Sensors, Vol. 19, Pages 4227: Synchronous Response Analysis of Features for Remote Sensing Crop Classification Based on Optical and SAR Time-Series Data

In this study, we designed an improved crop planting structure mapping framework for cloudy and rainy regions by combining optical data and SAR data, and we revealed the synchronous-response relationship of these two data types. First, we extracted geo-parcels from optical images with high spatial resolution. Second, we built a recurrent neural network (RNN)-based classifier suitable for remote sensing images on the geo-parcel scale. Third, we classified crops based on the two datasets and established the network. Fourth, we analyzed the synchronous response relationships of crops based on the results of the two classification schemes. This work is the basis for the application of remote sensing data for the fine mapping and growth monitoring of crop planting structures in cloudy and rainy areas in the future.

Source: Sensors - September 27, 2019 Category: Biotechnology Authors: Yingwei Sun Jiancheng Luo Tianjun Wu Ya ’nan Zhou Hao Liu Lijing Gao Wen Dong Wei Liu Yingpin Yang Xiaodong Hu Lingyu Wang Zhongfa Zhou Tags: Article Source Type: research