National Land Cover Mapping by Remote Sensing Under the Control of Interpreted Data
Land cover change is an important part of global change. Aiming to present situation of land cover in China, according to terrestrial ecosystem characteristic and remote sensing mapping, in this paper we put forward a remote sensed land cover classification system. In order to combine the accuracy of interpretation and speediness of self-classification, we integrated remote sensing classification, alternating interpretation and assistant information analysis, under the control of polygons position and borderline which provided by higher accurate land use data, with the data source of MODIS vegetation index products in 250m resolution, to realize national land cover remote sensing mapping in 2005. Using field survey data, the accuracy assessment is also implemented. Results show that: each class of land cover map has an exact precision, and the map can represent the characteristic and distribution trend of land cover in each region on the whole; the polygon patterns matched the image geography characteristics quite well. The overall precision of national land cover map is 91%, and the precision of each class is o-ver 89% .
land coverland useself-classificationremote sensing mappingMODIS
NETL
NSTL
万方数据
维普
