In this study we tried to explore the potential and the methodology for the cropland identification using high temporal resolution SPOT-. 4 VEGETATION (VGT) ...
The result of this study shows that the methodology used in this study is, in general, feasible for cropland identification in semi-arid area of north China ...
The objective of this study is to explore the potential and the methodology for the cropland change detection with Discrete Fourier Transform (DFT) approach ...
The objective of this study is to explore the potential and the methodology for the cropland change detection with Discrete Fourier Transform (DFT) approach ...
In this study we tried to explore the potential and the methodology for the cropland identification using high temporal resolution SPOT-4 VEGETATION (VGT) ...
Sixteen grassland classes were divided based on the IOCSG in Inner Mongolia ranging from forest and forest steppe to desert and semidesert.
Oct 7, 2022 · This study confirms the feasibility of the deep learning model in the application research of large-scale crop classification and mapping.
Mar 12, 2024 · Using long time series NDVI data, climate data, and statistical data, this study explored the effects of CC and human activities on vegetation ...
Missing: Cropland | Show results with:Cropland
Xiao et al. Characterization of forest types in northeastern China, using multi-temporal SPOT-4 VEGETATION sensor data. Remote Sensing of Environment. (2002).