IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)最新文献
{"title":"Environmental land degradation assessment in semi-arid Indus basin area using IRS-1B LISS-II data","authors":"N. M. Khan, Y. Sato","doi":"10.1109/IGARSS.2001.977916","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.977916","url":null,"abstract":"Degradation due to hydro-salinity in the Indus basin semi-arid irrigated area of Pakistan has deteriorated the vast productive agricultural land. The present approach was an effort through various GIS and remote sensing techniques like, image registration, color composites interpretation, vegetation and salinity indices, empirical modeling, interpolations, overlaying, and supervised classification (MLC), providing information about the cause, extent and magnitude of hydro-salinity prone areas.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124328502","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}
{"title":"Feature extraction and classification of urban high-resolution satellite imagery based on morphological preprocessing","authors":"J. Benediktsson, M. Pesaresi","doi":"10.1109/IGARSS.2001.976213","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.976213","url":null,"abstract":"Classification of panchromatic high resolution data from urban areas using a three-step approach based on morphological preprocessing is investigated. First, the morphological composition of geodesic opening and closing operations of different sizes is used in order to build a morphological profile. Secondly, feature extraction is applied in the second step. Thirdly, statistical classifiers are used to classify the features. Examples of the application of the proposed method are given for one satellite high-resolution data set from Athens, Greece. Both discriminant analysis (DA) and decision boundary feature extraction (DBFE) are applied successfully in the feature extraction phase. For the statistical classification, original, leave-one out (LOO), and enhanced statistics are used and evaluated. In experiments, the use of DA and DBFE shows promise when used with original and LOO statistics.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"7 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124098203","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}
{"title":"Application of remote sensing data for oil spill monitoring in the Guanabara Bay, Rio de Janeiro, Brazil","authors":"C. Bentz, F. Pellon de Miranda","doi":"10.1109/IGARSS.2001.976149","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.976149","url":null,"abstract":"This paper describes the application of remote sensing data for oil spill monitoring in the Guanabara Bay, Rio de Janeiro, Brazil. During the emergency, Landsat-5/TM (Thematic Mapper) and Radarsat-1 data were acquired to monitor the location of the spill and its movement. Image classification procedures have been utilized to highlight oil-covered areas on the water surface. Ambiguities in the oil detection were resolved with the aid of ancillary information in a GIS (geographic information system) environment. The results obtained helped PETROBRAS to optimize the emergency response procedures and subsequent cleaning efforts.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124101939","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}
J. Rogan, J. Franklin, D. Stow, L. Levien, C. Fischer
{"title":"Toward operational monitoring of forest cover change in California using multitemporal remote sensing data","authors":"J. Rogan, J. Franklin, D. Stow, L. Levien, C. Fischer","doi":"10.1109/IGARSS.2001.978266","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.978266","url":null,"abstract":"This paper presents preliminary results of research to improve upon an existing operational forest change detection monitoring strategy in California. Comparisons were. made between Landsat 5 TM and Landsat 7 ETM scene normalization techniques (absolute versus, relative). Prior to normalization, scenes containing wildfire smoke plumes were successfully corrected using a space-varying haze equalization algorithm. Simple dark object subtraction provided improved performance over relative (pseudo-invariant feature) approaches. A decision tree classifier produced high change map overall accuracy (86%) for five categories of forest cover change.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128103539","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}
{"title":"Minimum band set to classify AVHRR images","authors":"E. Piazza","doi":"10.1109/IGARSS.2001.977110","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.977110","url":null,"abstract":"Evaluates if multispectral IR satellite images can be classified using only two bands and how far from optimal such classification can be. Two different unsupervised classification algorithms for image classification have been applied to AHVRR (Advanced Very High Resolution Radiometer) images coming from the NOAA-14 (National Oceans and Atmospheric Administration) polar orbiter satellite. The goal is to assign each pixel to one of the following classes: sea, land, cloud, cloud edge or out of the scene. The last class is needed since the images are resampled with always the same geographical limit, thus, sometimes, due to the satellite being low on the horizon, some pixels can be out of the radiometer view. The first method is based on thresholds on the value of the NDVI (Normalized Differential Vegetation Index) alone. The second method is based on thresholds on 4 of the 5 bands of the AVHRR.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128113324","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}
{"title":"CARABAS measurements of coniferous forest stem volume on sloping terrain","authors":"G. Smith, L. Ulander, J. Fransson, F. Walter","doi":"10.1109/IGARSS.2001.978288","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.978288","url":null,"abstract":"Low frequency SAR has shown good results for the retrieval of stem volume in coniferous forests, where the scattering strength is directly related to the volume of the trunk. However, since the scattering is dominated by the trunk-ground dihedral mechanism, it is also sensitive to the topography (i.e. angle between trunk and ground). Using data from CARABAS, we show how the backscattering is sensitive to the topography and radar viewing geometry. However, unlike higher frequencies, the VHF scattering from trees on moderate slopes is still dominated by the trunk-ground interaction.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125457578","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}
{"title":"Color image segmentation using false colors and its applications to geo-images treatment: alphanumeric character recognition","authors":"S. Levachkine, A. Velázquez, V. Alexandrov","doi":"10.1109/IGARSS.2001.977952","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.977952","url":null,"abstract":"In this work an approach is proposed to segment the alphanumeric characters that present in a cartographic color map, using the model-of color RGB. Corresponding raster image is obtained by means of scanning, following to the strategies proposed in S. Levachkine et al. (2000). Our approach does not require a preprocessing of the images, because they only maintain the pixels that really belong to the characters we wish to segment, eliminating all those pixels that are not of interest, produced by a noise or obtained due to erroneous selection of scan parameters (for example, scan resolution), etc. The following identification of the alphanumeric characters supports by a set of neural network and the dictionaries with the character names related to the map or particular application that has previously been prepared.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125796117","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}
{"title":"Regional susceptibility, possibility and risk analyses of landslide in Ulsan Metropolitan City, Korea","authors":"S. Lee, B. Chang, W. Choi, E. Shin","doi":"10.1109/IGARSS.2001.977039","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.977039","url":null,"abstract":"The three steps of landslide hazard analysis such as susceptibility, possibility, and risk were performed to study area, Ulsan, using GIS. The susceptibility is a function of the probability of potential landslide occurrence and landslide-related factors. The possibility depends on the impact factor such as rainfall, earthquake and human activity and on the susceptibility. The risk depends on vulnerable objects such as people and property, and on the possibility. For the analyses, the topographic, geologic, soil, forest, meteorological, and population and facility database were constructed using GIS. Landslide susceptibility was analyzed using the landslide-occurrence factors by probability method that is summation of landslide occurrence probability values per each factors range or type. For landslide possibility analysis, the rainfall frequency map that was extracted from meteorological database was added to the susceptibility map, because most of the landslides in Korea occurred by heavy rain. For landslide risk analysis, the population and facility density maps that were created from the population and facility database were added to the possibility map.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121775407","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}
{"title":"Estimation of optical parameters of yellow sand dust clouds over desert areas from satellite-level data","authors":"T. Kusaka, S. Mori, T. Suzuki, H. Shibata","doi":"10.1109/IGARSS.2001.978013","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.978013","url":null,"abstract":"The yellow sand dust (called \"kosa\" in Japanese) transported from the deserts in the northern part of China often covers over East Asia in the late winter and spring. The dust particles in the atmosphere are regarded as a main source of atmospheric aerosols in East Asia. In this study, a new algorithm for estimating the optical properties of yellow sand dusts in the atmosphere and ground reflectances from ADEOS/POLDER data is described. First, the long-range transport of yellow sand dust was simulated to estimate the transport paths and the global mass distribution of yellow sand dust, because it is difficult to identify the widely spread hazy kosa cloud from POLDER data. Next, the optical properties of hazy kosa clouds over the desert area and ground reflectances were estimated, using the multi-viewing reflectances and polarizations at wavelengths 443 nm and 670 nm in several points selected from the POLDER image. As a result, it is shown that the refractive index of yellow sand dust is in the range from 1.45 to 1.55, and the optical thickness of yellow sand dust, t(443 nm) is 0.42 to 0.47, ground reflectance of the desert is 0.09 to 0.15 at the 443 nm channel, 0.28 to 0.31 at the 670 nm channel.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131381047","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}
{"title":"A wavelet based algorithm for pan sharpening Landsat 7 imagery","authors":"R. King, Jianwen Wang","doi":"10.1109/IGARSS.2001.976657","DOIUrl":"https://doi.org/10.1109/IGARSS.2001.976657","url":null,"abstract":"At IGARSS 2000 the Data Fusion Committee began the sponsorship of a series of contests with which the committee aimed to reach two goals. The first goal was to assess the state of the art of a clearly defined aspect of the data fusion field by empirically evaluating algorithms. The second goal was to identify collective weaknesses of current algorithms, so as to identify requirements of further research. The first contest focused in the sharpening of 30-m resolution multispectral images by using 15-m panchromatic imagery. The objective of the sharpening was to improve the spatial resolution of the multispectral imagery, while preserving the spectral information in homogeneous areas. For the IGARSS 2000 contest, Landsat 7 Thematic Mapper data acquired over urban and agricultural areas was used. Researchers from the Remote Sensing Technologies Center at Mississippi State University won the contest. This paper describes the pan sharpening methodology used.","PeriodicalId":135740,"journal":{"name":"IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132007786","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}