{"title":"Detect quasi-circular vegetation community patches using images of different spatial resolutions","authors":"Yuanyuan Li, Qingsheng Liu, Gaohuan Liu, Chong Huang","doi":"10.1109/CISP.2013.6745279","DOIUrl":null,"url":null,"abstract":"Recently some types of quasi-circular patchy vegetations have been found and proved by the high spatial resolution satellite remote sensing images and field investigations in the Yellow River Delta. In order to promote the monitoring of vegetation community patch extension and quantify the mechanism of vegetation community patch succession, there is a clear need for accurately and economically detecting the vegetation community patches. The main objective of this paper is to detect the quasi-circular vegetation community patches from the different spatial resolution images of the first civilian high resolution optical stereo mapping satellite of China (ZY-3). The results show that the front-facing, rear-facing, ground-facing panchromatic and multispectral images are effective and sufficient to detect the quasi-circular vegetation patches based on Circular Hough Transform (CHT), and the higher spatial resolution image had potential to provide the higher detection accuracy for the quasi-circular vegetation patches.","PeriodicalId":442320,"journal":{"name":"2013 6th International Congress on Image and Signal Processing (CISP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 6th International Congress on Image and Signal Processing (CISP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2013.6745279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Recently some types of quasi-circular patchy vegetations have been found and proved by the high spatial resolution satellite remote sensing images and field investigations in the Yellow River Delta. In order to promote the monitoring of vegetation community patch extension and quantify the mechanism of vegetation community patch succession, there is a clear need for accurately and economically detecting the vegetation community patches. The main objective of this paper is to detect the quasi-circular vegetation community patches from the different spatial resolution images of the first civilian high resolution optical stereo mapping satellite of China (ZY-3). The results show that the front-facing, rear-facing, ground-facing panchromatic and multispectral images are effective and sufficient to detect the quasi-circular vegetation patches based on Circular Hough Transform (CHT), and the higher spatial resolution image had potential to provide the higher detection accuracy for the quasi-circular vegetation patches.