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Characterizing Landscape Spatial Heterogeneity in Multisensor Images with Variogram Models

Characterizing Landscape Spatial Heterogeneity in Multisensor Images with Variogram Models
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摘要 Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index (NDVI) products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l'observation de la Terre (SPOT), Ad- vanced Spacebome Thermal Emission and Reflection Radiometer (ASTER) and Landsat Thematic Mapper (TM) images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands. Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index(NDVI) products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l'observation de la Terre(SPOT), Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER) and Landsat Thematic Mapper(TM) images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor images. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical semivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisensor images with consideration of their nominal spatial resolution, image size and spectral bands.
出处 《Chinese Geographical Science》 SCIE CSCD 2014年第3期317-327,共11页 中国地理科学(英文版)
基金 Under the auspices of National Natural Science Foundation of China(No.41071267,41001254) Natural Science Foundation of Fujian Province(No.2012I0005,2012J01167)
关键词 variogram modeling spatial heterogeneity characteristic scale multisensor image 空间异质性 图像像素 空间变异 多传感器 自然景观 归一化植被指数 空间分辨率 图像尺寸
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