Analysis of Dynamic Changes of Winter Wheat in Xinye County, Henan Province Based on SVM Method

Yan Si, Bing-Yuh Lu, Yun-Shang Wang, Ruei-Yuan Wang
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Abstract

The guarantee of grain yield is an important issue for national security. Wheat is one of the main grain crops in China, and monitoring the spatio-temporal changes in its planting area and yield has important implications for decision-making support. With the development of remote sensing technology, estimating the long-term changes in the area of wheat planting has become a vital agricultural monitoring method. This article uses GF-1 satellite WFV sensor data to estimate the wheat planting areas in Xinye County, Henan Province in 2017, 2020, and 2023, mainly using SVM algorithm for calculation and comparison. After classification, the overall classification accuracy reaches over 95%, and the Kappa coefficient is above 0.95. The results show that the winter wheat planting area in Xinye County has shown an increasing trend over the past six years, from 34296.295 hm2 in 2017 to 56914.662 hm2 in 2023. By analyzing and summarizing the changes in regional crops, it has an important contribution to regional production and agricultural evaluation decision-making.
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基于支持向量机的河南新叶县冬小麦产量动态变化分析
粮食产量保障是关系到国家安全的重大问题。小麦是中国主要粮食作物之一,监测其种植面积和产量的时空变化对决策支持具有重要意义。随着遥感技术的发展,估算小麦种植面积的长期变化已成为一种重要的农业监测手段。本文利用GF-1卫星WFV传感器数据对河南省新叶县2017年、2020年和2023年小麦种植面积进行估算,主要采用SVM算法进行计算和比较。分类后,总体分类准确率达到95%以上,Kappa系数在0.95以上。结果表明:近6年来,新叶县冬小麦种植面积呈增加趋势,从2017年的34296.295 hm2增加到2023年的56914.662 hm2;通过对区域作物变化的分析和总结,对区域生产和农业评价决策有重要贡献。
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