本文選題：Landsat影像　切入點：時序數(shù)據(jù)　出處：《地球信息科學學報》2017年08期 　論文類型：期刊論文

【摘要】：時序變化檢測已成為當前Landsat數(shù)據(jù)主流的變化檢測方法。本文從檢測算法對比、時序數(shù)據(jù)構(gòu)建和精度評價等方面對Landsat時序變化檢測進行回顧和評述,進而提出Landsat時序變化檢測當前所存在的問題,及其所面臨的挑戰(zhàn)。Landsat時序變化檢測算法可大致歸納為軌跡擬合法、光譜-時間軌跡法、基于模型的方法3大類,這些算法大多基于森林擾動提出;變化檢測常用指標有波段型、植被指數(shù)型、線性變換型、組合型4大類,每類指標的優(yōu)勢不同,可綜合多類指標以更全面地檢測不同擾動類型。盡管Landsat時序變化檢測已取得長足發(fā)展,但仍然面臨諸多挑戰(zhàn),其中最大挑戰(zhàn)是缺少一致性的參考數(shù)據(jù)集進行變化檢測精度評價。
[Abstract]:Time series change detection has become the mainstream change detection method in Landsat data. This paper reviews and comments on Landsat timing change detection from the aspects of detection algorithm comparison, timing data construction and accuracy evaluation, etc. Furthermore, the paper puts forward the existing problems of Landsat time series change detection and its challenges. Landsat time series change detection algorithms can be roughly classified into three categories: trajectory fitting method, spectrum time track method, model-based method, etc. Most of these algorithms are based on forest disturbance. The commonly used indicators for change detection are band type, vegetation index type, linear transformation type, combined type, and the advantages of each type are different. Although Landsat time series change detection has made great progress, it still faces many challenges, among which the biggest challenge is the lack of consistent reference data set to evaluate the accuracy of change detection.
【作者單位】： 云南大學國際河流與生態(tài)安全研究院;云南省國際河流與跨境生態(tài)安全重點實驗室;
【基金】：國家自然科學基金項目(41461017) 國家重點研發(fā)計劃課題(2016YFA0601601) 云南省中青年學術(shù)技術(shù)帶頭人后備人才培育計劃(2014HB005) 云南大學青年英才培育計劃
【分類號】：P237
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本文編號：1650022