Mapping Plastic Greenhouses Using Spectral Metrics Derived From GaoFen-2 Satellite Data

Abstract

Plastic greenhouses are an important hallmark of agricultural progress. To meet the growing demand for vegetable and food, the amount of plastic greenhouses has increased significantly over the past few decades. Remote sensing is considered as a promising data source for taking inventory and Monitoring plastic greenhouses for managing modern agriculture. However, a systematic catalog of number and spatial distribution of plastic greenhouses is mostly inexistent. This is primarily due to the complex land surface characteristics and seasonal changes, which make automated classification based on EO data challenging. Current approaches generally suffer from the susceptibility of approaches toward thresholds and changes in the phenological stage. Besides, they often require an extensive training of models, however, often the necessary amount of training data is inexistent. To address These issues, we suggest an adaptable and universal plastic greenhouse mapping method based on very high spatial resolution optical satellite data (GaoFen-2 image) with a three-step procedure. A plastic greenhouse gathering area (100 km2) is selected for the development of the initial method. We receive a very competitive mapping accuracy 97.34% and the likelihood of plastic greenhouses being mapped correctly reaches to 95.20%. Subsequently, we transfer it to a much larger area (2025 km2) featuring a different phenological stage and different surrounding patterns. The stable mapping accuracy proves the validity of our approach.