自然资源遥感2017，Vol.29Issue(3)：196-202,7.DOI:10.6046/gtzyyg.2017.03.29
基于高分一号时间序列数据的沙化土地分类
Sandy lands classification using GF-1 time series NDVI data
摘要
Abstract
In this study, GF-1 16 m multispectral images were used as data source, the spectral characteristics of each type of sandy land and its change characteristics of time series NDVI were analyzed, the sandy lands were classified by the GF-1 image at a single time, and time series NDVI data were compared with each other separately;on such a basis, the classification accuracy was evaluated.The results showed that the accuracy was 73.34% and Kappa coefficient was 0.7 by only using single time original data in growing season;however, the accuracy was increased to 92.04% by joining the time series NDVI data, with Kappa coefficient raised to 0.87;the accuracy was 81.44% and Kappa coefficient was 0.77 by using the time series NDVI data combined with non-growing season data, thus improving the classification accuracy obviously.It is indicated that GF-1 time series NDVI data have a huge application potential in the sandy lands classification.关键词
GF-1影像/时间序列NDVI/沙化土地/应用潜力Key words
GF-1 data/time series NDVI/sandy lands/application potential分类
信息技术与安全科学引用本文复制引用
丁相元,高志海,孙斌,吴俊君,薛传平,王燕..基于高分一号时间序列数据的沙化土地分类[J].自然资源遥感,2017,29(3):196-202,7.基金项目
国家高分辨率对地观测重大专项"高分林业遥感应用示范系统(一期)"(编号: 21-Y30B05-9001-13/15). （一期）
