Accurate land cover information is required for science, monitoring, and reporting. Land
cover changes naturally over time, as well as a result of anthropogenic activities. Monitoring …

Classification is a fundamental process in remote sensing used to relate pixel values to land
cover classes present on the surface. Over large areas land cover classification is …

The 30 m resolution US Department of Agriculture (USDA) crop data layer (CDL) is a widely
used crop type map for agricultural management and assessment, environmental impact …

Fractional vegetation cover (FVC) plays an important role in earth surface process
simulations, climate modeling, and global change studies. Several global FVC products …

Temporal-related features are important for improving land cover classification accuracy
using remote sensing data. This study investigated the efficacy of phenological features …

Impervious surface area (ISA) mapping at the global scale has entered a new era. Currently,
the number of high-resolution global ISA products is gradually increasing; however, a …

Land cover classification of finer resolution remote sensing data is always difficult to acquire
high-frequency time series data which contains temporal features for improving classification …

In remote sensing image classification, active learning aims to obtain an excellent
classification model by selecting informative or representative training samples. However …

Grasslands are the most dominant terrestrial ecosystem in China, but few national grassland
maps have been generated. The grassland resource map produced in the 1980s is widely …

Historical land cover maps are of high importance for scientists and policy makers studying
the dynamic character of land cover change in the Sudano-Sahel, including anthropogenic …