摘要
利用遥感图像监测森林覆盖及其变化是遥感应用的重要领域之一。本研究基于建德市2013和2014年Landsat8 OLI遥感影像数据、森林资源二类调查小班数据及林地落界数据。采用统计分布和Zone模型两种方法提取有林地小班变化信息。评价结果表明:基于统计分布法操作简单但效果不够理想;基于Zone模型法检测结果精度高于基于统计分布法,但存在较多伪变化,正确检测率为80.58%,漏检率为19.42%,错检率为84.89%,是一种较好的提取有林地小班变化信息的方法。
Using remote sensing images to detect forest cover and changes is one of the important contents of remote sensing research for forests.We studied extraction of forest sub-compartment changes information between 2013 and 2014 based on Landsat 8 OLI data and forest sub-compartment data using the statistical distribution and Zone model.The results showed:statistical distribution method was easy to actualize but dissatisfactory;the overall accuracy of the change information extraction of the Zone model was 80.58%,the missed detection rate was 19.42%,and the false detection rate was about 84.89%,the detection accuracy was better than the statistical distribution method and the Zone model was a good method to extract the change information of forest sub-compartment.
作者
龚鑫烨
华一枝
黄星旻
温小荣
林国忠
陶吉兴
徐达
GONG Xinye;HUA Yizhi;HUANG Xingmin;WEN Xiaorong;LIN Guozhong;TAO Jixing;XU Da(Co-Innovation for the Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing 210037, Jiangsu,China;College of Forestry,Nanjing Forestry University,Nanjing 210037,Jiangsu,China;Center for Forest Resource Monitoring of Zhejiang Province,Hangzhou 310020,Zhejiang,China)
出处
《中南林业科技大学学报》
CAS
CSCD
北大核心
2018年第10期34-40,共7页
Journal of Central South University of Forestry & Technology
基金
国家重点研发计划(2016YFC0502704)
江苏省林业三新工程项目(Lysx[2015]19)
南京林业大学科技创新基金项目(CX2011-24)
江苏高校优势学科建设工程资助项目(PAPD)
关键词
小班变化信息
遥感影像
Zone模型
change information of forest sub-compartment
remote sensing images
Zone model
