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Journal articles on the topic 'Imagery sensors'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Dabrowski, R., A. Orych, A. Jenerowicz, and P. Walczykowski. "PRELIMINARY RESULTS FROM THE PORTABLE IMAGERY QUALITY ASSESSMENT TEST FIELD (PIQuAT) OF UAV IMAGERY FOR IMAGERY RECONNAISSANCE PURPOSES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W4 (August 26, 2015): 111–15. http://dx.doi.org/10.5194/isprsarchives-xl-1-w4-111-2015.

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The article presents a set of initial results of a quality assessment study of 2 different types of sensors mounted on an unmanned aerial vehicle, carried out over an especially designed and constructed test field. The PIQuAT (Portable Imagery Quality Assessment Test Field) field had been designed especially for the purposes of determining the quality parameters of UAV sensors, especially in terms of the spatial, spectral and radiometric resolutions and chosen geometric aspects. The sensor used include a multispectral framing camera and a high-resolution RGB sensor. The flights were conducted

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Brown, Alison, and Paul Olson. "Navigation and Electro-Optic Sensor Integration Technology for Fusion of Imagery and Digital Mapping Products." Journal of Navigation 53, no. 1 (2000): 132–45. http://dx.doi.org/10.1017/s0373463399008735.

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Several military and commercial platforms are currently installing GPS and inertial navigation sensors concurrently with the introduction of high-quality visual capabilities and digital mapping/imagery databases. This enables autonomous geo-registration of sensor imagery using GPS/inertial position and attitude data, and also permits data from digital mapping products to be overlaid automatically on the sensor imagery. This paper describes the system architecture for a Navigation/Electro-Optic Sensor Integration Technology (NEOSIT) software application. The design is highly modular and based o

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Vatitsi, Katerina, Sofia Siachalou, Dionissis Latinopoulos, Ifigenia Kagalou, Christos S. Akratos, and Giorgos Mallinis. "Monitoring Water Quality Parameters in Small Rivers Using SuperDove Imagery." Water 16, no. 5 (2024): 758. http://dx.doi.org/10.3390/w16050758.

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Freshwater ecosystems provide an array of provisioning, regulating/maintenance, and cultural ecosystem services. Despite their crucial role, freshwater ecosystems are exceptionally vulnerable due to changes driven by both natural and human factors. Water quality is essential for assessing the condition and ecological health of freshwater ecosystems, and its evaluation involves various water quality parameters. Remote sensing has become an efficient approach for retrieving and mapping these parameters, even in optically complex waters such as small rivers. This study specifically focuses on mod

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Nuris, Rayhan, Jonson Lumban Gaol, and Teguh Prayogo. "CHLOROPHYLL-A CONCENTRATIONS ESTIMATION FROM AQUA-MODIS AND VIIRS-NPP SATELLITE SENSORS IN SOUTH JAVA SEA WATERS." International Journal of Remote Sensing and Earth Sciences (IJReSES) 12, no. 1 (2017): 63. http://dx.doi.org/10.30536/j.ijreses.2015.v12.a2673.

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This study aimed to estimate the concentration of chlorophyll-a from satellite imagery of National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in the south Java Sea waters and compare it to the concentrations of chlorophyll-a estimation result from the MODIS-Aqua satellite. NPP satellite had Visible/Infrared Imager Radiometer Suite (VIIRS) sensors which performance was same as Moderate Resolution Imaging Spectroradiometer (MODIS) sensor with a better spatial resolution. This study used daily satellite imagery of VIIRS-NPP for the period of Septe

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Molijn, Ramses, Lorenzo Iannini, Jansle Vieira Rocha, and Ramon Hanssen. "Sugarcane Productivity Mapping through C-Band and L-Band SAR and Optical Satellite Imagery." Remote Sensing 11, no. 9 (2019): 1109. http://dx.doi.org/10.3390/rs11091109.

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Space-based remote sensing imagery can provide a valuable and cost-effective set of observations for mapping crop-productivity differences. The effectiveness of such signals is dependent on several conditions that are related to crop and sensor characteristics. In this paper, we present the dynamic behavior of signals from five Synthetic Aperture Radar (SAR) sensors and optical sensors with growing sugarcane, focusing on saturation effects and the influence of precipitation events. In addition, we analyzed the level of agreement within and between these spaceborne datasets over space and time.

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White, Laura A., and Rebecca K. Gibson. "Comparing Fire Extent and Severity Mapping between Sentinel 2 and Landsat 8 Satellite Sensors." Remote Sensing 14, no. 7 (2022): 1661. http://dx.doi.org/10.3390/rs14071661.

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Mapping of fire extent and severity across broad landscapes and timeframes using remote sensing approaches is valuable to inform ecological research, biodiversity conservation and fire management. Compiling imagery from various satellite sensors can assist in long-term fire history mapping; however, inherent sensor differences need to be considered. The New South Wales Fire Extent and Severity Mapping (FESM) program uses imagery from Sentinel and Landsat satellites, along with supervised classification algorithms, to produce state-wide fire maps over recent decades. In this study, we compared

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Brotoisworo, P., RK Aranas, and MJ Felix. "Automated georeferencing of Diwata-2 multispectral imagery using feature matching." Journal of Physics: Conference Series 2214, no. 1 (2022): 012027. http://dx.doi.org/10.1088/1742-6596/2214/1/012027.

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Abstract The Diwata-2 microsatellite is a 56 kg optical microsatellite that features different optical sensors such as the medium resolution Spaceborne Multispectral Sensor (SMI) and a high-resolution sensor called High Precision Telescope (HPT). This research aims to develop an automated georeferencing workflow for coregistered multiband HPT and SMI imagery with a GSD of 5 meters and 127 meters respectively. Georeferencing is done using a mixture of FAST and SIFT feature matching algorithms where HPT imagery used SIFT descriptors and detectors and SMI used FAST detectors and SIFT descriptors.

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Philippe, Julien, Maria De Paolis, Dominique Henry, et al. "In-Situ Wireless Pressure Measurement Using Zero-Power Packaged Microwave Sensors." Sensors 19, no. 6 (2019): 1263. http://dx.doi.org/10.3390/s19061263.

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This paper reports the indoor wireless measurement of pressure from zero-power (or passive) microwave (24 GHz) sensors. The sensors are packaged and allow the remote measurement of overpressure up to 2.1 bars. Their design, fabrication process and packaging are detailed. From the measurement of sensor scattering parameters, the outstanding sensitivity of 995 MHz/bar between 0.8 and 2.1 bars was achieved with the full-scale measurement range of 1.33 GHz. Moreover, the 3D radar imagery technique was applied for the remote interrogation of these sensors in electromagnetic reverberant environments

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Dillen, Arnau, Fakhreddine Ghaffari, Olivier Romain, et al. "Optimal Sensor Set for Decoding Motor Imagery from EEG." Applied Sciences 13, no. 7 (2023): 4438. http://dx.doi.org/10.3390/app13074438.

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Brain–computer interfaces (BCIs) have the potential to enable individuals to interact with devices by detecting their intention from brain activity. A common approach to BCI is to decode movement intention from motor imagery (MI), the mental representation of an overt action. However, research-grade electroencephalogram (EEG) acquisition devices with a high number of sensors are typically necessary to achieve the spatial resolution required for reliable analysis. This entails high monetary and computational costs that make these approaches impractical for everyday use. This study investigates

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Fischer, Peter, Philipp Schuegraf, Nina Merkle, and Tobias Storch. "AN EVOLUTIONARY ALGORITHM FOR FAST INTENSITY BASED IMAGE MATCHING BETWEEN OPTICAL AND SAR SATELLITE IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-3 (April 23, 2018): 83–90. http://dx.doi.org/10.5194/isprs-annals-iv-3-83-2018.

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This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite

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Jóźków, G., and C. Toth. "Georeferencing experiments with UAS imagery." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-1 (November 7, 2014): 25–29. http://dx.doi.org/10.5194/isprsannals-ii-1-25-2014.

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Comparing typical airborne mapping systems with Unmanned Airborne Systems (UAS) developed for mapping purposes, there are several advantages and disadvantages of both systems. The unquestionable benefits of UAS are the much lower costs of equipment and the simple operation; though, the regulations to fly UAS greatly vary by country. Low cost, however, means small sensor size and low weight, thus, sensors usually lack the quality, negatively impacting the accuracy of UAS data and, consequently, any derived mapping products. This work compares the performance of three different positioning appro

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Thieme, Alison, Kusuma Prabhakara, Jyoti Jennewein, Brian T. Lamb, Greg W. McCarty, and Wells Dean Hively. "Intercomparison of Same-Day Remote Sensing Data for Measuring Winter Cover Crop Biophysical Traits." Sensors 24, no. 7 (2024): 2339. http://dx.doi.org/10.3390/s24072339.

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Winter cover crops are planted during the fall to reduce nitrogen losses and soil erosion and improve soil health. Accurate estimations of winter cover crop performance and biophysical traits including biomass and fractional vegetative groundcover support accurate assessment of environmental benefits. We examined the comparability of measurements between ground-based and spaceborne sensors as well as between processing levels (e.g., surface vs. top-of-atmosphere reflectance) in estimating cover crop biophysical traits. This research examined the relationships between SPOT 5, Landsat 7, and Wor

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Lynch, Heather J. "Satellite Remote Sensing for Wildlife Research in the Polar Regions." Marine Technology Society Journal 57, no. 3 (2023): 43–50. http://dx.doi.org/10.4031/mtsj.57.3.1.

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Abstract Wildlife research in the polar regions has historically been limited by the logistical constraints of site access, but recent developments in the use of satellite imagery for animal detection has unlocked new possibilities for pan-Arctic and pan-Antarctic monitoring of animal populations. A range of different sensor systems have been used for wildlife research, but most have focused on optical sensors that collect data in the visible spectrum and can be directly interpreted similar to a photograph. These include medium-resolution sensors like Landsat (30 m) and Sentinel-2 (10 m) and v

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Atkins, Jeff W., Atticus E. L. Stovall, and Xi Yang. "Mapping Temperate Forest Phenology Using Tower, UAV, and Ground-Based Sensors." Drones 4, no. 3 (2020): 56. http://dx.doi.org/10.3390/drones4030056.

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Phenology is a distinct marker of the impacts of climate change on ecosystems. Accordingly, monitoring the spatiotemporal patterns of vegetation phenology is important to understand the changing Earth system. A wide range of sensors have been used to monitor vegetation phenology, including digital cameras with different viewing geometries mounted on various types of platforms. Sensor perspective, view-angle, and resolution can potentially impact estimates of phenology. We compared three different methods of remotely sensing vegetation phenology—an unoccupied aerial vehicle (UAV)-based, downwar

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Dąbrowski, R., and A. Jenerowicz. "PORTABLE IMAGERY QUALITY ASSESSMENT TEST FIELD FOR UAV SENSORS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W4 (August 26, 2015): 117–22. http://dx.doi.org/10.5194/isprsarchives-xl-1-w4-117-2015.

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Nowadays the imagery data acquired from UAV sensors are the main source of all data used in various remote sensing applications, photogrammetry projects and in imagery intelligence (IMINT) as well as in other tasks as decision support. Therefore quality assessment of such imagery is an important task. The research team from Military University of Technology, Faculty of Civil Engineering and Geodesy, Geodesy Institute, Department of Remote Sensing and Photogrammetry has designed and prepared special test field- The Portable Imagery Quality Assessment Test Field (PIQuAT) that provides quality as

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Ladai, A. D., and J. Miller. "Point Cloud Generation from sUAS-Mounted iPhone Imagery: Performance Analysis." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (November 7, 2014): 201–5. http://dx.doi.org/10.5194/isprsarchives-xl-1-201-2014.

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The rapidly growing use of sUAS technology and fast sensor developments continuously inspire mapping professionals to experiment with low-cost airborne systems. Smartphones has all the sensors used in modern airborne surveying systems, including GPS, IMU, camera, etc. Of course, the performance level of the sensors differs by orders, yet it is intriguing to assess the potential of using inexpensive sensors installed on sUAS systems for topographic applications. This paper focuses on the quality analysis of point clouds generated based on overlapping images acquired by an iPhone 5s mounted on a

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Gillespie, Thomas W., Jasmine Chu, Elizabeth Frankenberg, and Duncan Thomas. "Assessment and prediction of natural hazards from satellite imagery." Progress in Physical Geography: Earth and Environment 31, no. 5 (2007): 459–70. http://dx.doi.org/10.1177/0309133307083296.

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Since 2000, there have been a number of spaceborne satellites that have changed the way we assess and predict natural hazards. These satellites are able to quantify physical geographic phenomena associated with the movements of the earth's surface (earthquakes, mass movements), water (floods, tsunamis, storms), and fire (wildfires). Most of these satellites contain active or passive sensors that can be utilized by the scientific community for the remote sensing of natural hazards over a number of spatial and temporal scales. The most useful satellite imagery for the assessment of earthquake da

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Yue, C. Y., T. Sun, and J. F. Xie. "THE REMOTE SENSING IMAGE GEOMETRICAL MODEL OF BP NEURAL NETWORK." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 7, 2020): 381–86. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-381-2020.

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Abstract. Imagery geometry models (IGMs) of the high-resolution satellite images (HRSIs) are always of great interest in the photogrammetry and remote sensing community for the raising new kinds of sensors and imaging systems. Especially the generalized sensor models (GSMs) have been widely used for positioning of satellite images, and the accuracy are already validated. Since Back propagation (BP) neural network is a better choice for the two key reasons of the replacement of physical sensor models by generalized sensor models, numerous mathematical estimations for every specialized sensor, a

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Khare, Smriti. "Remote Sensing Imagery Sensors and Image Interpretation." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (2021): 606–7. http://dx.doi.org/10.22214/ijraset.2021.38019.

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Abstract: Remote sensing a universal term that represents the activity of gaining data of an object with a sensor that is genuinely away from the item from an aircraft or satellite. Special cameras are used to gather remotely sensed picture which help the analyst to sense the things about the earth. Remote sensing makes it probable to assemble data of risky or unapproachable zones. Remote sensing data allows researchers to examine the biosphere's biotic and abiotic segments. Remote sensing is used in various fields to acquire the data which is widely used in Geographical Information System. Im

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Tang, Tim Y., Daniele De Martini, Shangzhe Wu, and Paul Newman. "Self-supervised learning for using overhead imagery as maps in outdoor range sensor localization." International Journal of Robotics Research 40, no. 12-14 (2021): 1488–509. http://dx.doi.org/10.1177/02783649211045736.

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Traditional approaches to outdoor vehicle localization assume a reliable, prior map is available, typically built using the same sensor suite as the on-board sensors used during localization. This work makes a different assumption. It assumes that an overhead image of the workspace is available and utilizes that as a map for use for range-based sensor localization by a vehicle. Here, range-based sensors are radars and lidars. Our motivation is simple, off-the-shelf, publicly available overhead imagery such as Google satellite images can be a ubiquitous, cheap, and powerful tool for vehicle loc

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Doubrawa, Betina, Ana Paula Dalla Corte, and Carlos Roberto Sanquetta. "Using different satellite imagery and classification techniques to assess the contribution of trees outside forests in the municipality of Maringá, Brazil." Revista Ceres 60, no. 4 (2013): 480–88. http://dx.doi.org/10.1590/s0034-737x2013000400006.

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Forest cover of the Maringá municipality, located in northern Parana State, was mapped in this study. Mapping was carried out by using high-resolution HRC sensor imagery and medium resolution CCD sensor imagery from the CBERS satellite. Images were georeferenced and forest vegetation patches (TOFs - trees outside forests) were classified using two methods of digital classification: reflectance-based or the digital number of each pixel, and object-oriented. The areas of each polygon were calculated, which allowed each polygon to be segregated into size classes. Thematic maps were built from the

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Dash, Jonathan, Grant Pearse, and Michael Watt. "UAV Multispectral Imagery Can Complement Satellite Data for Monitoring Forest Health." Remote Sensing 10, no. 8 (2018): 1216. http://dx.doi.org/10.3390/rs10081216.

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The development of methods that can accurately detect physiological stress in forest trees caused by biotic or abiotic factors is vital for ensuring productive forest systems that can meet the demands of the Earth’s population. The emergence of new sensors and platforms presents opportunities to augment traditional practices by combining remotely-sensed data products to provide enhanced information on forest condition. We tested the sensitivity of multispectral imagery collected from time-series unmanned aerial vehicle (UAV) and satellite imagery to detect herbicide-induced stress in a careful

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Kabiri, K., and M. Moradi. "A CROSS-SENSOR-BASED APPROACH TO ESTIMATE DEPTH VALUES IN NEARSHORE COASTAL WATERS, CASE STUDY: NAYBAND BAY, PERSIAN GULF." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences X-4/W1-2022 (January 13, 2023): 343–48. http://dx.doi.org/10.5194/isprs-annals-x-4-w1-2022-343-2023.

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Abstract. A cross-sensor-based approach using Landsat-8 OLI (L8/OLI) and Sentinel-2A MSI (S2A/MSI) imagers was examined to estimate bathymetric data in nearshore coastal waters. An L8/OLI image and an S2A/MSI image (Acquisition date: November 16, 2017) were selected from Nayband Bay, the southern region of Iran. In addition, precise bathymetric data for the studied area were used to calibrate the models and validate the results. Ratio together with traditional linear transform methods and a novel cross-sensor-based method were conducted to determine the depth values from both satellite images.

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Elmer, Nicholas J., Emily Berndt, Gary Jedlovec, and Kevin Fuell. "Limb Correction of Geostationary Infrared Imagery in Clear and Cloudy Regions to Improve Interpretation of RGB Composites for Real-Time Applications." Journal of Atmospheric and Oceanic Technology 36, no. 8 (2019): 1675–90. http://dx.doi.org/10.1175/jtech-d-18-0206.1.

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AbstractRed–green–blue (RGB) composites are increasingly used by operational forecasters to interpret vast amounts of satellite imagery by reducing several bands into a single, easily understood product which identifies important atmospheric features with unique colors. Limb effects, a result of an increase in optical pathlength of the absorbing atmosphere between the satellite and Earth as viewing zenith angle increases, adversely affects RGB composite interpretation by causing anomalous reductions in brightness temperature, thus changing the color interpretation of the RGB composites. In a p

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Akca, Devrim, Efstratios Stylianidis, Konstantinos Smagas, et al. "VOLUMETRIC FOREST CHANGE DETECTION THROUGH VHR SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1213–20. http://dx.doi.org/10.5194/isprs-archives-xli-b8-1213-2016.

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Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2

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Akca, Devrim, Efstratios Stylianidis, Konstantinos Smagas, et al. "VOLUMETRIC FOREST CHANGE DETECTION THROUGH VHR SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 1213–20. http://dx.doi.org/10.5194/isprsarchives-xli-b8-1213-2016.

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Quick and economical ways of detecting of planimetric and volumetric changes of forest areas are in high demand. A research platform, called FORSAT (A satellite processing platform for high resolution forest assessment), was developed for the extraction of 3D geometric information from VHR (very-high resolution) imagery from satellite optical sensors and automatic change detection. This 3D forest information solution was developed during a Eurostars project. FORSAT includes two main units. The first one is dedicated to the geometric and radiometric processing of satellite optical imagery and 2

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Caseiro, Alexandre, and Agnieszka Soszyńska. "Quantification of Gas Flaring from Satellite Imagery: A Comparison of Two Methods for SLSTR and BIROS Imagery." Journal of Imaging 9, no. 8 (2023): 152. http://dx.doi.org/10.3390/jimaging9080152.

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Gas flaring is an environmental problem of local, regional and global concerns. Gas flares emit pollutants and greenhouse gases, yet knowledge about the source strength is limited due to disparate reporting approaches in different geographies, whenever and wherever those are considered. Remote sensing has bridged the gap but uncertainties remain. There are numerous sensors which provide measurements over flaring-active regions in wavelengths that are suitable for the observation of gas flares and the retrieval of flaring activity. However, their use for operational monitoring has been limited.

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Cheshkova, A. F., and V. S. Riksen. "Strawberry Disease Detection Using Multispectral UAV Imagery." Agricultural Machinery and Technologies 19, no. 2 (2025): 45–52. https://doi.org/10.22314/2073-7599-2025-19-2-45-52.

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Accurate, timely, and non-invasive diagnosis of plant diseases is essential in the industrial cultivation of strawberries, as it helps minimize yield losses and reduce treatment costs. With the advancement of unmanned aerial vehicles and sensor technologies, remote sensing has emerged as a promising tool for monitoring crop health and detecting diseases. Early detection is especially important for sensitive crops such as garden strawberries. (Research purpose) The research aims to evaluate the potential of using multispectral sensors and unmanned aerial vehicles for detecting fungal diseases i

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Basnayake, Ranil, Erik Bollt, Nicholas Tufillaro, Jie Sun, and Michelle Gierach. "Regularization destriping of remote sensing imagery." Nonlinear Processes in Geophysics 24, no. 3 (2017): 367–78. http://dx.doi.org/10.5194/npg-24-367-2017.

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Abstract. We illustrate the utility of variational destriping for ocean color images from both multispectral and hyperspectral sensors. In particular, we examine data from a filter spectrometer, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (NPP) orbiter, and an airborne grating spectrometer, the Jet Population Laboratory's (JPL) hyperspectral Portable Remote Imaging Spectrometer (PRISM) sensor. We solve the destriping problem using a variational regularization method by giving weights spatially to preserve the other features of the image during

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Walczykowski, P., A. Orych, A. Jenerowicz, and P. Karcz. "Evaluating sensor linearity of chosen infrared sensors." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1 (November 7, 2014): 421–24. http://dx.doi.org/10.5194/isprsarchives-xl-1-421-2014.

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The paper describes a series of experiments conducted as part of the IRAMSWater Project, the aim of which is to establish methodologies for detecting and identifying pollutants in water bodies using aerial imagery data. The main idea is based on the hypothesis, that it is possible to identify certain types of physical, biological and chemical pollutants based on their spectral reflectance characteristics. The knowledge of these spectral curves is then used to determine very narrow spectral bands in which greatest reflectance variations occur between these pollutants. A frame camera is then equ

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Rafert, J. Bruce, Jaime Zabalza, Stephen Marshall, and Jinchang Ren. "Singular Spectrum Analysis: A Note on Data Processing for Fourier Transform Hyperspectral Imagers." Applied Spectroscopy 70, no. 9 (2016): 1582–88. http://dx.doi.org/10.1177/0003702816641420.

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Hyperspectral remote sensing is experiencing a dazzling proliferation of new sensors, platforms, systems, and applications with the introduction of novel, low-cost, low-weight sensors. Curiously, relatively little development is now occurring in the use of Fourier transform (FT) systems, which have the potential to operate at extremely high throughput without use of a slit or reductions in both spatial and spectral resolution that thin film based mosaic sensors introduce. This study introduces a new physics-based analytical framework called singular spectrum analysis (SSA) to process raw hyper

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Meier, Walter N., and Mingrui Dai. "High-resolution Sea-ICE motions from AMSR-E imagery." Annals of Glaciology 44 (2006): 352–56. http://dx.doi.org/10.3189/172756406781811286.

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AbstractPassive microwave remote-sensing imagery has proven to be a useful Source for Sea-ICE motions because of its all-sky capabilities. However, the low Spatial resolution of the passive microwave Sensors has not allowed the retrieval of Small-scale motion details Such as lead and ridge formation. The NAsA Earth Observing System Advanced Microwave Scanning Radiometer (AMSR-E) has more than double the Spatial resolution of previous passive microwave Sensors, allowing it to track the formation of moderate-sized leads and yield much more detailed and more accurate ICE-motion estimates. Compari

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Seidlova, Anna, Maria Kudelcikova, Jan Mihalik, and Donatas Rekus. "Interpretation of Remote Sensing Imagery." IOP Conference Series: Earth and Environmental Science 906, no. 1 (2021): 012070. http://dx.doi.org/10.1088/1755-1315/906/1/012070.

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Abstract The process of interpretation and analysis of remote sensing data is based on extracting meaningful information from satellite imagery. The quality of visual interpretation depends on the resolvability and recognisability of the main visual characteristics of each photo or images. The current process of image analysis is based on digital processing limited by used satellite or airborne sensors.

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Baiocchi, Valerio, and Francesca Giannone. "New Trends in High-Resolution Imagery Processing." Remote Sensing 15, no. 8 (2023): 2164. http://dx.doi.org/10.3390/rs15082164.

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Mills, J. P., and A. P. Cracknell. "ISPRS Commission I Symposium: From Sensors to Imagery." Photogrammetric Record 21, no. 116 (2006): 398–401. http://dx.doi.org/10.1111/j.1477-9730.2006.00401.x.

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Alevizos, Evangelos, Dimitrios Oikonomou, Athanasios V. Argyriou, and Dimitrios D. Alexakis. "Fusion of Drone-Based RGB and Multi-Spectral Imagery for Shallow Water Bathymetry Inversion." Remote Sensing 14, no. 5 (2022): 1127. http://dx.doi.org/10.3390/rs14051127.

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Shallow bathymetry inversion algorithms have long been applied in various types of remote sensing imagery with relative success. However, this approach requires that imagery with increased radiometric resolution in the visible spectrum be available. The recent developments in drones and camera sensors allow for testing current inversion techniques on new types of datasets with centimeter resolution. This study explores the bathymetric mapping capabilities of fused RGB and multispectral imagery as an alternative to costly hyperspectral sensors for drones. Combining drone-based RGB and multispec

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Jang, Fong Lin, and Chyun Chau Lin. "Relationships and Comparisons of Finger Surface Temperature Measurements from Three Different Kinds of Temperature Sensors." Applied Mechanics and Materials 284-287 (January 2013): 1559–63. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.1559.

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Temperature biofeedback has been used in behavioral medicine for more than three decades. Traditional temperature biofeedback uses the contact sensor of a thermistor to measure one’s finger surface temperature. The goal of this study is to discover new valid sensors for temperature biofeedback. Sixteen healthy young adult volunteers (23.1±2.0 years old) practiced cognitive imagery muscle relaxation with three kinds of temperature sensors (thermography imaging, thermistor, and infrared thermopile) to measure their finger surfaces simultaneously. The temperature readings from different sensors w

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Abi Kaberou, Alain. "Comparative use of UAV and Satellite Images in discrimination and estimation of cashew plantation areas." Journal of Geomatics 18, no. 2 (2024): 71–81. http://dx.doi.org/10.58825/jog.2024.18.2.147.

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Cashew plantations generate significant interest in Benin due to their high socioeconomic value for the population. A thorough understanding of the spatial distribution of these plantations is crucial for comprehending their environmental and socioeconomic impacts. In this study, various types of multi-sensor imagery were compared to assess each sensor's capabilities in mapping plantation areas. The study was conducted in the Savè commune, a major industrial cashew-producing region. Multispectral sensors from Landsat-8 Operational Land Imager (OLI), Sentinel-2A, and UAV multispectral platforms

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Mc’Okeyo, P. O., F. Nex, C. Persello, and A. Vrieling. "AUTOMATED CO-REGISTRATION OF INTRA-EPOCH AND INTER-EPOCH SERIES OF MULTISPECTRAL UAV IMAGES FOR CROP MONITORING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (August 3, 2020): 309–16. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-309-2020.

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Abstract. The application of UAV-based aerial imagery has advanced exponentially in the past two decades. This can be attributed to UAV operational flexibility, ultra-high spatial resolution, inexpensiveness, and UAV-based sensors enhancement. Nonetheless, the application of multitemporal series of multispectral UAV imagery still suffers significant misregistration errors, and therefore becoming a concern for applications such as precision agriculture. Direct image georeferencing and co-registration is commonly done using ground control points; this is usually costly and time consuming. This r

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Schläpfer, D., C. Popp, and R. Richter. "DRONE DATA ATMOSPHERIC CORRECTION CONCEPT FOR MULTI- AND HYPERSPECTRAL IMAGERY – THE DROACOR MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 473–78. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-473-2020.

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Abstract. Remote sensing with unmanned aerial vehicles (UAVs) is a fast and cost-efficient tool for mapping and environmental monitoring. The sensors are operated at low flight altitudes, usually below 500 m above ground, leading to spatial resolutions up to the centimeter range. This type of data causes new challenges in atmospheric compensation and surface reflectance retrieval. Based on these specific boundary conditions, a new drone based atmospheric correction concept (DROACOR) is proposed, which is designed for currently available UAV based sensors. It is suited for multispectral visible

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Campbell, Mel, Donna Delparte, Matthew Belt, Zhongqi Chen, Christopher C. Caudill, and Trevor Caughlin. "Diel Variation in Summer Stream Temperature in an Idaho Desert Stream and Implications for Identifying Thermal Refuges." Climate 13, no. 3 (2025): 44. https://doi.org/10.3390/cli13030044.

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Thermal refuges in streams are essential for the survival of coldwater fish species such as Redband trout (Oncorhynchus mykiss) in landscapes with stressful or lethal stream temperatures. We utilized an uncrewed aerial system (UAS) mounted with thermal and natural color sensors to conduct hourly flights over a 24 h period in the desert stream Little Jacks Creek during late summer when temperatures were near seasonal maximums and streamflow was near seasonal minimums. We used fine-resolution imagery to map stream temperatures and characterize how our thermal sensor exhibits variability across a

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Lewis, M. "Discrimination of arid vegetation composition with high resolution CASI imagery." Rangeland Journal 22, no. 1 (2000): 141. http://dx.doi.org/10.1071/rj0000141.

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CASI (Compact Airborne Spectrographic Imager) airborne imagery, with high spectral and spatial resolution, was evaluated for the discrimination of composition and variation in arid vegetation at Fowlers Gap Arid Zone Research Station in western New South Wales. The imagery was calibrated to surface reflectance using field reference spectra collected near the time of the overflight, and analysed in relation to reflectance spectra of plants at Fowlers Gap. Maps showing abundance of total perennial vegetation, chenopod shrubs and trees, were produced using methods that separated the vegetation co

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Gektin, U. M., N. A. Egoshkin, V. V. Eremeev, A. E. Kuznetcov, and A. M. Kochergin. "PRELAUNCH PHOTOGRAMMETRIC CALIBRATION OF RUSSIAN SATELLITE ELEKTRO-L IMAGERY INSTRUMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 161–63. http://dx.doi.org/10.5194/isprs-archives-xli-b6-161-2016.

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Technology of prelaunch geometric calibration of multispectral imagery instruments of Russian geostationary satellites “Elektro-L” No.1 and No.2 is considered. Circular control points are used as a test field. Its geometrical model is developed to take distortions in the collimator optical system into account. Multiple observations of a test field at different angles is used to cover the full visual field of a geostationary sensor. New algorithm of circular control point detection is developed and adapted to complex geometry of geostationary imagery. It is capable of processing images formed a

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Gektin, U. M., N. A. Egoshkin, V. V. Eremeev, A. E. Kuznetcov, and A. M. Kochergin. "PRELAUNCH PHOTOGRAMMETRIC CALIBRATION OF RUSSIAN SATELLITE ELEKTRO-L IMAGERY INSTRUMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B6 (June 17, 2016): 161–63. http://dx.doi.org/10.5194/isprsarchives-xli-b6-161-2016.

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Technology of prelaunch geometric calibration of multispectral imagery instruments of Russian geostationary satellites “Elektro-L” No.1 and No.2 is considered. Circular control points are used as a test field. Its geometrical model is developed to take distortions in the collimator optical system into account. Multiple observations of a test field at different angles is used to cover the full visual field of a geostationary sensor. New algorithm of circular control point detection is developed and adapted to complex geometry of geostationary imagery. It is capable of processing images formed a

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Li, Wangbin, Kaimin Sun, and Jinjiang Wei. "Adapting Cross-Sensor High-Resolution Remote Sensing Imagery for Land Use Classification." Remote Sensing 17, no. 5 (2025): 927. https://doi.org/10.3390/rs17050927.

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High-resolution visible remote sensing imagery, as a fundamental contributor to Earth observation, has found extensive application in land use classification. However, the heterogeneous array of optical sensors, distinguished by their unique design architectures, exhibit disparate spectral responses and spatial distributions when observing ground objects. These discrepancies between multi-sensor data present a significant obstacle to the widespread application of intelligent methods. In this paper, we propose a method tailored to accommodate these disparities, with the aim of achieving a smoot

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Xing, Fei, Ru An, Xulin Guo, and Xiaoji Shen. "Mapping the Continuous Cover of Invasive Noxious Weed Species Using Sentinel-2 Imagery and a Novel Convolutional Neural Regression Network." Remote Sensing 16, no. 9 (2024): 1648. http://dx.doi.org/10.3390/rs16091648.

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Invasive noxious weed species (INWS) are typical poisonous plants and forbs that are considered an increasing threat to the native alpine grassland ecosystems in the Qinghai–Tibetan Plateau (QTP). Accurate knowledge of the continuous cover of INWS across complex alpine grassland ecosystems over a large scale is required for their control and management. However, the cooccurrence of INWS and native grass species results in highly heterogeneous grass communities and generates mixed pixels detected by remote sensors, which causes uncertainty in classification. The continuous coverage of INWS at t

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Fryskowska, A., M. Wojtkowska, P. Delis, and A. Grochala. "SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 647–52. http://dx.doi.org/10.5194/isprs-archives-xli-b7-647-2016.

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The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5&dash;0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of La

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Fryskowska, A., M. Wojtkowska, P. Delis, and A. Grochala. "SOME ASPECTS OF SATELLITE IMAGERY INTEGRATION FROM EROS B AND LANDSAT 8." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B7 (June 21, 2016): 647–52. http://dx.doi.org/10.5194/isprsarchives-xli-b7-647-2016.

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The Landsat 8 satellite which was launched in 2013 is a next generation of the Landsat remote sensing satellites series. It is equipped with two new sensors: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). What distinguishes this satellite from the previous is four new bands (coastal aerosol, cirrus and two thermal infrared TIRS bands). Similar to its antecedent, Landsat 8 records electromagnetic radiation in a panchromatic band at a range of 0.5&dash;0.9 μm with a spatial resolution equal to 15 m. In the paper, multispectral imagery integration capabilities of La

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Gordon, Howard R. "Evolution of Ocean Color Atmospheric Correction: 1970–2005." Remote Sensing 13, no. 24 (2021): 5051. http://dx.doi.org/10.3390/rs13245051.

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Retrieval of water properties from satellite-borne imagers viewing oceans and coastal areas in the visible region of the spectrum requires removing the effect of the atmosphere, which contributes approximately 80–90% of the measured radiance over the open ocean in the blue spectral region. The Gordon and Wang algorithm originally developed for SeaWiFS (and used with other NASA sensors, e.g., MODIS) forms the basis for many atmospheric removal (correction) procedures. It was developed for application to imagery obtained over the open ocean (Case 1 waters), where the aerosol is usually non-absor

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Saeedi, Sajad, Carl Thibault, Michael Trentini, and Howard Li. "The COBRA fixed-wing georeferenced imagery dataset." International Journal of Intelligent Unmanned Systems 3, no. 2/3 (2015): 62–71. http://dx.doi.org/10.1108/ijius-10-2014-0008.

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Purpose – The purpose of this paper is to present a localization and mapping data set acquired by a fixed-wing unmanned aerial vehicle (UAV). The data set was collected for educational and research purposes: to save time in dealing with hardware and to compare the results with a benchmark data set. The data were collected in standard Robot Operating System (ROS) format. The environment, fixed-wing, and sensor configuration are explained in detail. GPS coordinates of the fixed-wing are also available as ground truth. The data set is available for download (www.ece.unb.ca/COBRA/open_source.htm).

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