Identification of Alpine Cold Vegetables Based on Sentinel-2A NDVI Time Series Data and Random Forest Method
Based on the Normalized Difference Vegetation Index time series data of Sentinel-2A satellite,combined with Random Forest classification method,this study accurately identifies and classifies the alpine cold vegetables planting area.Taking Xiji County as the research area,the Sentinel-2A remote sensing data covering the whole growth period of alpine cold vegetables in 2023 is used to construct NDVI time series data with 10 m high spatial resolution.Combined with field measurement data,Random Forest classification method is used to identify and classify alpine cold vegetables.The results show that the proposed method shows high accuracy and stability in the identification of alpine cold vegetables planting area,the overall accuracy is 93.52%,and the Kappa coefficient is 0.89.
万方数据
维普
