E3S Web Conf.
Volume 252, 20212021 International Conference on Power Grid System and Green Energy (PGSGE 2021)
|Number of page(s)||6|
|Section||Research and Development of Electrical Equipment and Energy Nuclear Power Devices|
|Published online||23 April 2021|
Crop distribution extraction based on Sentinel data
1 Xi’an University of Science and Technology, Xi’an, 710054 China
2 Xi'an Dadi Surveying And Mapping Co., Ltd, Xi’an, 710054 China 1
Remote sensing identification and classification of crops is the use of remote sensing for estimating crop planting area of timely and accurate monitoring of crop growth and plant diseases and insect pests in advance to make the product output to estimate the key and premise of the study using Sentinel-1 and Sentinel-2 satellite, by random forest algorithm, the traditional optical wavelengths and vegetation index The backward scattering field of red edge information and radar information in feature selection and feature classification, including winter wheat summer corn orchard woodland town water and bare land set three controls, such as the first group contains radar time characteristics, the characteristics of the second control group contains red edge long, the third group includes traditional vegetation index for phase characteristics, analyzed the different classification accuracy. The results from the confusion matrix show that the red edge band edge after index and the radar scattering information to join the crop classification accuracy is improved effectively. Sentinel optical and radar satellites with a time resolution of 5–6 days have great potential for crop monitoring research.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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