高分二號(hào)衛(wèi)星影像在變色松樹(shù)遙感監(jiān)測(cè)中的應(yīng)用

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中圖分類(lèi)號(hào)：S763.18 文獻(xiàn)標(biāo)志碼：A 文章編號(hào)：2096-9902（2025）12-0006-05

Abstract：Pinewiltdisease，causedbypinewoodnematode（Bursaphelenchusxylophilus），isadevastating forestdiseasethat posesseverethreatstoforestecosystemsThisstudyaimstoapplyGF-2sateliteimageryformonitoringdiscoloredpinetrees andevaluateitsefectivenessbyestablishingadeplearning-basedmonitoringsystemtoenhancetimelinessandacuracy. IntegratingGF-2sateliteremotesensingdatawithUAVaerialimagery，monitoringexperimentswereconductedinGuangning County，Guangdong Province.Imageprocessngtechniques，including Gram-Schmidt（GS）fusionandthe GreenNormalized DiferenceVegetation Index（GNDVI），significantlyimprovedthecontrastbetweendiscoloredpinetreesandtheirbackground. Using adeep learning algorithm for discolored pine tree extraction，the method achieved a precision of 94.65% ，recall of 83.30% andF1-score of 88.61% .The results demonstrate that the GF-2-based identification method ofers high accuracy and can provide reliable data support for precise monitoring of pine wilt disease.

Keywords：pine wilt disease;remote sensing;GF-2;image fusion;evaluation

松材線蟲(chóng)病是我國(guó)森林生態(tài)系統(tǒng)面臨的重大生物威脅之一，對(duì)森林資源造成了嚴(yán)重?fù)p害。（剩余6384字）