干旱区地理2024，Vol.47Issue(6)：1004-1014,11.DOI:10.12118/j.issn.1000-6060.2023.382
基于RF分类调优和SNIC聚类的新疆红枣种植区遥感提取
Remote sensing extraction of jujube planting area in Xinjiang based on RF classification optimization and SNIC clustering
摘要
Abstract
This study aims to efficiently extract the distribution information and planting area of jujube crops in Xinjiang,China,providing essential data support for predicting yield and price,consolidating poverty alleviation achievements,and aiding rural revitalization.Utilizing the Google Earth Engine cloud platform,this research ac-cesses Sentinel-1 radar images,Sentinel-2 optical images,and SRTM terrain data covering Xinjiang.From these data,44 features including spectral,textural,and terrain attributes are extracted,followed by a feature selection process.The optimized random forest classifier,after hyperparameter tuning,produces a spatial distribution map of Xinjiang's jujube planting areas with a 10 m resolution for the year 2021.Superpixel clustering method fur-ther processes the major jujube planting areas to determine the exact planting extents.The findings are as follows:(1)Employing a simple non-iterative clustering algorithm for classification and post-processing,the identified ju-jube cultivated area in Xinjiang spans 4253 km2,predominantly located in the southern regions of Aksu,Kashgar,Hotan Prefectures,and Bayingolin Mongol Autonomous Prefecture,as well as Turpan and Hami Cities in the east.(2)The accuracy of feature extraction is significantly enhanced through hyperparameter optimization of the random forest classifier,yielding an average overall classification accuracy of 0.86,a Kappa coefficient of 0.82,a producer accuracy for jujube extraction of 0.87,and a user accuracy of 0.80,as assessed via the confusion matrix.(3)Features from the Sentinel-1 polarization band are crucial for jujube information extraction,supplemented ef-fectively by spectral and textural features.Leveraging multisource remote sensing data,this method facilitates rapid acquisition of distribution and area data for jujube planting in Xinjiang,markedly benefiting agricultural modernization,resource conservation,and regional economic development.关键词
Google Earth Engine/Sentinel-1/2/红枣/特征优选/随机森林/超像素聚类Key words
Google Earth Engine/Sentinel-1/2/jujube/feature optimization/random forest/super-pixel clus-tering引用本文复制引用
赵国兵,郑江华,王蕾,高健,罗磊,尼格拉·吐尔逊,韩万强,关靖云..基于RF分类调优和SNIC聚类的新疆红枣种植区遥感提取[J].干旱区地理,2024,47(6):1004-1014,11.基金项目
基于"空天地"多源遥感监测技术的林果资源数据体系建设(20222101536) （20222101536）
2023年中央财政林草科技推广示范项目—新疆和田地区林果资源监测技术典型示范与推广(新[2024]TG15)资助 （新[2024]TG15）
