{"title":"THE FEASIBILITY STUDY OF LAND SURFACE TEMPER-ATURE MEASUREMENTS FROM SPACE","authors":"Z. Wan","doi":"10.11834/jrs.1989010","DOIUrl":"https://doi.org/10.11834/jrs.1989010","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123456054","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":"Technologies of extracting land utilization information based on SVM method with multi-window texture","authors":"K. Le","doi":"10.11834/jrs.20120415","DOIUrl":"https://doi.org/10.11834/jrs.20120415","url":null,"abstract":"In order to overcome the problem of fragmentation of ground objects and low accuracy in the single window texture classification,we present a new method of classification using SVM based on multi-window texture,using the Changjiaoba town of Foping county in Shaanxi Province as the test area.First we established the SVM classification model combined with texture analysis based on texture extraction from SPOT 5 remote sensing image.Then we used the model to classify and analyze the types of land use in the area by comparing it with single window texture classification and single data source(spectrum) SVM classification.The research result showed an overall accuracy for multi-window texture classification of 85.33%,which was 13.11% higher than the single window texture classification and 24.10% than single data source(spectrum) SVM.Therefore,we conclude that the method is effective and could solve the problem of fragmentation of ground objects and low accuracy in the single window texture classification.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"27 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123574974","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":"Spatial Resolution Enhancement of Microwave Radiometer Using BG Algorithm","authors":"Jiang Jing-shan","doi":"10.11834/jrs.20040505","DOIUrl":"https://doi.org/10.11834/jrs.20040505","url":null,"abstract":"In this paper, a BG algorithm to enhance the spatial resolution of microwave radiometer is introduced. The main principle of the BG algorithm is as follows. A higher resolution image can be obtained using the linear combination of the adjacent measurements if the density of the measurement is larger than that of the instrument. The principle is also suitable for other microwave remote sensing sensors. The tunable parameter referenced from the study of Stogryn is introduced in this paper, which it can balance the tradeoff between the spatial resolution and the system sensitivity, and prevent increasing the flicker noise of the image too serious when high spatial resolution is pursued. Simulated images of microwave radiometer at 20, 50, and 90GHz were enhanced. The rate of spatial resolution enhancement depends on the density of the sampling.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123711235","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":"Analysis on Urban Environment in Tangshan Using SPOT Image","authors":"Zhihuai Guo","doi":"10.11834/jrs.1987036","DOIUrl":"https://doi.org/10.11834/jrs.1987036","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125288111","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 Method for Fast Resampling of Remote Sensing Imagery","authors":"Yang Jin-song","doi":"10.11834/jrs.20020204","DOIUrl":"https://doi.org/10.11834/jrs.20020204","url":null,"abstract":"A method for fast resampling of remote sensing imagery has been developed based on the nature of the geometric distortion of raw imagery. The method was applied to resample SeaStar SeaWiFS and NOAA AVHRR images. Examples of the resampling of SeaStar SeaWiFS images are presented by using the results have shown that the resampling using the method suggested in this paper is much faster than other resampling methods. A weighted neighbour intensity interpolation has also been proposed. The quality of the resampled images is improved. The weighted neighbour intensity interpolation. Advantages of the weighted neighboun intensity interpolation over the nearest-neighbour and bilinear intensity interpolations have been discussed.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125337425","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":"Multi-exponential model based bias field correction of SAR sea ice image","authors":"Wang Gengzhong","doi":"10.11834/jrs.20110113","DOIUrl":"https://doi.org/10.11834/jrs.20110113","url":null,"abstract":"The paper proposes a novel algorithm of SAR sea ice image incidence angle bias field correction using multi-exponential model.In the algorithm,the image mean values along SAR azimuth direction are firstly calculated.Then an one-dimensional correction field is modeled by a multi-exponential model.Whereafter,the one-dimensional correction field is calculated by applying entropy minimization method.After that the original image is corrected by the two-dimensional correction field derived from the one-dimensional correction field.The experiment result indicates that the proposed algorithm is effective in correcting SAR sea ice image's incidence angle bias field.Besides,the proposed algorithm has better correction result than Karvonen's method without the incidence angle information of the pixels.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125391360","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":"Study on Multi-source Data Acquisitionin Airborne Scanning Laser Ranging-Imager Sensor","authors":"X. Yong-qi","doi":"10.11834/jrs.20020203","DOIUrl":"https://doi.org/10.11834/jrs.20020203","url":null,"abstract":"The Airborne Scanning Laser Ranging-Imager Sensor (ASLRIS) is a new generation of remote sensing and mapping system for providing 3D geosciences information. The system integrates the laser altimeter, IR imager, Differential Global Positioning System (DGPS) and Inertial Navigation System (INS), by which Digital Elevation Model (DEM) and Georeferenced Image (GI) can be generated quickly and effectively without ground control points. The electric synchronization technology makes sampling-time in consistency with laser ranger and scanning imager to match height data and image data.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125541181","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}
Xingfeng Chen, Li Liu, Jiaguo Li, Wenhao Ou, Yuhuan Zhang
{"title":"Application and research progress of fire monitoring using satellite remote sensing","authors":"Xingfeng Chen, Li Liu, Jiaguo Li, Wenhao Ou, Yuhuan Zhang","doi":"10.11834/jrs.20209118","DOIUrl":"https://doi.org/10.11834/jrs.20209118","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125581048","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}