Analysis of Dynamic Changes of Winter Wheat in Xinye County, Henan Province Based on SVM Method
Keywords:
Support Vector Machine (SVM), Winter wheat, Spatial and temporal distribution, Dynamic changes, Agricultural remote sensingAbstract
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.
