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Relevant bibliographies by topics / Microwave remote sensing

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Academic literature on the topic 'Microwave remote sensing'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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Journal articles on the topic "Microwave remote sensing"

1

Parry, J. T. "Satellite microwave remote sensing." Photogrammetria 40, no. 1 (September 1985): 66–67. http://dx.doi.org/10.1016/0031-8663(85)90048-1.

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Gawarecki, S. J. "Satellite microwave remote sensing." Dynamics of Atmospheres and Oceans 9, no. 3 (August 1985): 316–18. http://dx.doi.org/10.1016/0377-0265(85)90027-2.

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Croom, D. L. "Satellite Microwave Remote Sensing." IEE Proceedings F Communications, Radar and Signal Processing 132, no. 2 (1985): 130. http://dx.doi.org/10.1049/ip-f-1.1985.0030.

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Krohn, M. D. "Satellite microwave remote sensing." Earth-Science Reviews 22, no. 3 (November 1985): 249. http://dx.doi.org/10.1016/0012-8252(85)90072-8.

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Carver, K. R., C. Elachi, and F. T. Ulaby. "Microwave remote sensing from space." Proceedings of the IEEE 73, no. 6 (1985): 970–96. http://dx.doi.org/10.1109/proc.1985.13230.

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Graham, Alastair J. "Introduction to Microwave Remote Sensing." Photogrammetric Record 24, no. 126 (June 2009): 199. http://dx.doi.org/10.1111/j.1477-9730.2009.00531_1.x.

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Marghany, Maged. "Oil Spills and Remote Sensing Monitoring Challenges." International Journal of Oceanography & Aquaculture 7, no. 1 (2023): 1–12. http://dx.doi.org/10.23880/ijoac-16000234.

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This article has illustrated a handful of other concepts in addition to oil spills. This study investigated the harm caused by oil spills in a region, as well as the consequences of oil exploration and extraction on the environment, economy, and politics. The concept of oil spills, their causes, their different types, and the impacts of these calamities on the marine ecosystem are all covered in detail in this review. Oil spill management and response are essential for the environment and society. This review also provides basic information on monitoring oil spills from space. Optical and microwave remote sensing techniques have been used to address oil spill monitoring issues. The possibility of false alarms from lookalikes is the main problem when using radar and microwave data to monitor an oil spill. Therefore, numerous issues must be addressed to detect oil spills in space. It is crucial to combine these technologies with additional approaches such as in situ measurements and ground-based observations.

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Kumar, Suresh, and Vijay Bhagat. "Remote Sensing Satellites for Land Applications: A Review." Remote Sensing of Land 2, no. 2 (July 4, 2019): 96–104. http://dx.doi.org/10.21523/gcj1.18020203.

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Satellite remote sensing offers a unique opportunity in deriving various components of land information by integrating with ground based observation. Currently several remote sensing satellites are providing multispectral, hyperspectral and microwave data to cater the need of various land applications. Several old age remote sensing satellites have been updated with new generation satellites offering high spatial, spectral and temporal resolution. Microwave remote sensing data is now available with high spatial resolution and providing land information in cloudy weather condition that strengthening availability of remote sensing data in all days. Spatial resolution has significantly improved over the decades and temporal resolution has improved from months to daily. Indian Remote Sensing programs are providing state of the art satellite data in optical and microwave wavelength regions to meet large land applications in the country. Today several remote sensing data is available as open data sources. Upcoming satellite remote sensing data will help in precise characterization and quantification of land resources to support in sustainable land development planning to meet future challenges.

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Schlüter, Norbert, and Georg Heygster. "Remote sensing of Antarctic clouds with infrared and passive microwave sensors." Meteorologische Zeitschrift 11, no. 1 (March 5, 2002): 21–36. http://dx.doi.org/10.1127/0941-2948/2002/0011-0021.

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Barsukov, I. A., V. V. Boldyrev, M. I. Gavrilov, G. E. Evseev, A. N. Egorov, P. A. Il’gasov, V. Yu Pantsov, et al. "Satellite Microwave Radiometry for Earth Remote Sensing." Rocket-space device engineering and information systems 8, no. 1 (2021): 11–23. http://dx.doi.org/10.30894/issn2409-0239.2021.8.1.11.23.

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The issues of development of the direction of satellite microwave radiometry in Russia in the interests of operational meteorology and oceanography are considered. The analysis of the current state of Russian and foreign radiometric ERS equipment in the microwave range is carried out. The technical characteristics of onboard multichannel microwave radiometers, combining the functions of a scanner and a sounder, are analyzed. The issues of metrological support of microwave measurements of equipment installed on Russian satellites of the Meteor-M series are considered. The original method of internal calibration of the MTVZA-GYA microwave scanner/sounding device is analyzed in detail in order to form the antenna temperature scale. The MTVZA-GYA calibration unit measures the radiation intensity of two matched loads with known brightness temperatures (“hot” and “cold”). An on-board calibrator is used as a “hot” load, it serves as an imitator of an absolutely black body, its brightness temperature of which is in the range of 240–300 K. Absolute (external) calibration is a transition from antenna to brightness temperatures and is performed using high-precision radiation calculations for specially selected natural testing sites. The issues of preliminary processing of MTVZA-GYA data are considered and examples of microwave images of the Earth in the scale of brightness temperatures are given.

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Dissertations / Theses on the topic "Microwave remote sensing"

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Strawbridge, Fiona. "Passive microwave remote sensing of vegetation." Thesis, University of Bristol, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242948.

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Au, Wai Chung 1966. "Computational electomagnetics in microwave remote sensing." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/11645.

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Sreerekha, T. R. "Impact of clouds on microwave remote sensing." Berlin Logos-Verl, 2005. http://d-nb.info/979728304/34.

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Remund, Quinn P. "Multisensor microwave remote sensing in the cryosphere /." Diss., CLICK HERE for online access, 2000. http://contentdm.lib.byu.edu/ETD/image/etd7.pdf.

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Remund, Quinn P. "Multisensor Microwave Remote Sensing in the Cryosphere." BYU ScholarsArchive, 2003. https://scholarsarchive.byu.edu/etd/72.

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Because the earth's cryosphere influences global weather patterns and climate, the scientific community has had great interest in monitoring this important region. Microwave remote sensing has proven to be a useful tool in estimating sea and glacial ice surface characteristics with both scatterometers and radiometers exhibiting high sensitivity to important ice properties. This dissertation presents an array of studies focused on extracting key surface features from multisensor microwave data sets. First, several enhanced resolution image reconstruction issues are addressed. Among these are the optimization of the scatterometer image reconstruction (SIR) algorithm for NASA scatterometer (NSCAT) data, an analysis of Ku-band azimuthal modulation in Antarctica, and inter-sensor European Remote Sensing Satellite (ERS) calibration. Next, various methods for the removal of atmospheric distortions in image reconstruction of passive radiometer observations are considered. An automated algorithm is proposed which determines the spatial extent of sea ice in the Arctic and Antarctic regions from NSCAT data. A multisensor iterative sea ice statistical classification method which adapts to the temporally varying signatures of ice types is developed. The sea ice extent and classification algorithms are adopted for current SeaWinds scatterometer data sets. Finally, the automated inversion of large-scale forward electromagnetic scattering of models is considered and used to study the temporal evolution of the scattering properties of polar sea ice.

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English, Stephen James. "Remote sensing of meteorological parameters by microwave radiometry." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302777.

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Xiao, Renmeng. "Passive microwave snow mapping in Quebec." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq29810.pdf.

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Piles, Guillem Maria. "Multiscale soil moisture retrievals from microwave remote sensing observations." Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/77910.

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La humedad del suelo es la variable que regula los intercambios de agua, energía, y carbono entre la tierra y la atmósfera. Mediciones precisas de humedad son necesarias para una gestión sostenible de los recursos hídricos, para mejorar las predicciones meteorológicas y climáticas, y para la detección y monitorización de sequías e inundaciones. Esta tesis se centra en la medición de la humedad superficial de la Tierra desde el espacio, a escalas global y regional. Estudios teóricos y experimentales han demostrado que la teledetección pasiva de microondas en banda L es optima para la medición de humedad del suelo, debido a que la atmósfera es transparente a estas frecuencias, y a la relación directa de la emisividad del suelo con su contenido de agua. Sin embargo, el uso de la teledetección pasiva en banda L ha sido cuestionado en las últimas décadas, pues para conseguir la resolución temporal y espacial requeridas, un radiómetro convencional necesitaría una gran antena rotatoria, difícil de implementar en un satélite. Actualmente, hay tres principales propuestas para abordar este problema: (i) el uso de un radiómetro de apertura sintética, que es la solución implementada en la misión Soil Moisture and Ocean Salinity (SMOS) de la ESA, en órbita desde noviembre del 2009; (ii) el uso de un radiómetro ligero de grandes dimensiones y un rádar operando en banda L, que es la solución que ha adoptado la misión Soil Moisture Active Passive (SMAP) de la NASA, con lanzamiento previsto en 2014; (iii) el desarrollo de técnicas de desagregación de píxel que permitan mejorar la resolución espacial de las observaciones. La primera parte de la tesis se centra en el estudio del algoritmo de recuperación de humedad del suelo a partir de datos SMOS, que es esencial para obtener estimaciones de humedad con alta precisión. Se analizan diferentes configuraciones con datos simulados, considerando (i) la opción de añadir información a priori de los parámetros que dominan la emisión del suelo en banda L —humedad, rugosidad, temperatura del suelo, albedo y opacidad de la vegetación— con diferentes incertidumbres asociadas, y (ii) el uso de la polarización vertical y horizontal por separado, o del primer parámetro de Stokes. Se propone una configuración de recuperación de humedad óptima para SMOS. La resolución espacial de los radiómetros de SMOS y SMAP (40-50 km) es adecuada para aplicaciones globales, pero limita la aplicación de los datos en estudios regionales, donde se requiere una resolución de 1-10 km. La segunda parte de esta tesis contiene tres novedosas propuestas de mejora de resolución espacial de estos datos: • Se ha desarrollado un algoritmo basado en la deconvolución de los datos SMOS que permite mejorar la resolución espacial de las medidas. Los resultados de su aplicación a datos simulados y a datos obtenidos con un radiómetro aerotransportado muestran que es posible mejorar el producto de resolución espacial y resolución radiométrica de los datos. • Se presenta un algoritmo para mejorar la resolución espacial de las estimaciones de humedad de SMOS utilizando datos MODIS en el visible/infrarrojo. Los resultados de su aplicación a algunas de las primeras imágenes de SMOS indican que la variabilidad espacial de la humedad del suelo se puede capturar a 32, 16 y 8 km. • Un algoritmo basado en detección de cambios para combinar los datos del radiómetro y el rádar de SMAP en un producto de humedad a 10 km ha sido desarrollado y validado utilizando datos simulados y datos experimentales aerotransportados. Este trabajo se ha desarrollado en el marco de las actividades preparatorias de SMOS y SMAP, los dos primeros satélites dedicados a la monitorización de la variación temporal y espacial de la humedad de la Tierra. Los resultados presentados contribuyen a la obtención de estimaciones de humedad del suelo con la precisión y la resolución espacial necesarias para un mejor conocimiento del ciclo del agua y una mejor gestión de los recursos hídricos.
Soil moisture is a key state variable of the Earth's system; it is the main variable that links the Earth's water, energy and carbon cycles. Accurate observations of the Earth's changing soil moisture are needed to achieve sustainable land and water management, and to enhance weather and climate forecasting skill, flood prediction and drought monitoring. This Thesis focuses on measuring the Earth's surface soil moisture from space at global and regional scales. Theoretical and experimental studies have proven that L-band passive remote sensing is optimal for soil moisture sensing due to its all-weather capabilities and the direct relationship between soil emissivity and soil water content under most vegetation covers. However, achieving a temporal and spatial resolution that could satisfy land applications has been a challenge to passive microwave remote sensing in the last decades, since real aperture radiometers would need a large rotating antenna, which is difficult to implement on a spacecraft. Currently, there are three main approaches to solving this problem: (i) the use of an L-band synthetic aperture radiometer, which is the solution implemented in the ESA Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009; (ii) the use of a large lightweight radiometer and a radar operating at L-band, which is the solution adopted by the NASA Soil Moisture Active Passive (SMAP) mission, scheduled for launch in 2014; (iii) the development of pixel disaggregation techniques that could enhance the spatial resolution of the radiometric observations. The first part of this work focuses on the analysis of the SMOS soil moisture inversion algorithm, which is crucial to retrieve accurate soil moisture estimations from SMOS measurements. Different retrieval configurations have been examined using simulated SMOS data, considering (i) the option of adding a priori information from parameters dominating the land emission at L-band —soil moisture, roughness, and temperature, vegetation albedo and opacity— with different associated uncertainties and (ii) the use of vertical and horizontal polarizations separately, or the first Stokes parameter. An optimal retrieval configuration for SMOS is suggested. The spatial resolution of SMOS and SMAP radiometers (~ 40-50 km) is adequate for global applications, but is a limiting factor to its application in regional studies, where a resolution of 1-10 km is needed. The second part of this Thesis contains three novel downscaling approaches for SMOS and SMAP: • A deconvolution scheme for the improvement of the spatial resolution of SMOS observations has been developed, and results of its application to simulated SMOS data and airborne field experimental data show that it is feasible to improve the product of the spatial resolution and the radiometric sensitivity of the observations by 49% over land pixels and by 30% over sea pixels. • A downscaling algorithm for improving the spatial resolution of SMOS-derived soil moisture estimates using higher resolution MODIS visible/infrared data is presented. Results of its application to some of the first SMOS images show the spatial variability of SMOS-derived soil moisture observations is effectively captured at the spatial resolutions of 32, 16, and 8 km. • A change detection approach for combining SMAP radar and radiometer observations into a 10 km soil moisture product has been developed and validated using SMAP-like observations and airborne field experimental data. This work has been developed within the preparatory activities of SMOS and SMAP, the two first-ever satellites dedicated to monitoring the temporal and spatial variation on the Earth's soil moisture. The results presented contribute to get the most out of these vital observations, that will further our understanding of the Earth's water cycle, and will lead to a better water resources management.

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Stephen, Haroon. "Microwave Remote Sensing of Saharan Ergs and Amazon Vegetation." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1461.pdf.

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Ramnath, Vinod. "Estimation of soil moisture using active microwave remote sensing." Master's thesis, Mississippi State : Mississippi State University, 2003.

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Books on the topic "Microwave remote sensing"

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Calla, O. P. N. Microwave remote sensing. Edited by Saravanan A, Defence Research & Development Organisation (India), and Defence Scientific Information and Documentation Centre (India). New Delhi: Defence Research & Development Organisation, Ministry of Defence, India, 2009.

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1942-, Kong Jin Au, and Shin Robert T, eds. Theory of microwave remote sensing. New York: Wiley, 1985.

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Woodhouse, Iain H. Introduction to microwave remote sensing. Boca Raton, FL: CRC/Taylor & Francis, 2006.

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Introduction to microwave remote sensing. Boca Raton, FL: Taylor&Francis, 2005.

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M, Brennan Ann, and World Data Center A for Glaciology., eds. Passive microwave research: Microwave bibliography update, 1988-1991. Boulder, Colo., U.S.A. (Box 449, Boulder 80309): World Data Center for Glaciology (Snow and Ice), Cooperative Institute for Research in Environmental Sciences, University of Colorado, 1992.

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1937-, Janssen Michael A., ed. Atmospheric remote sensing by microwave radiometry. New York: Wiley, 1993.

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K, Moore Richard, and Fung Adrian K, eds. Microwave remote sensing: Active and passive. Dedham, MA: Artech House, 1986.

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Carsey, Frank D., ed. Microwave Remote Sensing of Sea Ice. Washington, D. C.: American Geophysical Union, 1992. http://dx.doi.org/10.1029/gm068.

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Yu, Raizer Victor, ed. Passive microwave remote sensing of oceans. Chichester: Wiley, 1998.

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Ulaby, Fawwaz T. Microwave remote sensing: Active and passive. Norwood, Mass: Artech House, 1986.

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Book chapters on the topic "Microwave remote sensing"

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Gupta, Ravi Prakash. "Microwave Sensors." In Remote Sensing Geology, 149–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-662-12914-2_10.

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Gupta, Ravi Prakash. "Microwave Sensors." In Remote Sensing Geology, 317–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05283-9_12.

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Gupta, Ravi P. "Microwave Sensors." In Remote Sensing Geology, 221–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-55876-8_15.

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Maul, G. A. "Microwave Remote Sensing." In Introduction to satellite oceanography, 397–505. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5061-0_5.

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Awange, Joseph, and John Kiema. "Microwave Remote Sensing." In Environmental Geoinformatics, 137–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03017-9_9.

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Awange, Joseph L., and John B. Kyalo Kiema. "Microwave Remote Sensing." In Environmental Geoinformatics, 133–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34085-7_9.

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Skou, Niels. "Microwave Radiometers." In Encyclopedia of Remote Sensing, 382–85. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_94.

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Ruf, Christopher. "Calibration, Microwave Radiometers." In Encyclopedia of Remote Sensing, 46–47. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_11.

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Rahmat-Samii, Yahya. "Microwave Horn Antennas." In Encyclopedia of Remote Sensing, 375–82. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_92.

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Skou, Niels. "Microwave Radiometers, Conventional." In Encyclopedia of Remote Sensing, 386–89. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-0-387-36699-9_95.

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Conference papers on the topic "Microwave remote sensing"

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Costes, Laurent, Chris Bushell, Michael J. Buckley, and Graeme Mason. "Microwave Humidity Sounder (MHS) antenna." In Remote Sensing, edited by Hiroyuki Fujisada and Joan B. Lurie. SPIE, 1999. http://dx.doi.org/10.1117/12.373211.

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Krimchansky, Sergey, Joel Susskind, Alexander Krimchansky, Donald Chu, Robert Lambeck, and Martin A. Davis. "GEO sounding using microwave instruments." In Remote Sensing, edited by Roland Meynart, Steven P. Neeck, and Haruhisa Shimoda. SPIE, 2004. http://dx.doi.org/10.1117/12.565283.

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Jiang, JingShang, He-guang Liu, Bin-qiang Zheng, Zhong-fan Fan, and Kai Zhao. "Multimode microwave remote sensor." In Satellite Remote Sensing, edited by Joan B. Lurie, Paolo Pampaloni, and James C. Shiue. SPIE, 1994. http://dx.doi.org/10.1117/12.197348.

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Tabart, C., F. Bayle, and Marc Trier. "Receiver for the microwave humidity sounder." In Remote Sensing, edited by Jaqueline E. Russell. SPIE, 1999. http://dx.doi.org/10.1117/12.373049.

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Lambrigtsen, B. H., S. T. Brown, S. J. Dinardo, T. C. Gaier, P. P. Kangaslahti, A. B. Tanner, J. R. Piepmeier, et al. "GeoSTAR: a microwave sounder for geostationary applications." In Remote Sensing, edited by Roland Meynart, Steven P. Neeck, and Haruhisa Shimoda. SPIE, 2006. http://dx.doi.org/10.1117/12.689121.

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Bidwell, Steven W. "Global precipitation measurement (GPM) microwave imager (GMI) instrument." In Remote Sensing, edited by Roland Meynart, Steven P. Neeck, and Haruhisa Shimoda. SPIE, 2006. http://dx.doi.org/10.1117/12.692339.

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Terentiev, Evgeni N., Nikolai E. Terentiev, and Fedor V. Shugaev. "Ultraresolution of microwave, color, and synthetic color images." In Remote Sensing, edited by Lorenzo Bruzzone. SPIE, 2004. http://dx.doi.org/10.1117/12.565619.

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Bombaci, Ornella, Michele L'Abbate, Carlo Svara, Francesco Caltagirone, and J. Guijarro. "ENVISAT-1 Microwave Radiometer (MWR): validation campaign achievements." In Remote Sensing, edited by Hiroyuki Fujisada. SPIE, 1998. http://dx.doi.org/10.1117/12.333624.

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Plyuschev, Victor, Leonid A. Mel'nikov, Yury Krylov, Valentin Andrianov, and Alexander Malinin. "Multichannel scanning microwave spaceborne radiometer." In Satellite Remote Sensing, edited by Joan B. Lurie, Paolo Pampaloni, and James C. Shiue. SPIE, 1994. http://dx.doi.org/10.1117/12.197344.

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Imperatore, Pasquale, Antonio Iodice, and Daniele Riccio. "Microwave remote sensing of natural stratification." In SPIE Remote Sensing. SPIE, 2011. http://dx.doi.org/10.1117/12.898355.

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Reports on the topic "Microwave remote sensing"

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Ramani, Suchitra. Microwave remote sensing for atmospheric chemistry. Office of Scientific and Technical Information (OSTI), September 2018. http://dx.doi.org/10.2172/1471300.

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Randa, J. Traceability for microwave remote-sensing radiometry. Gaithersburg, MD: National Institute of Standards and Technology, 2004. http://dx.doi.org/10.6028/nist.ir.6631.

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Kong, Jin A. Polarimetric Microwave Remote Sensing of the Ocean Surface. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada389270.

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Ferriday, J. G. Satellite remote sensing of global rainfall using passive microwave radiometry. Office of Scientific and Technical Information (OSTI), December 1994. http://dx.doi.org/10.2172/642694.

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Vesecky, John F. Ocean Surface Wind Retrieval Using Passive, Polarimetric Microwave Remote Sensing. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada628803.

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Sokol, J., T. J. Pultz, and A. E. Walker. Passive and Active Airborne Microwave Remote Sensing of Snow Cover. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1999. http://dx.doi.org/10.4095/219518.

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Werle, D. Radar remote sensing for application in forestry: a literature review for investigators and potential users of SAR data in Canada. Natural Resources Canada/CMSS/Information Management, 1989. http://dx.doi.org/10.4095/329188.

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Information provided in this document allows potential users of synthetic aperture radar (SAR) imagery as well as investigators participating in the Canadian Radar Data Development Program (RDDP) to obtain an overview of achievements, limitations and future potential of radar remote sensing for application in forestry, as portrayed in the published literature. Investigations concerned with radar remote sensing and its potential for application in forestry are reviewed. The main focus of these studies was the determination of microwave backscatter characteristics of forestry targets using different radar parameters, such as frequency, polarizations and incidence angle. Examples of selected targets include the following: coniferous and deciduous tree species, stands of different structure, age, tree height, clearcuts, or forestry environments in general as they change with the seasons. More than 75 studies based on airborne imaging radar, spaceborne radar as well as scatterometer data have been considered. Previous reviews which summarize information available in western Europe and North America are briefly introduced. Then, recent investigations covering the time period from the early 1980's onward are portrayed and discussed. The main results are summarized in a set of conclusions, followed by list of selected references and a list of Canadian institutions and organizations currently involved in radar remote sensing R&D for application in forestry.

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