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Spatio-temporal reflectance fusion via unmixing: accounting for both phenological and land-cover changes

机译:通过分解实现时空反射融合:解释物候变化和土地覆盖变化

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摘要

Owing to technical limitations the acquisition of fine spatial resolution images (e.g. Landsat data) with frequent (e.g. daily) coverage remains a challenge. One approach is to generate frequent Landsat surface reflectances through blending with coarse spatial resolution images (e.g. Moderate Resolution Imaging Spectroradiometer, MODIS). Existing implementations for data blending, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced STARFM (ESTARFM), have their shortcomings, particularly in predicting the surface reflectance characterized by land-cover-type changes. This article proposes a novel blending model, namely the Unmixing-based Spatio-Temporal Reflectance Fusion Model (U-STFM), to estimate the reflectance change trend without reference to the change type, i.e. phenological change (e.g. seasonal change in vegetation) or land-cover change (e.g. conversion of a vegetated area to a built-up area). It is based on homogeneous change regions (HCRs) that are delineated by segmenting the Landsat reflectance difference images. The proposed model was tested on both simulated and actual data sets featuring phenological and land-cover changes. It proved more capable of capturing both types of change compared to STARFM and ESTARFM. The improvement was particularly observed on those areas characterized by land-cover-type changes. This improved fusion algorithm will thereby open new avenues for the application of spatio-temporal reflectance fusion.
机译:由于技术上的限制,获取具有频繁(例如每天)覆盖的精细空间分辨率图像(例如Landsat数据)仍然是一个挑战。一种方法是通过与粗糙的空间分辨率图像(例如中分辨率成像光谱仪,MODIS)混合来产生频繁的Landsat表面反射率。现有的数据混合实现,例如时空自适应反射融合模型(STARFM)和增强型STARFM(ESTARFM),都有其缺点,特别是在预测以土地覆盖类型变化为特征的表面反射率方面。本文提出了一种新颖的混合模型,即基于非混合的时空反射率融合模型(U-STFM),以在不参考变化类型(即物候变化(例如植被的季节变化)或土地)的情况下估计反射率变化趋势。 -覆盖变化(例如将植被区域转换为建筑区域)。它基于均化变化区域(HCR),该区域通过分割Landsat反射率差异图像来描绘。在具有物候和土地覆盖变化特征的模拟和实际数据集上测试了该模型。与STARFM和ESTARFM相比,事实证明,它更能捕获两种类型的变化。特别是在那些以土地覆盖类型变化为特征的地区,情况有所改善。这种改进的融合算法将因此为时空反射融合的应用开辟新的途径。

著录项

  • 来源
    《International journal of remote sensing》 |2014年第16期|6213-6233|共21页
  • 作者

    Bo Huang; Hankui Zhang;

  • 作者单位

    Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong,Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, NT, Hong Kong;

    Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, NT, Hong Kong;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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