Grassland Type Remote Sensing Classification Dataset

The current agricultural industry faces dual challenges of precision agriculture and environmental protection, particularly in the automatic classification and monitoring of grassland types. Existing remote sensing technologies often suffer from inconsistent data and insufficient classification accuracy, making them difficult to meet practical application needs. This dataset aims to provide high-quality grassland type image data to address the issues of data scarcity and inaccurate labeling in remote sensing classification. Data collection uses high-resolution remote sensing images, obtained via drones and satellites, ensuring data diversity and authenticity. We have implemented multiple rounds of labeling, expert review, and other quality control measures to ensure high labeling accuracy and consistency. The data is stored in JPG format and organized by category folders for ease of subsequent use and management.