A5103173852- Remote Sensing and Land Use
- Remote Sensing in Agriculture
- Species Distribution and Climate Change
- Remote-Sensing Image Classification
- Environmental Changes in China
- Land Use and Ecosystem Services
China Agricultural University
2021-2024
Ministry of Agriculture and Rural Affairs
2024
High-quality training samples are essential for accurate land cover classification. Due to the difficulties in collecting a large number of samples, it is great significance collect high-quality sample dataset with limited size but effective distribution. In this paper, we proposed an object-oriented sampling approach by segmenting image blocks expanded from systematically distributed seeds (object-oriented approach) and carried out rigorous comparison seven strategies, including random...
Accurate information on the spatial and temporal distribution of abandoned cropland (AC) is crucial for protecting arable land, maintaining regional food security ecological stability. Nevertheless, unavailability dedicated monitoring AC, along with extended time frame required remote sensing surveillance intricate transformation land cover types following abandonment, poses considerable challenges in producing accurate AC maps scientific purposes. To address these challenges, a new...