Film Mulching Mapping Based on Very High Resolution Satellite Imagery

Abstract

Plastic mulch has been widely used in agricultural cultivation for its significantly increasement toward crop yield since last century, and has recently draw lots of attention from the government side, due to the environmental concerns caused by the agricultural plastic mulch. In this study, a few-shot learning based deep learning model is designed for film mulching mapping using very high resolution satellite imagery. Firstly, the image restoration model is pre-trained by massive unlabeled very resolution satellite imagery samples. Then, the film mulching mapping model is set by the pre-training model weights and trained by few labeled film mulching imagery samples. Results show the proposed method could achieve well film mulching mapping performance, and the F1-score reaches 0.9, which is useful in the agricultural irrigation management and yield prediction.