{"title":"The Application of Remote Sensing Techniques in China","authors":"Shijun Yang","doi":"10.1080/01431168708948671","DOIUrl":"https://doi.org/10.1080/01431168708948671","url":null,"abstract":"Abstract The current status of the application of remote sensing techniques in China is described. The Chinese LANDSAT ground station was recently put into operation, and more than thirty low and medium altitude aircraft for remote sensing applications are now operational. Digital image processing systems are now widely used in remote sensing applications, while new instruments and sensors have been developed and are now in use. Applications of remote sensing in China for land resource surveys, urban pollution detection and environmental monitoring, agriculture, forestry, hydrology, geology, coal mining, uranium exploration, glaciology and cryopedology are discussed.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134431229","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":"Optimal integration-based adaptive direction filter for InSAR interferogram","authors":"Wang Ping","doi":"10.11834/jrs.20090609","DOIUrl":"https://doi.org/10.11834/jrs.20090609","url":null,"abstract":"In this paper,we present a new InSAR phase filtering method based on optimal integration. The algorithms can preserve very well the phase details while at the same time smoothing out the noise. Firstly,we use statistical method to determine the number of windows used for the filtering. It is an empirical constant associated with coherence. Secondly,eight linear directional windows are singled out,within each window a filtering is performed,and at the same time the mean coherence for each window is calculated. The proposed filtering will linearly combine a certain number (which has been determined in the first step) of the eight directional windows. However,directional windows with smaller filtering standard deviation will be given priority. Finally,the new phase value is calculated in terms of the weighted mean value of chosen linear windows. In this step,optimal integration is used to determine the weight of each directional window. The proposed filter is adaptively implemented by altering the number of the linear windows selected for filtering according to the coherence. Strategy of using both linear windows and optimal integration makes great difference in the filtering and achieve a good tradeoff between phase noise suppressing and signal preserving. Experimental results with both simulated and real data sets show that the new filter reduces the noise effectively while still minimizing the loss of signals.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"14 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":"115127718","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":"Spatio-temporal variability of Arctic sea ice from 2002 to 2011","authors":"C. Ke, Haitao Peng, Bo Sun, H. Xie","doi":"10.11834/jrs.20132044","DOIUrl":"https://doi.org/10.11834/jrs.20132044","url":null,"abstract":"The significant decline of Arctic sea ice under global warming, especially in summer, plays an important role in global and regional climate change, and affects global and regional ecosystems. Here, the spatio-temporal variations of Arctic sea ice and their causes were analyzed based on satellite microwave AMSR-E data for June 2002 through February 2011. The results showed that the extent of Arctic sea ice decreased by 82800 km2 annually, decreasing most rapidly in summer. The rate of decrease in summer for the period 2002—2011 was more than twice that of 1979—2006; moreover, sea ice concentration also decreased. The sea ice conditions were heavy in 2003 and 2004, while 2007 experienced a minimal sea ice area. Perennial sea ice decreased approximately 30% between 2002 and 2011 with decreases occurring in the Beaufort Sea, Chukchi Sea, East Siberian Sea, Laptev Sea, Kara Sea, and over the vast area from these marginal seas to the Arctic Ocean. Increases in seasonal sea ice occurred in regions where perennial sea ice decreased. The sea ice area has a significant negative relationship with the annual average temperature, and the decrease trend will continue with global warming intensification.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"350 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":"115284196","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}
Shi Xiaotian, Ma Hongchao, Zhou Weiwei, Zhang Liang
{"title":"Semivariogram-based weight estimation for error detection in point clouds from stereo images","authors":"Shi Xiaotian, Ma Hongchao, Zhou Weiwei, Zhang Liang","doi":"10.11834/jrs.20165334","DOIUrl":"https://doi.org/10.11834/jrs.20165334","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"25 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":"115320980","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":"Ocean Color Analysis and an Algorithm for the Retrieval of Multiconstituents Based on Remote Sensing Reflectance","authors":"Tang Junwu","doi":"10.11834/jrs.19970403","DOIUrl":"https://doi.org/10.11834/jrs.19970403","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"36 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":"115431193","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":"Possibilistic c-Means Algorithm Improving the Pixel Unmixing of Remotely Sensed Image","authors":"Hu Dong-min","doi":"10.11834/jrs.20050221","DOIUrl":"https://doi.org/10.11834/jrs.20050221","url":null,"abstract":"The existence of mixed pixels is the main factor influencing the classification accuracy of remotely sensed image. Fuzzy classification is an important method of unmixing the mixed pixels. Its results depend on how accurate the membership value to various types of each pixel after classification corresponds to its actual component. If the clustering number is not equal to the actual type number in the unsupervised classification, or there are some types untrained in the supervised classification, the accuracy of the popular algorithm, namely Fuzzy c-means (FCM) will be degraded. Fortunately, Possibilistic c-means (PCM) is insensitive to it and can work well. This paper proposes the pixel unmixing method of remotely sensed image based on PCM algorithm. The priority of the PCM is illustrated by an actual example in the supervised classification in this paper.","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"82 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":"115432294","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 and trend analysis of remote sensing technology for earthquake emergency investigation","authors":"Qiang Li, Dan Geng, Jingfa Zhang, L. Gong","doi":"10.11834/jrs.20210078","DOIUrl":"https://doi.org/10.11834/jrs.20210078","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"9 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":"115491493","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":"Observing the response of the land surface to climate variability by time series analysis of satellite observations","authors":"M. Massimo, Jia Li","doi":"10.11834/jrs.20166223","DOIUrl":"https://doi.org/10.11834/jrs.20166223","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"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":"115610451","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 OF DISASTER AS A MEASURE FOR EXISTENCE & DEVELOPMENT OF HUMAN BEING","authors":"Yinxiang Chen","doi":"10.11834/jrs.1990034","DOIUrl":"https://doi.org/10.11834/jrs.1990034","url":null,"abstract":"","PeriodicalId":217329,"journal":{"name":"National Remote Sensing Bulletin","volume":"52 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":"115624353","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}