江西科学2025，Vol.43Issue(6)：1048-1055,8.DOI:10.13990/j.issn1001-3679.2025.06.006
基于时序Sentinel-2影像和物候特征的淮河流域中游耕地非粮化监测
Monitoring Non-Grain Conversion of Cropland in the Middle Huai River Basin Using Time-Series Sentinel-2 Imagery and Phenological Features
摘要
Abstract
Food security serves as a fundamental cornerstone of national security.In recent years,the non-grain conversion of cropland has gradually become a key factor threatening food security.This study focused on the middle Huai River Basin and constructed a dynamic monitoring model for non-grain conversion of cropland by integrating Sentinel-2 imagery with the phenological characteristics of major crops,using differences in vegetation indices such as NDVI and LSWI during key phenological stages.Spatial autocorrelation analysis was applied to reveal the spatial distribution of non-grain conversion in the middle Huai River Basin in 2023.The results indicated that the non-grain conversion of cropland in the middle reaches of the Huai River Basin generally exhibited a distinct spatial pattern,with higher levels in the northeast and lower levels in the southwest.Global spatial autocorrelation re-vealed significant clustering of non-grain conversion,while local spatial autocorrelation fur-ther identified three clustering patterns:"high-high""low-low"and"high-low,"corre-sponding to economic crop-dominated areas,major grain-producing areas,and transition-al zones.Topographic conditions,economic benefits,and regional disparities in policy im-plementation were identified as the core factors driving the spatial pattern of non-grain con-version.The study confirmed the high accuracy and practicality of remote sensing technology in the dynamic monitoring of non-grain conversion,while also providing methodological and theoretical support for agricultural authorities to dynamically manage cropland use con-version.关键词
耕地非粮化/淮河流域中游/Sentinel-2/物候特征/空间自相关Key words
non-grain conversion of cropland/Huai River basin/Sentinel-2/phenological features/spatial autocorrelation分类
天文与地球科学引用本文复制引用
CHEN Xinjiang,ZHAO Mingsong,SHENG Le,WU Tong,ZHANG Daoyu..基于时序Sentinel-2影像和物候特征的淮河流域中游耕地非粮化监测[J].江西科学,2025,43(6):1048-1055,8.基金项目
安徽省自然科学基金项目(2208085MD88) （2208085MD88）
安徽理工大学人才引进项目(ZY020). （ZY020）
