Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578470
P. Gaiser, W.C. Boncyk, C. Swift
The following paper describes a K-Band Autocorrelation Radiometer called CORRAD. The purpose of CORRAD is to measure tropospheric water vapor. A description of the hardware is included. The calibration technique is described in detail.
{"title":"Calibration of a K-Band Autocorrelation Radiometer","authors":"P. Gaiser, W.C. Boncyk, C. Swift","doi":"10.1109/IGARSS.1992.578470","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578470","url":null,"abstract":"The following paper describes a K-Band Autocorrelation Radiometer called CORRAD. The purpose of CORRAD is to measure tropospheric water vapor. A description of the hardware is included. The calibration technique is described in detail.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133749493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576684
V. Etkin, A. Kuzmin, Y.G. Trokhimoveky
{"title":"IR and microwave sea surface observations under calm weather conditions","authors":"V. Etkin, A. Kuzmin, Y.G. Trokhimoveky","doi":"10.1109/IGARSS.1992.576684","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576684","url":null,"abstract":"","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133781812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576681
I. Sano, S. Mukai
A procedure to derive the chlorophyll map using the CZCS data is described here. Phytoplankton pigment concentration near the sea surface is estimated from the ocean color data. It is shown here how 11. SYSTEM FLOW to derive an improved pigment map of the sea surface from the Nimbus-7 CZCS data, and also shown that the obtained results partly coincide with the truth data near Japan.
{"title":"Pigment Concentration Derived From Ocean Color","authors":"I. Sano, S. Mukai","doi":"10.1109/IGARSS.1992.576681","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576681","url":null,"abstract":"A procedure to derive the chlorophyll map using the CZCS data is described here. Phytoplankton pigment concentration near the sea surface is estimated from the ocean color data. It is shown here how 11. SYSTEM FLOW to derive an improved pigment map of the sea surface from the Nimbus-7 CZCS data, and also shown that the obtained results partly coincide with the truth data near Japan.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115522906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578294
M. Dawson, J. Olvera, A. Fung, M. Manry
A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.
{"title":"Inversion of Surface Parameters Using Fast Learning Neural Networks","authors":"M. Dawson, J. Olvera, A. Fung, M. Manry","doi":"10.1109/IGARSS.1992.578294","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578294","url":null,"abstract":"A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115646158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578487
D. Tanré, E. Vermote, B. Holben, Y. Kaufman
Remote sensing of aerosol optical thickness from space is difficult over continental surfaces. There are two retrieval algorithms, one based on the use of dark targets and a second based on contrast reduction between selected pixels. Improvements in the contrast reduction method are reported. A procedure is developed for using the satellite image to evaluate whether conditions for applying the structure method are met. The theoretical background is discussed, and the usefulness of the structure functions is demonstrated. The method is applied to NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery where simultaneous ground measurements are used for validation.
{"title":"Satellite Aerosols Retrieval Over Land Surfaces Using the Structure Functions","authors":"D. Tanré, E. Vermote, B. Holben, Y. Kaufman","doi":"10.1109/IGARSS.1992.578487","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578487","url":null,"abstract":"Remote sensing of aerosol optical thickness from space is difficult over continental surfaces. There are two retrieval algorithms, one based on the use of dark targets and a second based on contrast reduction between selected pixels. Improvements in the contrast reduction method are reported. A procedure is developed for using the satellite image to evaluate whether conditions for applying the structure method are met. The theoretical background is discussed, and the usefulness of the structure functions is demonstrated. The method is applied to NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery where simultaneous ground measurements are used for validation.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124194757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578655
E. Mougin, D. Lo Seen, S. Rambal, B. Lacaze
{"title":"A Regional Sahelian Grassland Model to Be Coupled with Satellite Multispectral Data","authors":"E. Mougin, D. Lo Seen, S. Rambal, B. Lacaze","doi":"10.1109/IGARSS.1992.578655","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578655","url":null,"abstract":"","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114572349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576700
Ke Zhang
Expert systems (ES) have been shown to be useful in many areas of natural resource and environmental impact studies. However, the major obstacle in the development of expert system is difficult to extract expert’s knowledge into a knowledge base. An alternative approach that can overcome the obstacle is to extract domain knowledge from information system by machine learning. This study is the first experiment of knowledge extraction from geographic information system (KEGIS). Major effort in this study is to develop a landuse expert system with a knowledge base that is generated by learning from sample data of a geographic information system (GIS). In this study, 154 sample areas were selected from Wongnute County, Inner Mongolia, for knowledge base extraction. With the landuse knowledge base, an inference engine, and a user interface, a landuse expert system has been constructed for landuse consulting. In an accuracy test, The landuse expert system can provide 73% of correct siggestions. This result ;how& that the knowledge base created by KEGIS can closely represent the ’real world‘.
{"title":"Expert System Based On Knowledge Extraction From A GIS","authors":"Ke Zhang","doi":"10.1109/IGARSS.1992.576700","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576700","url":null,"abstract":"Expert systems (ES) have been shown to be useful in many areas of natural resource and environmental impact studies. However, the major obstacle in the development of expert system is difficult to extract expert’s knowledge into a knowledge base. An alternative approach that can overcome the obstacle is to extract domain knowledge from information system by machine learning. This study is the first experiment of knowledge extraction from geographic information system (KEGIS). Major effort in this study is to develop a landuse expert system with a knowledge base that is generated by learning from sample data of a geographic information system (GIS). In this study, 154 sample areas were selected from Wongnute County, Inner Mongolia, for knowledge base extraction. With the landuse knowledge base, an inference engine, and a user interface, a landuse expert system has been constructed for landuse consulting. In an accuracy test, The landuse expert system can provide 73% of correct siggestions. This result ;how& that the knowledge base created by KEGIS can closely represent the ’real world‘.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114812288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578322
P. Hardin, D. G. Long
Satellite wind scatterometers are microwave radars designed to measure near-surface wind speed and direction over the oceans. This was the primary mission for the Seasat-A Scatterometer (SASS), which acquired 14.6 Ghz data over 50 km resolution cells during its three month mission in 1978. However, an image reconstruction technique utilizing overlap in resolution cells from successive satellite orbits can improve that spatial resolution to 5 km over land. An experiment conducted on a reconstructed image of central South America illustrates the potential of this imagery for discriminating between tropical forest, woodland, and tropical grass-shrubland. The potential for deriving geophysical information from reconstructed scatterometer imagery of the earth's surface is discussed.
{"title":"Land Imaging with Reconstructed High-Resolution Seasat-A Scatterometer Data an Amazon Experiment","authors":"P. Hardin, D. G. Long","doi":"10.1109/IGARSS.1992.578322","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578322","url":null,"abstract":"Satellite wind scatterometers are microwave radars designed to measure near-surface wind speed and direction over the oceans. This was the primary mission for the Seasat-A Scatterometer (SASS), which acquired 14.6 Ghz data over 50 km resolution cells during its three month mission in 1978. However, an image reconstruction technique utilizing overlap in resolution cells from successive satellite orbits can improve that spatial resolution to 5 km over land. An experiment conducted on a reconstructed image of central South America illustrates the potential of this imagery for discriminating between tropical forest, woodland, and tropical grass-shrubland. The potential for deriving geophysical information from reconstructed scatterometer imagery of the earth's surface is discussed.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114546450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.576714
A. Monti-Guarnieri, C. Prati, F. Rocca
Wave domain SAR focusing can he exactly implemented hp means of the Stolt interpolation if rectangular geometries are assumed and targets are fixed. However, when target’s motion has to he considered, or when the sensor trajectory is not a straight line parallel to the sources, the Stolt interpolation is just an approximation. This paper introduces first an exact focusing technique for uniform target motion. Secondly, the Stolt interpolation is extended to non rectilinear motion of the sensors.
{"title":"SAR Focusing In Non-standard Geometries: A Generalized Approach","authors":"A. Monti-Guarnieri, C. Prati, F. Rocca","doi":"10.1109/IGARSS.1992.576714","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.576714","url":null,"abstract":"Wave domain SAR focusing can he exactly implemented hp means of the Stolt interpolation if rectangular geometries are assumed and targets are fixed. However, when target’s motion has to he considered, or when the sensor trajectory is not a straight line parallel to the sources, the Stolt interpolation is just an approximation. This paper introduces first an exact focusing technique for uniform target motion. Secondly, the Stolt interpolation is extended to non rectilinear motion of the sensors.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"391 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120864980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1992-05-26DOI: 10.1109/IGARSS.1992.578490
S. Liang, A. Strahler
Based on a rigorous canopy radiative transfer equation, the multiple scattering radiance is approximated by the asymptotic theory, and the single scattering radiance calculation, which requires an numerical intergration due to considering the hotspot effect, is simplified. A new formulation is presented to obtain more exact angular dependence of the sky radiance distribution. The unscattered solar radiance and single scattering radiance are calculated exactly, and the multiple scattering is approximated by the delta two-stream atmospheric radiative transfer model. The numerical algorithms prove that the parametric canopy model is very accurate, especially when the viewing angles are smaller than 55 deg. The Powell algorithm is used to retrieve biospheric parameters from the ground measured multiangle observations.
{"title":"An Explicit Canopy Brdf Model and Inversion","authors":"S. Liang, A. Strahler","doi":"10.1109/IGARSS.1992.578490","DOIUrl":"https://doi.org/10.1109/IGARSS.1992.578490","url":null,"abstract":"Based on a rigorous canopy radiative transfer equation, the multiple scattering radiance is approximated by the asymptotic theory, and the single scattering radiance calculation, which requires an numerical intergration due to considering the hotspot effect, is simplified. A new formulation is presented to obtain more exact angular dependence of the sky radiance distribution. The unscattered solar radiance and single scattering radiance are calculated exactly, and the multiple scattering is approximated by the delta two-stream atmospheric radiative transfer model. The numerical algorithms prove that the parametric canopy model is very accurate, especially when the viewing angles are smaller than 55 deg. The Powell algorithm is used to retrieve biospheric parameters from the ground measured multiangle observations.","PeriodicalId":441591,"journal":{"name":"[Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium","volume":"41 5-6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116167663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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