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Characterizing landscape spatial heterogeneity in multisensor images with variogram models |
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| Authors: | Bingwen Qiu Canying Zeng Chongcheng Cheng Zhenghong Tang Jianyang Gao Yinpo Sui |
| Institution: | 1. Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Fuzhou University, Fuzhou, 350002, China 2. Community and Regional Planning Program, University of Nebraska-Lincoln, Lincoln, 68588, USA 3. Geological Remote Sensing Centre of Fujian Province, Fuzhou, 350011, China |
| Abstract: | 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. |
| Keywords: | variogram modeling spatial heterogeneity characteristic scale multisensor image |
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