自然资源遥感2025，Vol.37Issue(2)：39-48,10.DOI:10.6046/zrzyyg.2023350
多云多雨区耕地撂荒多源遥感协同监测
Collaborative monitoring of abandoned arable land in cloudy and rainy areas based on multisource remote sensing data
摘要
Abstract
In cloudy and rainy areas,the humid and hot climate and cloud contamination during the rainy season often cause the loss of optical data.Hence,optical data alone fail to enable the accurate monitoring of abandoned land.This study proposed a method for monitoring abandoned land in cloudy and rainy areas based on multisource remote sensing data.By integrating optical and synthetic aperture Radar(SAR)remote sensing data,this study extracted the multitemporal optical and SAR-derived features of vegetation and assessed their importance using the GINI index.Employing the random forest classifier,this study mapped the spatial distribution of abandoned land in Jiexi County in 2021.The results show that the proposed method achieved a relatively high accuracy in identifying abandoned land in cloudy and rainy areas,yielding an overall accuracy of 87.0％.This value represents an improvement of 6.7 and 13.8 percentage points,respectively,compared to the results derived solely from optical and SAR remote sensing features.The analysis reveals that the normalized difference vegetation index(NDVI),soil-adjusted vegetation index(SAVI),polarization entropy,normalized difference water index(NDWI),and anti-entropy are crucial for identifying abandoned land.Additionally,key months for distinguishing abandoned from non-abandoned land include February,April,June,August,and December.This study establishes a monitoring model for abandoned land based on multisource features and multitemporal phases,providing technical support for monitoring abandoned land in cloudy and rainy areas.关键词
撂荒地/多源遥感/多云多雨区/耕地/时序特征Key words
abandoned land/multisource remote sensing/cloudy and rainy areas/arable land/temporal features分类
计算机与自动化引用本文复制引用
肖文菊,杨颖频,吴志峰..多云多雨区耕地撂荒多源遥感协同监测[J].自然资源遥感,2025,37(2):39-48,10.基金项目
广州大学研究生创新能力培养资助计划"多源遥感协同的撂荒地监测研究"(编号:2022GDJC-M14)、国家自然科学基金项目"华南地区甘蔗种植分布早期遥感精准监测研究"(编号:42201413)和国家自然科学基金-广东联合基金重点项目"粤港澳大湾区湿地资源遥感监测及其生态功能评估研究"(编号:U1901219)共同资助. （编号:2022GDJC-M14）
