Farmland Surface Water Detection Dataset

The current agricultural sector faces many challenges in water monitoring and management, including water pollution and low irrigation efficiency. Traditional methods cannot quickly and accurately identify and assess water conditions. Existing solutions rely heavily on manual inspection and simple remote sensing image analysis, with low efficiency and insufficient accuracy. This dataset aims to provide high-quality data support for the application of AI technology in water extraction and disaster monitoring, addressing the limitations of traditional methods. Data collection is carried out using high-resolution cameras and remote sensing satellites, covering various climates and geographical environments to ensure data diversity and representativeness. To ensure data quality, multiple rounds of annotation, consistency checks, and expert reviews are implemented as quality control measures. Data is stored in JPG format with annotation information in JSON format to facilitate subsequent processing and analysis.