Obtaining farmland information from high resolution remote sensing satellite images

This article proposes a method for obtaining farmland information in high-resolution satellite images. Firstly, divide the pixels of satellite images into a set of soft object regions and correspond them to a class. Secondly, the representation of each object region is estimated by aggregating the classes of pixels in the object region. Then, design the Hamacher operator decision method to make decisions on the neutral fuzzy part. Finally, calculate the relationship weights and weighted aggregation between the target regions, with the highest aggregation being the category of the pixel region. The experimental results show that the proposed method can effectively obtain cultivated land information from high-resolution satellite images. Meanwhile, compared with existing mature methods, the scoring values of our method have significantly improved.