidity standard deviations are largest at tropical stations in June July August months. It is expected that the outcome of this research can help readers to understand the characteristics of moist products among centers.
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Metsar, Jaanus, Karin Kollo, and Artu Ellmann. "MODERNIZATION OF THE ESTONIAN NATIONAL GNSS REFERENCE STATION NETWORK." Geodesy and cartography 44, no. 2 (August 8, 2018): 55–62. http://dx.doi.org/10.3846/gac.2018.2023.
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The first GNSS (Global Navigation Satellite System) CORS (Continuously Operating Reference Station) in Estonia became operational in 1996. Starting from 2008 four Estonian CORS are incorporated into the EPN (EUREF Permanent GNSS Network). During the years 2014-2015 modernization of the GNSS CORS in Estonia was carried out. Currently the total number of the resulting ESTPOS reference stations is 28. These ESTPOS stations were interconnected to the I order national geodetic network by a special GNSS campaign in 2017. The maintenance and compilation of the ESTPOS based research products is explained. Aspects of the ESTPOS usage, including also the real time surveys, are discussed. Comparisons with SWEPOS (Swedish national GNSS CORS) and FinnRef (Finnish national GNSS CORS) networks indicate possibilities for further ESTPOS developments.
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Caputo, Teresa, Eliana Bellucci Sessa, Malvina Silvestri, Maria Fabrizia Buongiorno, Massimo Musacchio, Fabio Sansivero, and Giuseppe Vilardo. "Surface Temperature Multiscale Monitoring by Thermal Infrared Satellite and Ground Images at Campi Flegrei Volcanic Area (Italy)." Remote Sensing 11, no. 9 (April 28, 2019): 1007. http://dx.doi.org/10.3390/rs11091007.
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Land Surface Temperature (LST) from satellite data is a key component in many aspects of environmental research. In volcanic areas, LST is used to detect ground thermal anomalies providing a supplementary tool to monitor the activity status of a particular volcano. In this work, we describe a procedure aimed at identifying spatial thermal anomalies in thermal infrared (TIR) satellite frames which are corrected for the seasonal influence by using TIR images from ground stations. The procedure was applied to the volcanic area of Campi Flegrei (Italy) using TIR ASTER and Landsat 8 satellite imagery and TIR ground images acquired from the Thermal Infrared volcanic surveillance Network (TIRNet) (INGV, Osservatorio Vesuviano). The continuous TIRNet time-series images were processed to evaluate the seasonal component which was used to correct the surface temperatures estimated by the satellite’s discrete data. The results showed a good correspondence between de-seasoned time series of surface ground temperatures and satellite temperatures. The seasonal correction of satellite surface temperatures allows monitoring of the surface thermal field to be extended to all the satellite frames, covering a wide portion of Campi Flegrei volcanic area.
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Jagoda, Marcin, Miłosława Rutkowska, Paweł Lejba, Jacek Katzer, Romuald Obuchovski, and Dominykas Šlikas. "Satellite Laser Ranging for Retrieval of the Local Values of the Love h2 and Shida l2 Numbers for the Australian ILRS Stations." Sensors 20, no. 23 (November 30, 2020): 6851. http://dx.doi.org/10.3390/s20236851.
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This paper deals with the analysis of local Love and Shida numbers (parameters h2 and l2) values of the Australian Yarragadee and Mount Stromlo satellite laser ranging (SLR) stations. The research was conducted based on data from the Medium Earth Orbit (MEO) satellites, LAGEOS-1 and LAGEOS-2, and Low Earth Orbit (LEO) satellites, STELLA and STARLETTE. Data from a 60-month time interval, from 01.01.2014 to 01.01.2019, was used. In the first research stage, the Love and Shida numbers values were determined separately from observations of each satellite; the obtained values of h2, l2 exhibit a high degree of compliance, and the differences do not exceed formal error values. At this stage, we found that it was not possible to determine l2 from the data of STELLA and STARLETTE. In the second research stage, we combined the satellite observations of MEO (LAGEOS-1+LAGEOS-2) and LEO (STELLA+STARLETTE) and redefined the h2, l2 parameters. The final values were adopted, and further analyses were made based on the values obtained from the combined observations. For the Yarragadee station, local h2 = 0.5756 ± 0.0005 and l2 = 0.0751 ± 0.0002 values were obtained from LAGEOS-1 + LAGEOS-2 and h2 = 0.5742 ± 0.0015 were obtained from STELLA+STARLETTE data. For the Mount Stromlo station, we obtained the local h2 = 0.5601 ± 0.0006 and l2 = 0.0637 ± 0.0003 values from LAGEOS-1+LAGEOS-2 and h2 = 0.5618 ± 0.0017 from STELLA + STARLETTE. We found discrepancies between the local parameters determined for the Yarragadee and Mount Stromlo stations and the commonly used values of the h2, l2 parameters averaged for the whole Earth (so-called global nominal parameters). The sequential equalization method was used for the analysis, which allowed to determine the minimum time interval necessary to obtain stable h2, l2 values. It turned out to be about 50 months. Additionally, we investigated the impact of the use of local values of the Love/Shida numbers on the determination of the Yarragadee and Mount Stromlo station coordinates. We proposed to determine the stations (X, Y, Z) coordinates in International Terrestrial Reference Frame 2014 (ITRF2014) in two computational versions: using global nominal h2, l2 values and local h2, l2 values calculated during this research. We found that the use of the local values of the h2, l2 parameters in the process of determining the stations coordinates influences the result.
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Ajtai, Nicolae, Alexandru Mereuta, Horatiu Stefanie, Andrei Radovici, Camelia Botezan, Olga Zawadzka-Manko, Iwona Stachlewska, Kerstin Stebel, and Claus Zehner. "SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe." Remote Sensing 13, no. 5 (February 24, 2021): 844. http://dx.doi.org/10.3390/rs13050844.
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This paper presents the validation results of Aerosol Optical Depth (AOD) retrieved from the Spinning Enhanced Visible Infrared Radiometer (SEVIRI) data using the near-real-time algorithm further developed in the frame of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project. The SEVIRI AOD was compared against multiple data sources: six stations of the Aerosol Robotic Network (AERONET) in Romania and Poland, three stations of the Aerosol Research Network in Poland (Poland–AOD) and Moderate Resolution Imaging Spectroradiometer (MODIS) data overlapping Romania, Czech Republic and Poland. The correlation values between a four-month dataset (June–September 2014) from SEVIRI and the closest temporally available data for both ground-based and satellite products were identified. The comparison of the SEVIRI AOD with the AERONET AOD observations generally shows a good correlation (r = 0.48–0.83). The mean bias is 0.10–0.14 and the root mean square error RMSE is between 0.11 and 0.15 for all six stations cases. For the comparison with Poland–AOD correlation values are 0.55 to 0.71. The mean bias is 0.04–0.13 and RMSE is between 0.10 and 0.14. As for the intercomparison to MODIS AOD, correlations values were generally lower (r = 0.33–0.39). Biases of −0.06 to 0.24 and RMSE of 0.04 to 0.28 were in good agreement with the ground–stations retrievals. The validation of SEVIRI AOD with AERONET results in the best correlations followed by the Poland–AOD network and MODIS retrievals. The average uncertainty estimates are evaluated resulting in most of the AOD values falling above the expected error range. A revised uncertainty estimate is proposed by including the observed bias form the AERONET validation efforts.
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Kim, Chang Ki, Hyun-Goo Kim, Yong-Heack Kang, Chang-Yeol Yun, and Yun Gon Lee. "Intercomparison of Satellite-Derived Solar Irradiance from the GEO-KOMSAT-2A and HIMAWARI-8/9 Satellites by the Evaluation with Ground Observations." Remote Sensing 12, no. 13 (July 4, 2020): 2149. http://dx.doi.org/10.3390/rs12132149.
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Solar irradiance derived from satellite imagery is useful for solar resource assessment, as well as climate change research without spatial limitation. The University of Arizona Solar Irradiance Based on Satellite–Korea Institute of Energy Research (UASIBS-KIER) model has been updated to version 2.0 in order to employ the satellite imagery produced by the new satellite platform, GK-2A, launched on 5 December 2018. The satellite-derived solar irradiance from UASIBS-KIER model version 2.0 is evaluated against the two ground observations in Korea at instantaneous, hourly, and daily time scales in comparison with the previous version of UASIBS-KIER model that was optimized for the COMS satellite. The root mean square error of the UASIBS-KIER model version 2.0, normalized for clear-sky solar irradiance, ranges from 4.8% to 5.3% at the instantaneous timescale when the sky is clear. For cloudy skies, the relative root mean square error values are 14.5% and 15.9% at the stations located in Korea and Japan, respectively. The model performance was improved when the UASIBS-KIER model version 2.0 was used for the derivation of solar irradiance due to the finer spatial resolution. The daily aggregates from the proposed model are proven to be the most reliable estimates, with 0.5 km resolution, compared with the solar irradiance derived by the other models. Therefore, the solar resource map built by major outputs from the UASIBS-KIER model is appropriate for solar resource assessment.
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Walczak, Ken, Geza Gyuk, Andrew Kruger, Enoch Byers, and Sigi Huerta. "NITESat: A High Resolution, Full-Color, Light Pollution Imaging Satellite Mission." International Journal of Sustainable Lighting 19, no. 1 (June 28, 2017): 48–55. http://dx.doi.org/10.26607/ijsl.v19i1.68.
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The NITESat (Night Imaging and Tracking Experiment Satellite) mission is a 2U CubeSat satellite designed for nighttime Earth imaging to quantify and characterize light pollution across the Midwestern United States. It is accompanied and supported by an array of ground-based light pollution observing stations called GONet (Ground Observing Network). NITESat is a pilot mission testing the potential for a simple and inexpensive (<$500,000) satellite to deliver high-resolution, three-color regional data of artificial light at night. In addition, GONet will form the core of an educational outreach program by establishing an array of all-sky monitors covering the imaging region of the satellite with 20+ full sky light pollution citizen-operated stations. This will provide synchronized data coinciding with the NITESat overpasses as well as providing near continuous night sky quality monitoring. If the initial mission is a success, the potential exists to expand the program into a low cost constellation of satellites capable of delivering global coverage. NITESat is being designed, built and will be operated by the Far Horizons program at the Adler Planetarium in Chicago, Illinois. Far Horizons is a student and volunteer centered program offering hands-on engineering and scientific research opportunities for education.
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Xu, Fenglin, Bin Guo, Bei Ye, Qia Ye, Huining Chen, Xiaohui Ju, Jinyun Guo, and Zhongliang Wang. "Systematical Evaluation of GPM IMERG and TRMM 3B42V7 Precipitation Products in the Huang-Huai-Hai Plain, China." Remote Sensing 11, no. 6 (March 22, 2019): 697. http://dx.doi.org/10.3390/rs11060697.
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Accurate estimation of high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) and Tropical Rainfall Measuring Mission (TRMM) is critical for hydrological and meteorological research, providing a benchmark for the continued development and future improvement of these products. This study aims to comprehensively evaluate the Integrated Multi-Satellite Retrievals for GPM (IMERG) and TRMM 3B42V7 products at multiple temporal scales from 1 January 2015 to 31 December 2017 over the Huang-Huai-Hai Plain in China, using daily precipitation data from 59 meteorological stations. Three commonly used statistical metrics (CC, RB, and RMSE) are adopted to quantitatively verify the accuracy of two satellite precipitation products. The assessment also takes into account the precipitation detection capability (POD, FAR, CSI, and ACC) and frequency of different precipitation intensities. The results show that the IMERG and 3B42V7 present strong correlation with meteorological stations observations at annual and monthly scales (CC > 0.90), whereas moderate at the daily scale (CC = 0.76 and 0.69 for IMERG and 3B42V7, respectively). The spatial variability of the annual and seasonal precipitation is well captured by these two satellite products. And spatial patterns of precipitation gradually decrease from south to north over the Huang-Huai-Hai Plain. Both IMERG and 3B42V7 products overestimate precipitation compared with the station observations, of which 3B42V7 has a lower degree of overestimation. Relative to the IMERG, annual precipitation estimates from 3B42V7 show lower RMSE (118.96 mm and 142.67 mm, respectively), but opposite at the daily, monthly, and seasonal scales. IMERG has a better precipitation detection capability than 3B42V7 (POD = 0.83 and 0.67, respectively), especially when detecting trace and solid precipitation. The two precipitation products tend to overestimate moderate (2–10 mm/d) and heavy (10–50 mm/d) precipitation events, but underestimate violent (>50 mm/d) precipitation events. The IMERG is not found capable to detecting precipitation events of different frequencies more precisely. In general, the accuracy of IMERG is better than 3B42V7 product in the Huang-Huai-Hai Plain. The IMERG satellite precipitation product with higher temporal and spatial resolutions can be regarded a reliable data sources in studying hydrological and climatic research.
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Paek, Sung Wook, Sivagaminathan Balasubramanian, Sangtae Kim, and Olivier de Weck. "Small-Satellite Synthetic Aperture Radar for Continuous Global Biospheric Monitoring: A Review." Remote Sensing 12, no. 16 (August 7, 2020): 2546. http://dx.doi.org/10.3390/rs12162546.
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Space-based radar sensors have transformed Earth observation since their first use by Seasat in 1978. Radar instruments are less affected by daylight or weather conditions than optical counterparts, suitable for continually monitoring the global biosphere. The current trends in synthetic aperture radar (SAR) platform design are distinct from traditional approaches in that miniaturized satellites carrying SAR are launched in multiples to form a SAR constellation. A systems engineering perspective is presented in this paper to track the transitioning of space-based SAR platforms from large satellites to small satellites. Technological advances therein are analyzed in terms of subsystem components, standalone satellites, and satellite constellations. The availability of commercial satellite constellations, ground stations, and launch services together enable real-time SAR observations with unprecedented details, which will help reveal the global biomass and their changes owing to anthropogenic drivers. The possible roles of small satellites in global biospheric monitoring and the subsequent research areas are also discussed.
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Belabid, Nasreddine, Feng Zhao, Luca Brocca, Yanbo Huang, and Yumin Tan. "Near-Real-Time Flood Forecasting Based on Satellite Precipitation Products." Remote Sensing 11, no. 3 (January 27, 2019): 252. http://dx.doi.org/10.3390/rs11030252.
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Floods, storms and hurricanes are devastating for human life and agricultural cropland. Near-real-time (NRT) discharge estimation is crucial to avoid the damages from flood disasters. The key input for the discharge estimation is precipitation. Directly using the ground stations to measure precipitation is not efficient, especially during a severe rainstorm, because precipitation varies even in the same region. This uncertainty might result in much less robust flood discharge estimation and forecasting models. The use of satellite precipitation products (SPPs) provides a larger area of coverage of rainstorms and a higher frequency of precipitation data compared to using the ground stations. In this paper, based on SPPs, a new NRT flood forecasting approach is proposed to reduce the time of the emergency response to flood disasters to minimize disaster damage. The proposed method allows us to forecast floods using a discharge hydrograph and to use the results to map flood extent by introducing SPPs into the rainfall–runoff model. In this study, we first evaluated the capacity of SPPs to estimate flood discharge and their accuracy in flood extent mapping. Two high temporal resolution SPPs were compared, integrated multi-satellite retrievals for global precipitation measurement (IMERG) and tropical rainfall measurement mission multi-satellite precipitation analysis (TMPA). The two products are evaluated over the Ottawa watershed in Canada during the period from 10 April 2017 to 10 May 2017. With TMPA, the results showed that the difference between the observed and modeled discharges was significant with a Nash–Sutcliffe efficiency (NSE) of −0.9241 and an adapted NSE (ANSE) of −1.0048 under high flow conditions. The TMPA-based model did not reproduce the shape of the observed hydrographs. However, with IMERG, the difference between the observed and modeled discharges was improved with an NSE equal to 0.80387 and an ANSE of 0.82874. Also, the IMERG-based model could reproduce the shape of the observed hydrographs, mainly under high flow conditions. Since IMERG products provide better accuracy, they were used for flood extent mapping in this study. Flood mapping results showed that the error was mostly within one pixel compared with the observed flood benchmark data of the Ottawa River acquired by RadarSat-2 during the flood event. The newly developed flood forecasting approach based on SPPs offers a solution for flood disaster management for poorly or totally ungauged watersheds regarding precipitation measurement. These findings could be referred to by others for NRT flood forecasting research and applications.
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Llauca, Harold, Waldo Lavado-Casimiro, Karen León, Juan Jimenez, Kevin Traverso, and Pedro Rau. "Assessing Near Real-Time Satellite Precipitation Products for Flood Simulations at Sub-Daily Scales in a Sparsely Gauged Watershed in Peruvian Andes." Remote Sensing 13, no. 4 (February 23, 2021): 826. http://dx.doi.org/10.3390/rs13040826.
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This study investigates the applicability of Satellite Precipitation Products (SPPs) in near real-time for the simulation of sub-daily runoff in the Vilcanota River basin, located in the southeastern Andes of Peru. The data from rain gauge stations are used to evaluate the quality of Integrated Multi-satellite Retrievals for GPM–Early (IMERG-E), Global Satellite Mapping of Precipitation–Near Real-Time (GSMaP-NRT), Climate Prediction Center Morphing Method (CMORPH), and HydroEstimator (HE) at the pixel-station level; and these SPPs are used as meteorological inputs for the hourly hydrological modeling. The GR4H model is calibrated with the hydrometric station of the longest record, and model simulations are also verified at one station upstream and two stations downstream of the calibration point. Comparing the sub-daily precipitation data observed, the results show that the IMERG-E product generally presents higher quality, followed by GSMaP-NRT, CMORPH, and HE. Although the SPPs present positive and negative biases, ranging from mild to moderate, they do represent the diurnal and seasonal variability of the hourly precipitation in the study area. In terms of the average of Kling-Gupta metric (KGE), the GR4H_GSMaP-NRT’ yielded the best representation of hourly discharges (0.686), followed by GR4H_IMERG-E’ (0.623), GR4H_Ensemble-Mean (0.617) and GR4H_CMORPH’ (0.606), and GR4H_HE’ (0.516). Finally, the SPPs showed a high potential for monitoring floods in the Vilcanota basin in near real-time at the operational level. The results obtained in this research are very useful for implementing flood early warning systems in the Vilcanota basin and will allow the monitoring and short-term hydrological forecasting of floods by the Peruvian National Weather and Hydrological Service.
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Ermakov, Dmitry, Alexey Kuzmin, Evgeny Pashinov, Victor Sterlyadkin, Andrey Chernushich, and Eugene Sharkov. "Comparison of Vertically Integrated Fluxes of Atmospheric Water Vapor According to Satellite Radiothermovision, Radiosondes, and Reanalysis." Remote Sensing 13, no. 9 (April 22, 2021): 1639. http://dx.doi.org/10.3390/rs13091639.
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The atmospheric advection of water vapor is one of the most important components of the planetary hydrological cycle. Radiosondes are a means for regular observations of water vapor fluxes. However, their data are sparse in space and time. A more complete picture is provided by reanalysis assimilating these data. However, a statistically representative check of the reanalysis estimates of the water vapor fluxes far from regularly operating weather stations is difficult. The previously proposed and developed method of satellite radiothermovision makes it possible to reconstruct the vertically integrated advective water vapor fluxes from satellite microwave radiometry. In this work, for the first time, the results of direct comparisons of long (5 year) time series of zonal vertically integrated daily water vapor fluxes based on the data of radiosondes, reanalysis, and satellite radiothermovision are performed and presented. It is shown that all the data series are statistically reliably correlated (at a confidence level of 0.995). The regression factor between the fluxes from reanalysis and satellite radiothermovision was close to 1, but with a noticeable bias (the latter were about 60 kg/(m·s) less on average). Grounds are given for the hypothesis that calculations based on satellite radiothermovision mainly characterize water vapor fluxes in the lower troposphere (up to heights of about 4 km). Its verification, as well as the analysis of the noted cases of violation of the correlation between the fluxes from satellite radiothermovision and reanalysis, requires further research.
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Chousianitis, Konstantinos, Xanthos Papanikolaou, George Drakatos, and G. Akis Tselentis. "NOANET: A Continuously Operating GNSS Network for Solid-Earth Sciences in Greece." Seismological Research Letters 92, no. 3 (March 17, 2021): 2050–64. http://dx.doi.org/10.1785/0220200340.
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Abstract The NOANET network is a continuously operating high-rate Global Navigation Satellite System (GNSS) network in Greece whose primary role is to enhance and support geophysical research employing GNSS data. This network is operated by the Institute of Geodynamics of the National Observatory of Athens and currently (September 2020) consists of 26 stations, most of which are located close to major seismogenic structures of Greece to optimally measure tectonic and seismically induced motions. All NOANET receivers are configured to record and collect data with a sampling rate of 1 Hz, although some of them also collect data every 5 Hz on their ring buffer. The network is committed to free and open data sharing within the scientific community, and the collected data are made available via the NOANET data repository and distribution point for all interested parties with no limitations. Integrity, validity, and quality checks of the acquired data are performed using a variety of software tools along with in-house developed programs to supervise the network performance and detect ill-formed data and/or awkward station behavior. In addition, the conventional low-rate GNSS observation data of all NOANET stations are routinely processed on a daily basis to supervise their performance through their position time series. Since the beginning of its establishment, the NOANET network has recorded a variety of deformation signals, and a large number of published papers have used GNSS data from stations that are part of NOANET to constrain, model, and interpret the nature of the associated geophysical phenomena.
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Zou, Lilong, Yan Wang, Iraklis Giannakis, Fabio Tosti, Amir M. Alani, and Motoyuki Sato. "Mapping and Assessment of Tree Roots Using Ground Penetrating Radar with Low-Cost GPS." Remote Sensing 12, no. 8 (April 20, 2020): 1300. http://dx.doi.org/10.3390/rs12081300.
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In this paper, we have presented a methodology combining ground penetrating radar (GPR) and a low-cost GPS receiver for three-dimensional detection of tree roots. This research aims to provide an effective and affordable testing tool to assess the root system of a number of trees. For this purpose, a low-cost GPS receiver was used, which recorded the approximate position of each GPR track, collected with a 500 MHz RAMAC shielded antenna. A dedicated post-processing methodology based on the precise position of the satellite data, satellite clock offsets data, and a local reference Global Navigation Satellite System (GNSS) Earth Observation Network System (GEONET) Station close to the survey site was developed. Firstly, the positioning information of local GEONET stations was used to filter out the errors caused by satellite position error, satellite clock offset, and ionosphere. In addition, the advanced Kalman filter was designed to minimise receiver offset and the multipath error, in order to obtain a high precision position of each GPR track. Kirchhoff migration considering near-field effect was used to identify the three-dimensional distribution of the root. In a later stage, a novel processing scheme was used to detect and clearly map the coarse roots of the investigated tree. A successful case study is proposed, which supports the following premise: the current scheme is an affordable and accurate mapping method of the root system architecture.
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Siqueira, Ricardo Almeida de, Daniel Alejandro Vila, and João Maria de Sousa Afonso. "The Performance of the Diurnal Cycle of Precipitation from Blended Satellite Techniques over Brazil." Remote Sensing 13, no. 4 (February 17, 2021): 734. http://dx.doi.org/10.3390/rs13040734.
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The knowledge of the diurnal cycle of precipitation is of extreme relevance to understanding the physical/dynamic processes associated with the spatial and temporal distribution of precipitation. The main difficulty of this task is the lack of surface precipitation information over certain regions on an hourly time scale and the low spatial representativeness of these data (normally surface gauges). In order to overcome these difficulties, the main objective of this study is to create a 3-h precipitation accumulation database from the gauge-adjusted daily regional precipitation products to resolve the diurnal cycle properly. This study also proposes to evaluate different methodologies for partitioning gauge-adjusted daily precipitation products, i.e., a product made by the combination of satellite estimates and surface gauge observations, into 3-h precipitation accumulation. Two methodologies based on the calculation of a conversion factor F between a daily gauge-adjusted product, combined scheme (CoSch, hereafter), and a non-gauge-adjusted one, the integrated multi-satellite retrievals for GPM (IMERG)-Early (IMERG, hereafter) were tested for this research. Hourly rain gauge stations for the period of 2015–2018 over Brazil were used to assess the performance of the proposed methodologies over the whole region and five sub-regions with homogeneous precipitation regimes. Standard statistical metrics and categorical indices related with the capability to detect rainfall events were used to compare the ability of each product to represent the diurnal cycle. The results show that the new 3-h CoSch products show better agreement with rainfall gauge stations when compared with IMERG, better capturing the diurnal cycle of precipitation. The biggest improvement was over northeastern region close to the coast, where IMERG was not able to capture the diurnal cycle properly. One of the proposed methodologies (CoSchB) performed better on the critical success index and equitable threat score metrics, suggesting that this is the best product over the two. The downside, when compared with the other methodology (CoSchA), was a slight increase in the values of bias and mean absolute error, but still at acceptable levels.
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Brewin, Robert J. W., Werenfrid Wimmer, Philip J. Bresnahan, Tyler Cyronak, Andreas J. Andersson, and Giorgio Dall’Olmo. "Comparison of a Smartfin with an Infrared Sea Surface Temperature Radiometer in the Atlantic Ocean." Remote Sensing 13, no. 5 (February 24, 2021): 841. http://dx.doi.org/10.3390/rs13050841.
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The accuracy and precision of satellite sea surface temperature (SST) products in nearshore coastal waters are not well known, owing to a lack of in-situ data available for validation. It has been suggested that recreational watersports enthusiasts, who immerse themselves in nearshore coastal waters, be used as a platform to improve sampling and fill this gap. One tool that has been used worldwide by surfers is the Smartfin, which contains a temperature sensor integrated into a surfboard fin. If tools such as the Smartfin are to be considered for satellite validation work, they must be carefully evaluated against state-of-the-art techniques to quantify data quality. In this study, we developed a Simple Oceanographic floating Device (SOD), designed to float on the ocean surface, and deployed it during the 28th Atlantic Meridional Transect (AMT28) research cruise (September and October 2018). We attached a Smartfin to the underside of the SOD, which measured temperature at a depth of ∼0.1 m, in a manner consistent with how it collects data on a surfboard. Additional temperature sensors (an iButton and a TidbiT v2), shaded and positioned a depth of ∼1 m, were also attached to the SOD at some of the stations. Four laboratory comparisons of the SOD sensors (Smartfin, iButton and TidbiT v2) with an accurate temperature probe (±0.0043 K over a range of 273.15 to 323.15 K) were also conducted during the AMT28 voyage, over a temperature range of 290–309 K in a recirculating water bath. Mean differences (δ), referenced to the temperature probe, were removed from the iButton (δ=0.292 K) and a TidbiT v2 sensors (δ=0.089 K), but not from the Smartfin, as it was found to be in excellent agreement with the temperature probe (δ=0.005 K). The SOD was deployed for 20 min periods at 62 stations (predawn and noon) spanning 100 degrees latitude and a gradient in SST of 19 K. Simultaneous measurements of skin SST were collected using an Infrared Sea surface temperature Autonomous Radiometer (ISAR), a state-of-the-art instrument used for satellite validation. Additionally, we extracted simultaneous SST measurements, collected at slightly different depths, from an underway conductivity, temperature and depth (CTD) system. Over all 62 stations, the mean difference (δ) and mean absolute difference (ϵ) between Smartfin and the underway CTD were −0.01 and 0.06 K respectively (similar results obtained from comparisons between Smartfin and iButton and Smartfin and TidbiT v2), and the δ and ϵ between Smartfin and ISAR were 0.09 and 0.12 K respectively. In both comparisons, statistics varied between noon and predawn stations, with differences related to environmental variability (wind speed and sea-air temperature differences) and depth of sampling. Our results add confidence to the use of Smartfin as a citizen science tool for evaluating satellite SST data, and data collected using the SOD and ISAR were shown to be useful for quantifying near-surface temperature gradients.
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Alemu, Woubet G., and Michael C. Wimberly. "Evaluation of Remotely Sensed and Interpolated Environmental Datasets for Vector-Borne Disease Monitoring Using In Situ Observations over the Amhara Region, Ethiopia." Sensors 20, no. 5 (February 28, 2020): 1316. http://dx.doi.org/10.3390/s20051316.
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Despite the sparse distribution of meteorological stations and issues with missing data, vector-borne disease studies in Ethiopia have been commonly conducted based on the relationships between these diseases and ground-based in situ measurements of climate variation. High temporal and spatial resolution satellite-based remote-sensing data is a potential alternative to address this problem. In this study, we evaluated the accuracy of daily gridded temperature and rainfall datasets obtained from satellite remote sensing or spatial interpolation of ground-based observations in relation to data from 22 meteorological stations in Amhara Region, Ethiopia, for 2003–2016. Famine Early Warning Systems Network (FEWS-Net) Land Data Assimilation System (FLDAS) interpolated temperature showed the lowest bias (mean error (ME) ≈ 1–3 °C), and error (mean absolute error (MAE) ≈ 1–3 °C), and the highest correlation with day-to-day variability of station temperature (COR ≈ 0.7–0.8). In contrast, temperature retrievals from the blended Advanced Microwave Scanning Radiometer on Earth Observing Satellite (AMSR-E) and Advanced Microwave Scanning Radiometer 2 (AMSR2) passive microwave and Moderate-resolution Imaging Spectroradiometer (MODIS) land-surface temperature data had higher bias and error. Climate Hazards group InfraRed Precipitation with Stations (CHIRPS) rainfall showed the least bias and error (ME ≈ −0.2–0.2 mm, MAE ≈ 0.5–2 mm), and the best agreement (COR ≈ 0.8), with station rainfall data. In contrast FLDAS had the higher bias and error and the lowest agreement and Global Precipitation Mission/Tropical Rainfall Measurement Mission (GPM/TRMM) data were intermediate. This information can inform the selection of geospatial data products for use in climate and disease research and applications.
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Al-Yaari, A., S. Dayau, C. Chipeaux, C. Aluome, A. Kruszewski, D. Loustau, and J. P. Wigneron. "The AQUI Soil Moisture Network for Satellite Microwave Remote Sensing Validation in South-Western France." Remote Sensing 10, no. 11 (November 20, 2018): 1839. http://dx.doi.org/10.3390/rs10111839.
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Global soil moisture (SM) products are currently available thanks to microwave remote sensing techniques. Validation of these satellite-based SM products over different vegetation and climate conditions is a crucial step. INRA (National Institute of Agricultural Research) has set up the AQUI SM and soil temperature in situ network (composed of three main sites Bouron, Bilos, and Hermitage), over a flat area of dense pine forests, in South-Western France (the Bordeaux–Aquitaine region) to validate the Soil Moisture and Ocean salinity (SMOS) satellite SM products. SMOS was launched in 2009 by the European Space Agency (ESA). The aims of this study are to present the AQUI network and to evaluate the SMOS SM product (in the new SMOS-IC version) along with other microwave SM products such as the active ASCAT (Advanced Scatterometer) and the ESA combined (passive and active) CCI (Climate Change Initiative) SM retrievals. A first comparison, using Pearson correlation, Bias, RMSE (Root Mean Square Error), and Un biased RMSE (ubRMSE) scores, between the 0–5 cm AQUI network and ASCAT, CCI, and SMOS SM products was conducted. In general all the three products were able to reproduce the annual cycle of the AQUI in situ observations. CCI and ASCAT had best and similar correlations (R~0.72) over the Bouron and Bilos sites. All had comparable correlations over the Hermitage sites with overall average values of 0.74, 0.68, and 0.69 for CCI, SMOS-IC, and ASCAT, respectively. Considering anomalies, correlation values decreased for all products with best ability to capture day to day variations obtained by ASCAT. CCI (followed by SMOS-IC) had the best ubRMSE values (mostly < 0.04 m3/m3) over most of the stations. Although the region is highly impacted by radio frequency interferences, SMOS-IC followed correctly the in situ SM dynamics. All the three remotely-sensed SM products (except SMOS-IC over some stations) overestimated the AQUI in situ SM observations. These results demonstrate that the AQUI network is likely to be well-suited for satellite microwave remote sensing evaluations/validations.
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Werner, Małgorzata, Maciej Kryza, and Jakub Guzikowski. "Can Data Assimilation of Surface PM2.5 and Satellite AOD Improve WRF-Chem Forecasting? A Case Study for Two Scenarios of Particulate Air Pollution Episodes in Poland." Remote Sensing 11, no. 20 (October 12, 2019): 2364. http://dx.doi.org/10.3390/rs11202364.
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Based on the Weather Research and Forecasting model with Chemistry (WRF-Chem) model and Gridpoint Statistical Interpolation (GSI) assimilation tool, a forecasting system was used for two selected episodes (winter and summer) over Eastern Europe. During the winter episode, very high particular matter (PM2.5, diameter less than 2.5 µm) concentrations, related to low air temperatures and increased emission from residential heating, were measured at many stations in Poland. During the summer episode, elevated aerosol optical depth (AOD), likely related to the transport of pollution from biomass fires, was observed in Southern Poland. Our aim is to verify if there is a relevant positive impact of surface and satellite data assimilation (DA) on modeled PM2.5 concentrations, and to assess whether there are significant differences in the DA’s impact on concentrations between the two seasons. The results show a significant difference in the impact of surface and satellite DA on the model results between the summer and winter episode, which to a large degree is related to the availability of the satellite data. For example, the application of satellite DA raises the factor of two statistic from 0.18 to 0.78 for the summer episode, whereas this statistic remains unchanged (0.71) for the winter. The study suggests that severe winter air pollution episodes in Poland and Eastern Europe in general, often related to the dense cover of low clouds, will benefit from the assimilation of surface observations rather than satellite data, which can be very sparse in such meteorological situations. In contrast, the assimilation of satellite data can have a greater positive impact on the model results during summer than the assimilation of surface data for the same period.
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Liu, Yuling, Yunyue Yu, Peng Yu, Heshun Wang, and Yuhan Rao. "Enterprise LST Algorithm Development and Its Evaluation with NOAA 20 Data." Remote Sensing 11, no. 17 (August 24, 2019): 2003. http://dx.doi.org/10.3390/rs11172003.
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Satellite land surface temperatures (LSTs) have been routinely produced for decades from a variety of polar-orbiting and geostationary satellites, which makes it possible to generate LST climate data globally. However, consistency of the satellite LSTs from different satellite missions is a concern for such purpose; an enterprise satellite LST algorithm is desired for the LST production through different satellite missions, or at the least, through series satellites of a satellite mission. The enterprise LST algorithm employs the split window technique and uses the emissivity explicitly in its formula. This research focuses on the enterprise LST algorithm design, development and its evaluations with the National Oceanic and Atmospheric Administration’s (NOAA) 20 (N20) Visible Infrared Imaging Radiometer Suite (VIIRS) data available since 5 January 2018. In this study, the enterprise LST algorithm was evaluated using simulation dataset consisting of over 2000 profiles from SeeBor collection and the results show a bias of 0.19 K and 0.34 K and standard deviation of 0.48 K and 0.69 K for nighttime and daytime, respectively. The in situ observations from seven NOAA Surface Radiation budget (SURFRAD) sites and two Baseline Surface Radiation Network (BSRN) sites were used for LST validation. The results indicate a bias of −0.3 K and a root mean square error (RMSE) of 2.06 K for SURFRAD stations and a bias of 0.2 K and a RMSE of ~2 K for BSRN sites. Further, the cross-satellite analysis presents a bias of 0.7 K and an RMSE of 1.9 K for comparisons with AQUA MODIS LST (MYD11_L2, Collection 6). The enterprise N20 VIIRS LST product reached the provisional maturity in February 2019 and is ready for users to use in their applications.
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Kaczmarek, Adrian, and Bernard Kontny. "Identification of the Noise Model in the Time Series of GNSS Stations Coordinates Using Wavelet Analysis." Remote Sensing 10, no. 10 (October 10, 2018): 1611. http://dx.doi.org/10.3390/rs10101611.
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Analysis of the time series of coordinates is extremely important in geodynamic research. Indeed, the correct interpretation of coordinate changes may facilitate an understanding of the diverse geophysical processes taking place in the earth’s crust. At present, when rigorously processing global navigation satellite system (GNSS) observations, the influence of deformations in the surface of the earth’s crust is not considered. This article presents signal modelling for the influence on the analysis of noise occurring in the time series of GNSS station coordinates. The modelling of coordinate time series was undertaken using the classic least-squares estimation (LSE) method and the inverse continuous wavelet transform (CWT). In order to determine the type of noise character, the coefficient spectral index was used. Analyses have demonstrated that the nature of noise in measurement data does not depend on the signal estimation method. The differences between classic modelling (LSE) of the time series with annual and semiannual oscillation and signal reconstruction are very small ( Δ κ = 0.0 ÷−0.2).
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Wu, Xiaotao, Guihua Lu, Zhiyong Wu, Hai He, Tracy Scanlon, and Wouter Dorigo. "Triple Collocation-Based Assessment of Satellite Soil Moisture Products with In Situ Measurements in China: Understanding the Error Sources." Remote Sensing 12, no. 14 (July 15, 2020): 2275. http://dx.doi.org/10.3390/rs12142275.
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With the increasing utilization of satellite-based soil moisture products, a primary challenge is knowing their accuracy and robustness. This study presents a comprehensive assessment over China of three widely used global satellite soil moisture products, i.e., Soil Moisture Active Passive (SMAP), European Space Agency (ESA) Climate Change Initiative (CCI) Soil Moisture, Soil Moisture and Ocean Salinity (SMOS). In situ soil moisture from 1682 stations and Variable Infiltration Capacity (VIC) model are used to evaluate the performance of SMAP_L3, ESA_CCI_SM_COMBINED, SMOS_CATDS_L3 from 31 March 2015 to 3 June 2018. The Triple Collocation (TC) approach is used to minimize the uncertainty (e.g., scale issue) during the validation process. The TC analysis is conducted using three triplets, i.e., [SMAP-Insitu-VIC], [CCI-Insitu-VIC], [SMOS-Insitu-VIC]. In general, SMAP is the most reliable product, reflecting the main spatiotemporal characteristics of soil moisture, while SMOS has the lowest accuracy. The results demonstrate that the overall root mean square error of SMAP, CCI, SMOS is 0.040, 0.028, 0.107 m3m−3, respectively. The overall temporal correlation coefficient of SMAP, CCI, SMOS is 0.68, 0.65, 0.38, respectively. The overall fractional root mean square error of SMAP, CCI, SMOS is 0.707, 0.750, 0.897, respectively. In irrigated areas, the accuracy of CCI is reduced due to the land surface model (which does not consider irrigation) used for the rescaling of the CCI_COMBINED soil moisture product during the merging process, while SMAP and SMOS preserve the irrigation signal. The quality of SMOS is most strongly impacted by land surface temperature, vegetation, and soil texture, while the quality of CCI is the least affected by these factors. With the increase of Radio Frequency Interference, the accuracy of SMOS decreases dramatically, followed by SMAP and CCI. Higher representativeness error of in situ stations is noted in regions with higher topographic complexity. This study helps to provide a guideline for the application of satellite soil moisture products in scientific research and gives some references (e.g., modify data algorithm according to the main error sources) for improving the data quality.
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Rutkowska, Miłosława, and Marcin Jagoda. "SLR Technique Used For Description Of The Earth Elasticity." Artificial Satellites 50, no. 3 (September 1, 2015): 127–41. http://dx.doi.org/10.1515/arsa-2015-0010.
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Abstract We present estimated values for the global elastic parameters (h2, l2) derived from the analysis of Satellite Laser Ranging (SLR) data. We analyse SLR data for LAGEOS 1 and LAGEOS 2 and for two low satellites, STARLETTE and STELLA, collected over a period of 2.5 years, from January 1 2005 to July 1 2007, from 18 globally distributed ground stations. The adjusted final values (h2, l2) for all satellites are compared. A major discrepancy between the two solutions was only found for the Shida number l2. Computations were performed using GEODYN II NASA/GSFC software. The following analysis is the continuation of our research published in Jagoda and Rutkowska (2013); that analysis was conducted separately for the two low satellites, STELLA and STARLETTE (separately for STELLA and separately for STARLETTE) whereas in this study we present the results of determining h2 and l2 parameters obtained from the joint observation of the STELLA and STARLETTE satellites (STARLETTE + STELLA) and joint observation of high satellites: LAGEOS 1 and LAGEOS 2 (LAGEOS 1 + LAGEOS 2). The combination of the observation aims at an increased stability of the estimates and reduced errors of the means of the parameters being determined.
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Sun, Peng, Kefei Zhang, Suqin Wu, Moufeng Wan, and Yun Lin. "Retrieving Precipitable Water Vapor from Real-Time Precise Point Positioning Using VMF1/VMF3 Forecasting Products." Remote Sensing 13, no. 16 (August 16, 2021): 3245. http://dx.doi.org/10.3390/rs13163245.
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Real-time precise point positioning (RT-PPP) has become a powerful technique for the determination of the zenith tropospheric delay (ZTD) over a GPS (global positioning system) or GNSS (global navigation satellite systems) station of interest, and the follow-on high-precision retrieval of precipitable water vapor (PWV). The a priori zenith hydrostatic delay (ZHD) and the mapping function used in the PPP approach are the two factors that could affect the accuracy of the PPP-based ZTD significantly. If the in situ atmospheric pressure is available, the Saastamoinen model can be used to determine ZHD values, and the model-predicted ZHD results are of high accuracy. However, not all GPS/GNSS are equipped with an in situ meteorological sensor. In this research, the daily forecasting ZHD and mapping function values from VMF1 forecasting (VMF1_FC) and VMF3 forecasting (VMF3_FC) products were used for the determination of the GPS-derived PWV. The a priori ZHDs derived from VMF1_FC and VMF3_FC were first evaluated by comparing against the reference ZHDs from globally distributed radiosonde stations. GPS observations from 41 IGS stations that have co-located radiosonde stations during the period of the first half of 2020 were used to test the quality of GPS-ZTD and GPS-PWV. Three sets of ZTDs estimated from RT-PPP solutions using the a priori ZHD and mapping function from the following three VMF products were evaluated: (1) VMF1_FC; (2) VMF3_FC (resolution 5° × 5°); (3) VMF3_FC (resolution 1° × 1°). The results showed that, when the ZHDs from 443 globally distributed radiosonde stations from 1 July 2018 to 30 June 2021 were used as the reference, the mean RMSEs of the ZHDs from the three VMF products were 5.9, 5.4, and 4.3 mm, respectively. The ZTDs estimated from RT-PPP at 41 selected IGS stations were compared with those from IGS, and the results showed that the mean RMSEs of the ZTDs of the 41 stations from the three PPP solutions were 8.6, 9.0, and 8.6 mm, respectively, and the mean RMSEs of the PWV converted from their corresponding ZWDs were 1.9, 2.4, and 1.7 mm, respectively, in comparison with the reference PWV from co-located radiosonde stations. The results suggest that the a priori ZHD and mapping function from VMF1_FC and VMF3_FC can be used for the precise determination of real-time GPS/GNSS-PWV in most regions, especially the VMF3_FC (resolution 1° × 1°) product.
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Olive, Xavier. "FDI(R) for satellites: How to deal with high availability and robustness in the space domain?" International Journal of Applied Mathematics and Computer Science 22, no. 1 (March 1, 2012): 99–107. http://dx.doi.org/10.2478/v10006-012-0007-8.
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FDI(R) for satellites: How to deal with high availability and robustness in the space domain?The European leader for satellite systems and at the forefront of orbital infrastructures, Thales Alenia Space, is a joint venture between Thales (67%) and Finmeccanica (33%) and forms with Telespazio a Space Alliance. Thales Alenia Space is a worldwide reference in telecoms, radar and optical Earth observation, defence and security, navigation and science. It has 11 industrial sites in 4 European countries (France, Italy, Spain and Belgium) with over 7200 employees worldwide. Satellite evolution and the wish to design more autonomous missions imply the enhancement of the satellite architecture and special attention paid to fault management (i.e., Fault Detection, Isolation and Recovery, or FDIR, in space). Nevertheless, the constraints on FDIR techniques and strategies remain the same as for standard missions: robustness, reactive detection, quick isolation/identification and validation. This paper gives an introduction to Fault Tolerance (FT) in the space domain and some principles for the coming FT architectures. The current context of FDIR is presented by describing the approach implemented on telecommunication satellites and, more precisely, on one of the most FDIR sensible subsystems: the AOCS (Attitude and Orbit Control System). Following the current state of FDIR in the space domain, some perspectives are given such as a centralized distributed FDIR strategy for the next generation of autonomous satellites as well as some research tracks and hybrid diagnosis.
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Hernandez-Marin, Martin, Ruben Esquivel-Ramirez, Mario Eduardo Zermeño-De-Leon, Lilia Guerrero-Martinez, Jesus Pacheco-Martinez, and Thomas J. Burbey. "Ongoing research on the pumping-induced land deformation in the Aguascalientes Valley: an analysis of the recent data of vertical deformation, groundwater level variations and local seismicity." Proceedings of the International Association of Hydrological Sciences 382 (April 22, 2020): 99–102. http://dx.doi.org/10.5194/piahs-382-99-2020.
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Abstract. In the Aguascalientes valley, middle Mexico, the demand of groundwater from the local aquifer system was suddenly increased after the late 1970s. Since then, several related problems have been occurring or become critical such as land subsidence, ground fissuring, and low-magnitude earthquakes. The most recent data of vertical deformation from PSInSAR, groundwater levels, and earthquakes, has provided critical information regarding the relationship amongst all these processes. In particular, that related to land subsidence, earth fissuring and seismicity. Regarding this, more satellite imagery and data from GPS stations are being revised as a possibility of a more generalized vertical deformation derived with low-magnitude seismicity. A particular seismic event recorded on 6 April 2019 has revealed critical information on the close association between vertical displacements occurred in active faults and low-magnitude seismic events.
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Lee, Dabin, Jin-Yong Jeong, Hyo Keun Jang, Jun-Oh Min, Myung Joon Kim, Seok Hyun Youn, Taehee Lee, and Sang Heon Lee. "Comparison of Particulate Organic Carbon to Chlorophyll-a Ratio Based on the Ocean Color Satellite Data at the Ieodo and Socheongcho Ocean Research Stations." Journal of Coastal Research 90, sp1 (September 2, 2019): 267. http://dx.doi.org/10.2112/si90-033.1.
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Gentilucci, Matteo, Margherita Bufalini, Marco Materazzi, Maurizio Barbieri, Domenico Aringoli, Piero Farabollini, and Gilberto Pambianchi. "Calculation of Potential Evapotranspiration and Calibration of the Hargreaves Equation Using Geostatistical Methods over the Last 10 Years in Central Italy." Geosciences 11, no. 8 (August 19, 2021): 348. http://dx.doi.org/10.3390/geosciences11080348.
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Potential evapotranspiration (ET0) is an indicator of great interest for water budget analysis and the agricultural sector. Therefore, the purpose of this study was to make the calculation reliable even if only the temperature data were present. In this research, the ET0 was initially calculated for a limited number of weather stations (12) using the Penman–Monteith method. In some cases, the simplified Penman–Monteith formula was adopted, while in others, as in the case of mountain weather stations, the complete formula was employed to consider the differences in vegetation, deduced from satellite surveys. Subsequently, the ET0 was calculated with the Hargreaves–Samani (HS) formula, calibrating the Hargreaves coefficient, through the spatialization of ET0, by the geostatistical method. The results showed a high reliability of the HS method in comparison with simplified PM (PM) method, and complete Penman–Monteith (cPM) method, with a minimum calibration of the empirical Hargreaves coefficient. In particular, a very good correlation between the results obtained in the mountain environment with the uncalibrated HS method and the cPM method was also observed in this area, while PM showed discordant and much higher results than ET0 compared with the other methods. It follows that this procedure allowed a more accurate estimate of potential evapotranspiration with a view to territory management, both in terms of water resources and the irrigation needs of the vegetation.
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Huang, Yanyan, Hongli Zhao, Yunzhong Jiang, and Xin Lu. "A Method for the Optimized Design of a Rain Gauge Network Combined with Satellite Remote Sensing Data." Remote Sensing 12, no. 1 (January 5, 2020): 194. http://dx.doi.org/10.3390/rs12010194.
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A well-designed rain gauge network can provide precise and detailed rainfall data for earth science research; meanwhile, satellite precipitation data has been developed to generate more real spatial features, which provides new data support for the improvement of ground station network design methods. In this paper, satellite precipitation data are introduced into the design of a rain gauge network and an optimized method for designing a rain gauge network that comprehensively considers the information content, spatiotemporality, and accuracy (ISA) of the data is proposed. After screening the potential stations, the average spatial information index of the rain gauge network, which is calculated from remote sensing data, is used to address the shortcomings of applying spatial information from single-use measurement data. Then, the greedy ranking algorithm is used to rank the order in which the rain gauges are added to the network. The results of the rain gauge network design in the upper reaches of the Chaobai river show that compared with two methods that do not consider spatiality or use only measured data to consider spatiality, the proposed method performs better in terms of the spatial layout and accuracy verification. This study provides new ideas and references for the design of hydrological station networks and explores the use of remote sensing data for the layout of ground-based station networks.
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Draper, Clara, and Rolf H. Reichle. "Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses." Monthly Weather Review 147, no. 6 (May 23, 2019): 2163–88. http://dx.doi.org/10.1175/mwr-d-18-0393.1.
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Abstract A newly developed, weakly coupled land and atmosphere data assimilation system for NASA’s Global Earth Observing System model is presented, and used to demonstrate the benefit of assimilating satellite soil moisture into an atmospheric reanalysis. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The atmosphere is sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally, the soil moisture assimilation induced some substantial improvements. For example, in a large region spanning from western Europe across southern Russia, the soil moisture assimilation decreased the RMSE against independent station observations of daily maximum 2-m temperature () by up to 0.4 K, and of 2-m specific humidity (q2m) by up to 0.5 g kg−1. Over all available stations, the mean RMSE was reduced from 2.82 to 2.79 K, while the mean q2m RMSE was reduced from 1.25 to 1.20 g kg−1. The soil moisture assimilation also reduced the mean RMSE across 29 flux tower sites from 34.2 to 32.6 W m−2 for latent heating, and from 37.7 to 36.5 W m−2 for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.
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Jonathan, Bamber, and Bentley Charles r. "A comparison of satellite-altimetry and ice-thickness measurements of the Ross Ice Shelf, Antarctica." Annals of Glaciology 20 (1994): 357–64. http://dx.doi.org/10.3189/1994aog20-1-357-364.
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The launch of ERS-l provides coverage, by satellite altimetry, of a large part of the Ross Ice Shelf ineluding areas of input from Byrd Glacier and Ice Streams D and E. Five 35 d repeats of fast-delivery data, comprising approximately 100000 height estimates, have been used to produce a Digital Elevation Model (DEM) of the Ross Icc Shelf north of 81.5° S. Careful filtering of the altimeter data, which removed about 30% of the measurements, ensured that only valid values were used. The data were grldded to produce a DEM with a cell size of 10km. Repeatability of the data was assessed from an analysis of crossing points of ascending and descending tracks. The rms cross-over difference for the ice shelf was 0.94 m. Using the five repeat tracks gave a random error of 0.30 m for an averaged height measurement. Regionally correlated errors in the orbit and geoid add a systematic long wavelength bias of approximately 2m to the final elevation estimate. Two of the latest geoid models, OSU91-A and JGMI, were compared with the available in situ data and hYdrostatic models based on ice and water densities.The altimetry was compared with ice-thickness data from Ross Icc Shelf Geophysical and Glaciological Survey (RIGGS) stations and Scott Polar Research Institute radio-echo-sounding surveys undertaken in the 1970s. Differences between the DEM and heights calculated from ice thicknesses and a standard density -depth equation lie, in general, within the combined measurement errors. There are, however, several areas where this is not the case. Prominent north-south stripes of different ice thickness shown on a RIGGS map apparently do not exist. Low elevations are associated with high-density ice draining from East Antarctic outlet glaciers. The grounding line of Icc Streams D and E and an ice plain behind it are clearly demarcated by the break in surface slope. Grounded ice north of Steershead is also observed
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Jonathan, Bamber, and Bentley Charles r. "A comparison of satellite-altimetry and ice-thickness measurements of the Ross Ice Shelf, Antarctica." Annals of Glaciology 20 (1994): 357–64. http://dx.doi.org/10.1017/s0260305500016694.
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The launch of ERS-l provides coverage, by satellite altimetry, of a large part of the Ross Ice Shelf ineluding areas of input from Byrd Glacier and Ice Streams D and E. Five 35 d repeats of fast-delivery data, comprising approximately 100000 height estimates, have been used to produce a Digital Elevation Model (DEM) of the Ross Icc Shelf north of 81.5° S. Careful filtering of the altimeter data, which removed about 30% of the measurements, ensured that only valid values were used. The data were grldded to produce a DEM with a cell size of 10km. Repeatability of the data was assessed from an analysis of crossing points of ascending and descending tracks. The rms cross-over difference for the ice shelf was 0.94 m. Using the five repeat tracks gave a random error of 0.30 m for an averaged height measurement. Regionally correlated errors in the orbit and geoid add a systematic long wavelength bias of approximately 2m to the final elevation estimate. Two of the latest geoid models, OSU91-A and JGMI, were compared with the available in situ data and hYdrostatic models based on ice and water densities.The altimetry was compared with ice-thickness data from Ross Icc Shelf Geophysical and Glaciological Survey (RIGGS) stations and Scott Polar Research Institute radio-echo-sounding surveys undertaken in the 1970s. Differences between the DEM and heights calculated from ice thicknesses and a standard density -depth equation lie, in general, within the combined measurement errors. There are, however, several areas where this is not the case. Prominent north-south stripes of different ice thickness shown on a RIGGS map apparently do not exist. Low elevations are associated with high-density ice draining from East Antarctic outlet glaciers. The grounding line of Icc Streams D and E and an ice plain behind it are clearly demarcated by the break in surface slope. Grounded ice north of Steershead is also observed
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An, Hao, Wei Yan, Shuangshuang Bian, and Shuo Ma. "Rain Monitoring with Polarimetric GNSS Signals: Ground-Based Experimental Research." Remote Sensing 11, no. 19 (October 1, 2019): 2293. http://dx.doi.org/10.3390/rs11192293.
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In recent years, there has been a preliminary research on monitoring rainfall information based on polarimetric Global Navigation Satellite System (GNSS) signals, which is a quite novel concept. After previous theoretical research on monitoring rain based on polarimetric phase shift of GNSS signals, the paper aims to detect rain using polarimetric GNSS signals from a ground-based experiment. Firstly, a conical horn antenna specially designed for receiving dual-polarized (H, horizontal, and V, vertical) GNSS signals was developed, and an experimental system for polarimetric GNSS rain detection was built. Then, taking Global Positioning System (GPS) satellites as signal source, a ground-based experiment was carried out at a mountain in Nanjing, where heavy rain tends to occur frequently in rainy season. Additionally, a data processing algorithm mainly following Padullés et al. (2016) to solve the problems of quality control, unlocking, hardware effect, phase ambiguity, multipath effect was applied independently to this ground-based data from the polarimetric GNSS rain detection system. Also, the multi-source data from nearby weather radar and weather stations was used for verification. Results from 14 GPS satellites show that the obtained phase shift is zero in all no-rain days while it is not zero during rainy days, which is in accordance with the actual situation. Compared with weather radar and rain gauges’ data, the results verify that the phase shift is caused by rain. Besides, when individual cases are examined, many show that their tendencies of accumulated phase shift are quite similar to that of a weather station’s rainfall data, even some correlation coefficients are up to 0.99. These demonstrate the reliability of our experimental system and the feasibility of the data processing algorithm. This study will provide technical support for future spaceborne experiment, which has promising applications in global rain monitoring.
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Wu, Kai, Ce Ji, Lei Luo, and Xinyuan Wang. "Simulation Study of Moon-Based InSAR Observation for Solid Earth Tides." Remote Sensing 12, no. 1 (January 1, 2020): 123. http://dx.doi.org/10.3390/rs12010123.
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The observation of solid earth tides (SET) provides an important basis for understanding the structure of the earth’s interior, and has long been the focus of research in geoscience. However, actually, there still exist some limitations in capturing its global-scale information only with ground stations. Remote sensing technology can realize large-scale deformation monitoring of high point density constantly. However, it is still difficult for the artificial satellite system to meet the requirements of SET monitoring in terms of field of view and temporal resolution now. In this work, the moon is hypothesized as a new platform for SET observation combined with interferometric synthetic aperture radar (InSAR) technology. Based on the tidal model and lunar ephemeris, the spatial and temporal characteristics of the SET from the lunar view were analyzed. Furthermore, the calculations demonstrate that more abundant SET information can be observed in this view. After comparing various observation modes, the single-station with repeat-pass differential InSAR was selected for this simulation. We mainly considered the restriction of observation geometry on moon-based InSAR under three signal bandwidths, thereby providing a reference for the sensor design. The results demonstrate that the moon-based platform offers the potential to become an optimal SET observation method.
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Gao, Wenliang, Jingxiang Gao, Liu Yang, Mingjun Wang, and Wenhao Yao. "A Novel Modeling Strategy of Weighted Mean Temperature in China Using RNN and LSTM." Remote Sensing 13, no. 15 (July 30, 2021): 3004. http://dx.doi.org/10.3390/rs13153004.
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In the meteorology of Global Navigation Satellite System, the weighted mean temperature (Tm) is a key parameter in the process of converting the zenith wetness delay into precipitable water vapor, and it plays an important role in water vapor monitoring. In this research, two deep learning algorithms, namely, recurrent neural network (RNN) and long short-term memory neural network (LSTM), were used to build a high-precision weighted mean temperature model for China using their excellent time series memory capability. The model needs site location information and measured surface temperature to predict the weighted mean temperature. We used data from 118 stations in and around China provided by the Integrated Global Radiosonde Archive from 2010 to 2015 to train the model and data from 2016 for model testing. The root mean square error (RMSE) of the RNN_Tm and LSTM_Tm models were 3.01 K and 2.89 K, respectively. Compared with the values calculated by the empirical GPT3 model, the accuracy was improved by 31.1% (RNN_Tm) and 33.9% (LSTM_Tm). In addition, we selected another 10 evenly distributed stations in China and used the constructed model to test the prediction capability of the weighted mean temperature from 2010 to 2016. The RMSE values were 2.95 K and 2.86 K, which proved that the model also exhibits high generalization in non-modeling sites in China. In general, the RNN_Tm and LSTM_Tm models have a good performance in weighted mean temperature prediction.
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Zapata-Rios, X., P. D. Brooks, P. A. Troch, J. McIntosh, and C. Rasmussen. "Influence of climate variability on water partitioning and effective energy and mass transfer (EEMT) in a semi-arid critical zone." Hydrology and Earth System Sciences Discussions 12, no. 8 (August 17, 2015): 7933–69. http://dx.doi.org/10.5194/hessd-12-7933-2015.
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Abstract. The Critical Zone (CZ) is the heterogeneous, near-surface layer of the planet that regulates life-sustaining resources. Previous research has demonstrated that a quantification of the influxes of effective energy and mass (EEMT) to the CZ can predict its structure and function. In this study, we quantify how climate variability in the last three decades (1984–2012) has affected water availability and the temporal trends in EEMT. This study takes place in the 1200 km2 upper Jemez River Basin in northern New Mexico. The analysis of climate, water availability, and EEMT was based on records from two high elevation SNOTEL stations, PRISM data, catchment scale discharge, and satellite derived net primary productivity (MODIS). Records from the two SNOTEL stations showed clear increasing trends in winter and annual temperatures (+1.0–1.3 °C decade−1; +1.2–1.4 °C decade−1, respectively), decreasing trends in winter and annual precipitation (−41.6–51.4 mm decade−1; −69.8–73.2 mm decade−1, respectively) and maximum Snow Water Equivalent (SWE; −33.1–34.7 mm decade−1). The water partitioning fluxes at the basin scale showed statistically significant decreasing trends in precipitation (−61.7 mm decade−1), discharge (−17.6 mm decade−1) and vaporization (−45.7 mm decade−1). Similarly Q50, an indicator of snowmelt timing, is occurring 4.3 days decade−1 earlier. Results from this study indicated a decreasing trend in water availability, a reduction in forest productivity (4 g C m−2 per 10 mm of reduction in Precipitation) and EEMT (1.2–1.3 MJ m2 decade−1). These changes in EEMT point towards a hotter, drier and less productive ecosystem which may alter critical zone processes in high elevation semi-arid systems.
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Dabrowska-Zielinska, Katarzyna, Jan Musial, Alicja Malinska, Maria Budzynska, Radoslaw Gurdak, Wojciech Kiryla, Maciej Bartold, and Patryk Grzybowski. "Soil Moisture in the Biebrza Wetlands Retrieved from Sentinel-1 Imagery." Remote Sensing 10, no. 12 (December 7, 2018): 1979. http://dx.doi.org/10.3390/rs10121979.
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The objective of the study was to estimate soil moisture (SM) from Sentinel-1 (S-1) satellite images acquired over wetlands. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in north-eastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to SM retrieval for a broad range of vegetation and soil moisture conditions. The methodology is based on research into the effect of vegetation on backscatter (σ°) changes under different soil moisture and Normalized Difference Vegetation Index (NDVI) values. The NDVI was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. It was found that the state of the vegetation expressed by NDVI can be described by the indices such as the difference between σ° VH and VV, or the ratio of σ° VV/VH, as calculated from the Sentinel-1 images in the logarithmic domain. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the newly developed models using Water Cloud Model (WCM) that includes the derived indices based on S-1, allowed the estimation of SM for wetlands with reasonable accuracy (10 vol. %). The developed soil moisture retrieval algorithms based on S-1 data are suited for wetland ecosystems, where soil moisture values are several times higher than in agricultural areas.
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Gauci, Adam, Aldo Drago, and John Abela. "Gap Filling of the CALYPSO HF Radar Sea Surface Current Data through Past Measurements and Satellite Wind Observations." International Journal of Navigation and Observation 2016 (November 9, 2016): 1–9. http://dx.doi.org/10.1155/2016/2605198.
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High frequency (HF) radar installations are becoming essential components of operational real-time marine monitoring systems. The underlying technology is being further enhanced to fully exploit the potential of mapping sea surface currents and wave fields over wide areas with high spatial and temporal resolution, even in adverse meteo-marine conditions. Data applications are opening to many different sectors, reaching out beyond research and monitoring, targeting downstream services in support to key national and regional stakeholders. In the CALYPSO project, the HF radar system composed of CODAR SeaSonde stations installed in the Malta Channel is specifically serving to assist in the response against marine oil spills and to support search and rescue at sea. One key drawback concerns the sporadic inconsistency in the spatial coverage of radar data which is dictated by the sea state as well as by interference from unknown sources that may be competing with transmissions in the same frequency band. This work investigates the use of Machine Learning techniques to fill in missing data in a high resolution grid. Past radar data and wind vectors obtained from satellites are used to predict missing information and provide a more consistent dataset.
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Natsagdorj, Enkhjargal, Tsolmon Renchin, Philippe De Maeyer, and Bayanjargal Darkhijav. "Spatial Distribution of Soil Moisture in Mongolia Using SMAP and MODIS Satellite Data: A Time Series Model (2010–2025)." Remote Sensing 13, no. 3 (January 20, 2021): 347. http://dx.doi.org/10.3390/rs13030347.
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Soil moisture is one of the essential variables of the water cycle, and plays a vital role in agriculture, water management, and land (drought) and vegetation cover change as well as climate change studies. The spatial distribution of soil moisture with high-resolution images in Mongolia has long been one of the essential issues in the remote sensing and agricultural community. In this research, we focused on the distribution of soil moisture and compared the monthly precipitation/temperature and crop yield from 2010 to 2020. In the present study, Soil Moisture Active Passive (SMAP) and Moderate Resolution Imaging Spectroradiometer (MODIS) data were used, including the MOD13A2 Normalized Difference Vegetation Index (NDVI), MOD11A2 Land Surface Temperature (LST), and precipitation/temperature monthly data from the Climate Research Unit (CRU) from 2010 to 2020 over Mongolia. Multiple linear regression methods have previously been used for soil moisture estimation, and in this study, the Autoregressive Integrated Moving Arima (ARIMA) model was used for soil moisture forecasting. The results show that the correlation was statistically significant between SM-MOD and soil moisture content (SMC) from the meteorological stations at different depths (p < 0.0001 at 0–20 cm and p < 0.005 at 0–50 cm). The correlation between SM-MOD and temperature, as represented by the correlation coefficient (r), was 0.80 and considered statistically significant (p < 0.0001). However, when SM-MOD was compared with the crop yield for each year (2010–2019), the correlation coefficient (r) was 0.84. The ARIMA (12, 1, 12) model was selected for the soil moisture time series analysis when predicting soil moisture from 2020 to 2025. The forecasting results are shown for the 95 percent confidence interval. The soil moisture estimation approach and model in our study can serve as a valuable tool for confident and convenient observations of agricultural drought for decision-makers and farmers in Mongolia.
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Cigna, Francesca, Deodato Tapete, and Zhong Lu. "Remote Sensing of Volcanic Processes and Risk." Remote Sensing 12, no. 16 (August 10, 2020): 2567. http://dx.doi.org/10.3390/rs12162567.
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Remote sensing data and methods are increasingly being embedded into assessments of volcanic processes and risk. This happens thanks to their capability to provide a spectrum of observation and measurement opportunities to accurately sense the dynamics, magnitude, frequency, and impacts of volcanic activity in the ultraviolet (UV), visible (VIS), infrared (IR), and microwave domains. Launched in mid-2018, the Special Issue “Remote Sensing of Volcanic Processes and Risk” of Remote Sensing gathers 19 research papers on the use of satellite, aerial, and ground-based remote sensing to detect thermal features and anomalies, investigate lava and pyroclastic flows, predict the flow path of lahars, measure gas emissions and plumes, and estimate ground deformation. The strong multi-disciplinary character of the approaches employed for volcano monitoring and the combination of a variety of sensor types, platforms, and methods that come out from the papers testify the current scientific and technology trends toward multi-data and multi-sensor monitoring solutions. The research advances presented in the published papers are achieved thanks to a wealth of data including but not limited to the following: thermal IR from satellite missions (e.g., MODIS, VIIRS, AVHRR, Landsat-8, Sentinel-2, ASTER, TET-1) and ground-based stations (e.g., FLIR cameras); digital elevation/surface models from airborne sensors (e.g., Light Detection And Ranging (LiDAR), or 3D laser scans) and satellite imagery (e.g., tri-stereo Pléiades, SPOT-6/7, PlanetScope); airborne hyperspectral surveys; geophysics (e.g., ground-penetrating radar, electromagnetic induction, magnetic survey); ground-based acoustic infrasound; ground-based scanning UV spectrometers; and ground-based and satellite Synthetic Aperture Radar (SAR) imaging (e.g., TerraSAR-X, Sentinel-1, Radarsat-2). Data processing approaches and methods include change detection, offset tracking, Interferometric SAR (InSAR), photogrammetry, hotspots and anomalies detection, neural networks, numerical modeling, inversion modeling, wavelet transforms, and image segmentation. Some authors also share codes for automated data analysis and demonstrate methods for post-processing standard products that are made available for end users, and which are expected to stimulate the research community to exploit them in other volcanological application contexts. The geographic breath is global, with case studies in Chile, Peru, Ecuador, Guatemala, Mexico, Hawai’i, Alaska, Kamchatka, Japan, Indonesia, Vanuatu, Réunion Island, Ethiopia, Canary Islands, Greece, Italy, and Iceland. The added value of the published research lies on the demonstration of the benefits that these remote sensing technologies have brought to knowledge of volcanoes that pose risk to local communities; back-analysis and critical revision of recent volcanic eruptions and unrest periods; and improvement of modeling and prediction methods. Therefore, this Special Issue provides not only a collection of forefront research in remote sensing applied to volcanology, but also a selection of case studies proving the societal impact that this scientific discipline can potentially generate on volcanic hazard and risk management.
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Kim, Chang Ki, Hyun-Goo Kim, Yong-Heack Kang, Chang-Yeol Yun, Boyoung Kim, and Jin Young Kim. "Solar Resource Potentials and Annual Capacity Factor Based on the Korean Solar Irradiance Datasets Derived by the Satellite Imagery from 1996 to 2019." Remote Sensing 13, no. 17 (August 28, 2021): 3422. http://dx.doi.org/10.3390/rs13173422.
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The Korea Institute of Energy Research builds Korean solar irradiance datasets, using gridded solar insolation estimates derived using the University of Arizona solar irradiance based on Satellite–Korea Institute of Energy Research (UASIBS–KIER) model, with the incorporation of geostationary satellites over the Korean Peninsula, from 1996 to 2019. During the investigation period, the monthly mean of daily total irradiance was in a good agreement with the in situ measurements at 18 ground stations; the mean absolute error is also normalized to 9.4%. It is observed that the irradiance estimates in the datasets have been gradually increasing at a rate of 0.019 kWh m−2 d−1 per year. The monthly variation in solar irradiance indicates that the meteorological conditions in the spring season dominate the annual solar insolation. In addition, the local distribution of solar irradiance is primarily affected by the geographical environment; higher solar insolation is observed in the southern part of Korea, but lower solar insolation is observed in the mountainous range in Korea. The annual capacity factor is the secondary output from the Korean solar irradiance datasets. The reliability of the estimate of this factor is proven by the high correlation coefficient of 0.912. Thus, in accordance with the results from the spatial distribution of solar irradiance, the southern part of Korea is an appropriate region for establishing solar power plants exhibiting a higher annual capacity factor than the other regions.