Title
Synchronous Response Analysis of Features for Remote Sensing Crop Classification Based on Optical and SAR Time-Series Data.
Abstract
Accurate crop classification is the basis of agricultural research, and remote sensing is the only effective measuring technique to classify crops over large areas. Optical remote sensing is effective in regions with good illumination; however, it usually fails to meet requirements for highly accurate crop classification in cloud-covered areas and rainy regions. Synthetic aperture radar (SAR) can achieve active data acquisition by transmitting signals; thus, it has strong resistance to cloud and rain interference. 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.
Year
DOI
Venue
2019
10.3390/s19194227
SENSORS
Keywords
Field
DocType
optical time-series data,SAR time-series data,RNN,synchronous response relationship,cloudy and rainy region,crop classification
Time series,Response analysis,Synthetic aperture radar,Data acquisition,Remote sensing,Recurrent neural network,Data type,Engineering,Classifier (linguistics),Image resolution
Journal
Volume
Issue
ISSN
19
19
1424-8220
Citations 
PageRank 
References 
1
0.35
0
Authors
12
Name
Order
Citations
PageRank
Yingwei Sun110.35
Jian-Cheng Luo29920.75
Tianjun Wu3265.06
Ya'nan Zhou410.35
Hao Liu591.54
Lijing Gao611.36
Wen Dong731.08
Wei Liu810.69
Yingpin Yang910.69
Xiaodong Hu1010.35
Lingyu Wang1110.35
Zhongfa Zhou1211.02