期刊论文

Wang, Guangxing

英文

ISPRS Journal of Photogrammetry and Remote Sensing

0924-2716

2019

152

145-165

10.1016/j.isprsjprs.2019.04.011

The data of this study was obtained from the projects funded by the National Bureau to Combat Desertification, State Forestry Administration of China, the Fellowship from the China Scholarship Council, Projects of Hunan Province Science and Technology Plan (2015RS4048, 2016SK2026), China Postdoctoral Science Foundation project (2014M562147) and Central South University of Forestry and Technology, China.

本校为其他机构

Traditional parametric methods for classification of land use and land cover (LULC) types using remote sensing imagery assume a global distribution model and fail to consider local variation of categorical variables. Differently, non-parametric methods do not make any statistical assumptions but are typically sensitive to the sample sizes of training sample data that usually require a high cost to collect in the field. Geostatistical classifiers, such as indicator kriging and simulation, are local variability-based methods that exhibit great po...