数字农科院2.0

Extraction of Sugarcane Planting Area Based on Similarity of NDVI Time Series

文献类型： 外文期刊

作者： Deng, Shiqin;Gao, Maofang;Ren, Chao;Li, Shilei;Liang, Yongjian

作者机构：

关键词： Vegetation mapping;Time series analysis;Data mining;Satellites;Remote sensing;Image reconstruction;Indexes;Crops;Decision-tree;normalized difference vegetation index;singular value decomposition;sugarcane

期刊名称： IEEE ACCESS

ISSN： 2169-3536

年卷期： 2022 年 10 卷

页码：

收录情况： SCIE（2022版） ; ; EI（2022版）

摘要： Timely and accurate estimation of the sugarcane planting area is of vital importance to the country's agricultural production and sugar development. In remote sensing crop mapping based on spectral similarity, there will be have a phenomenon of foreign matters with the same spectrum by obtaining an accurate crop reference curve for crop identification, limiting mapping accuracy. In this study, we improved the spectral reconstruction method based on singular value decomposition (SR-SVD). A decision tree model was established based on the similarity of the sugarcane Normalized Difference Vegetation Index (NDVI) time series curve and the fluctuation range of NDVI in different growth periods. Using the Sentinel-2 (Level-2A) image data set to extract sugarcane planting area in two regions of Chongzuo City, Guangxi, China, the overall accuracy was higher than 96%, respectively. The results show that through the spectral similarity and the determination of the threshold fluctuation range, not only high-precision mapping of sugarcane can be achieved, but the problem of same spectrum with different objects can also be solved. Therefore, this method can provide accurate information on the sugarcane planting areas and technical support for monitoring the structure of sugarcane planting in the region.

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