基于遥感地理特征曲线的主要农作物种植面积大尺度提取

doi:10.12190/j.issn.2096-1197.2021.01.18

Abstract

Abstract: 【Objective】 To study the method for extracting the growing area of main crops in Hulun Buir City and Hinggan League in Inner Mongolia by using remote sensing geographic feature curve data.【Methods】 NDVI calculated by using MOD09Q1 as the dataset,46^th,2018;reconstructed time series dataset by using the method of NRF filter and integrate feature curve data sets by adding NDVI minimum in May,DEM data,the slope data and LSWI maximum in May. The CART decision tree classification method was used to extract the growing area of 5 main crops,and the ground quadrat data was used to verify the accuracy.【Results】 The standard feature curve of wheat,oilseed rape,corn,soybean,and rice was built,and the crop information extraction models were constructed for the different areas;the relative accuracy of ground quadrat data verification reached more than 77%.【Conclusion】 Considering the remote sensing geographic feature curves,it was feasible to quickly extract the area of main crops on a large scale by using the CART decision tree classification method.

Key words: The remote sensing geographic feature curves, Large scale, Crop, Area extraction

CLC Number:

TP79

Wulantuya, YU Lifeng, BAO Junwei, XU Hongtao, Wuyundeji, REN Tingting, ZHAO Jiale, DUN Huixia, YU Weizhuo. Large scale extraction of main crops growing area based on remote sensing geographic feature curve[J].Journal of Northern Agriculture, 2021, 49(1): 127-134.

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URL: https://journal30.magtechjournal.com/bfnyxb/EN/10.12190/j.issn.2096-1197.2021.01.18

https://journal30.magtechjournal.com/bfnyxb/EN/Y2021/V49/I1/127

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Large scale extraction of main crops growing area based on remote sensing geographic feature curve

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