S. Arockiaraj, Amit Kumar, Najmul Hoda, A. Jeyaseelan
{"title":"基于高分辨率QuickBird卫星影像的开放混交林树种识别与定量研究","authors":"S. Arockiaraj, Amit Kumar, Najmul Hoda, A. Jeyaseelan","doi":"10.31357/JTFE.V5I2.2658","DOIUrl":null,"url":null,"abstract":"Present study deals with identification and quantification of tree species within an open mixed forest in parts of Ranchi district Jharkhand, India using high resolution QuickBird satellite data using image processing and GIS techniques. A high resolution QuickBird satellite image was used for shadow enhancement and tree crown area extraction. The First Principal Component of QuickBird satellite images was employed to enhance the shadowed area and subsequently shadow and non-shadow area were classified using ISODATA. The satellite image was used for crown area extraction with standard deviation of NDVI value and the crowns were classified into five classes using Maximum Likelihood supervised algorithm. Result shows that barring few limitation, the high resolution QuickBird image provides rapid and accurate results in terms of identification and quantification of tree species in conjugation with field verification and attained 88% of classification accuracy. It reduces the time required for obtaining inventory data in open mixed forest. Results also showed that total 5,522 trees of various species were present in the study area and dominated by Shorea robusta (80.48%) followed by Ziziphus mauritiana (16.26%), unknown tree (1.81%), Ficus religiosa (0.98%) and Mangifera indica (0.47%). The demography patterns of the locals mainly tribal (89.9%) exhibited their direct as well as indirect dependency on mixed forests resources for their subsistence and livelihood. The study necessitate towards the effective implication of policies to raise the standard of living of tribal people in the region.","PeriodicalId":17445,"journal":{"name":"Journal of Tropical Forestry","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Identification and Quantification of Tree Species in Open Mixed Forests using High Resolution QuickBird Satellite Imagery\",\"authors\":\"S. Arockiaraj, Amit Kumar, Najmul Hoda, A. Jeyaseelan\",\"doi\":\"10.31357/JTFE.V5I2.2658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Present study deals with identification and quantification of tree species within an open mixed forest in parts of Ranchi district Jharkhand, India using high resolution QuickBird satellite data using image processing and GIS techniques. A high resolution QuickBird satellite image was used for shadow enhancement and tree crown area extraction. The First Principal Component of QuickBird satellite images was employed to enhance the shadowed area and subsequently shadow and non-shadow area were classified using ISODATA. The satellite image was used for crown area extraction with standard deviation of NDVI value and the crowns were classified into five classes using Maximum Likelihood supervised algorithm. Result shows that barring few limitation, the high resolution QuickBird image provides rapid and accurate results in terms of identification and quantification of tree species in conjugation with field verification and attained 88% of classification accuracy. It reduces the time required for obtaining inventory data in open mixed forest. Results also showed that total 5,522 trees of various species were present in the study area and dominated by Shorea robusta (80.48%) followed by Ziziphus mauritiana (16.26%), unknown tree (1.81%), Ficus religiosa (0.98%) and Mangifera indica (0.47%). The demography patterns of the locals mainly tribal (89.9%) exhibited their direct as well as indirect dependency on mixed forests resources for their subsistence and livelihood. The study necessitate towards the effective implication of policies to raise the standard of living of tribal people in the region.\",\"PeriodicalId\":17445,\"journal\":{\"name\":\"Journal of Tropical Forestry\",\"volume\":\"31 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Tropical Forestry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31357/JTFE.V5I2.2658\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Tropical Forestry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31357/JTFE.V5I2.2658","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification and Quantification of Tree Species in Open Mixed Forests using High Resolution QuickBird Satellite Imagery
Present study deals with identification and quantification of tree species within an open mixed forest in parts of Ranchi district Jharkhand, India using high resolution QuickBird satellite data using image processing and GIS techniques. A high resolution QuickBird satellite image was used for shadow enhancement and tree crown area extraction. The First Principal Component of QuickBird satellite images was employed to enhance the shadowed area and subsequently shadow and non-shadow area were classified using ISODATA. The satellite image was used for crown area extraction with standard deviation of NDVI value and the crowns were classified into five classes using Maximum Likelihood supervised algorithm. Result shows that barring few limitation, the high resolution QuickBird image provides rapid and accurate results in terms of identification and quantification of tree species in conjugation with field verification and attained 88% of classification accuracy. It reduces the time required for obtaining inventory data in open mixed forest. Results also showed that total 5,522 trees of various species were present in the study area and dominated by Shorea robusta (80.48%) followed by Ziziphus mauritiana (16.26%), unknown tree (1.81%), Ficus religiosa (0.98%) and Mangifera indica (0.47%). The demography patterns of the locals mainly tribal (89.9%) exhibited their direct as well as indirect dependency on mixed forests resources for their subsistence and livelihood. The study necessitate towards the effective implication of policies to raise the standard of living of tribal people in the region.