基于GEE的多源遙感影像特征優(yōu)選方法的水稻種植區(qū)信息提取

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中圖分類號(hào)：TP79;S127 文獻(xiàn)標(biāo)識(shí)碼：A 文章編號(hào)：1000-4440（2025）06-1159-10

Abstract：Multi-temporal Sentinel-1/2datademonstratesignificantadvantagesinidentifyingandmonitoringrice cultivation incomplex mountainousandhillyareas，aswellasincloudyandrainyenvironments，which providerich information forriceidentification.However，anexcesivenumberoffeature variablesmayleadtodimensionaldisastersandinformationredundancy.Inthis study，a featureselectionmethod wasemployedtoevaluate therecognitionaccuracyoffive feature combination schemes（spectral features，spectral features + vegetation indices，spectral features + vegetation indices + texture features，spectral features + vegetation indices + texture features + radarinformation，and feature selection） forricecultivationarea，using Sentinel-1/2multi-spectralandmulti-temporaldata.Thespatial mappingacuracyof each schemewas alsoanalyzed.Theresults indicatedthat Scheme five，which incorporatedfeature selection，performed the best in rice identification，with an overall accuracy of 92.60% ，a Kappa coefficient of O.903 O，and an F1 score of 92.40 % ： Comparedwiththericecultivationareadatain2O24fromtheJiangxi Statistical Yearbook，Schemefiveachievedahighaccuracy of 98.73% in estimating the rice area in Jiangxi province，with a significantly lower relative error compared to

Schemeone-Scheme four.Theresults of this studyconfirm that the integrated application ofmulti-source remote sensing data and multi-temporal feature selection methods caneffectively reduce data redundancy and enhance the accuracy and precision of rice area extraction.

Key words：multi-source remote sensing；rice； Jiangxi province；feature selection；random forest method

糧食安全是國(guó)家安全與社會(huì)穩(wěn)定的基石，黨的二十大報(bào)告強(qiáng)調(diào)“全方位夯實(shí)糧食安全根基”的重要性，對(duì)保障糧食安全提出更高的要求[1]。（剩余12846字）