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  • Variogram Analysis for Assessing Landscape Spatial Heterogeneity in NDVI: an Example Applied to Agriculture in the Jiansanjiang Reclamation area, Northeast China

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    Author(s)
    Wen, Z
    Wu, S
    Liu, F
    Zhang, S
    Dale, P
    Griffith University Author(s)
    Dale, Patricia E.
    Year published
    2013
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    Abstract
    It is necessary to characterize and monitor the spatial heterogeneity of agricultural landscapes, to assist the spatial understanding of some related agricultural processes and to predict food production patterns. In the study, variogram models fitted to empirical variograms are proposed to retrieve spatial heterogeneity characteristics, and they are applied to NDVI data generated from Landsat TM imagery at a 30 m pixel scale. Four representative study sites with distinct landscape patterns, located in the Honghe farm of Jiansanjiang Reclamation Area, Northeast China, were selected for spatial heterogeneity testing and ...
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    It is necessary to characterize and monitor the spatial heterogeneity of agricultural landscapes, to assist the spatial understanding of some related agricultural processes and to predict food production patterns. In the study, variogram models fitted to empirical variograms are proposed to retrieve spatial heterogeneity characteristics, and they are applied to NDVI data generated from Landsat TM imagery at a 30 m pixel scale. Four representative study sites with distinct landscape patterns, located in the Honghe farm of Jiansanjiang Reclamation Area, Northeast China, were selected for spatial heterogeneity testing and analyzing. The results provided quantitative agricultural landscape knowledge: (1) the agricultural landscape heterogeneity at different directions within the study area could be effectively quantified with the variogram model and then interpreted; (2) the spatial heterogeneity of the dry land matrix was normally larger than that of the paddy field matrix; and (3) the agricultural spatial heterogeneity was affected by two factors: the land use type and the distribution pattern of land use types. As remote sensing techniques can now provide various types of surface monitoring data, we argue that quantitative variogram analysis of the data for spatial heterogeneity can help identify explain related ecological phenomena. It could also be used to improve quantitative agricultural remote sensing monitoring in a spatial heterogeneity area as well.
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    Journal Title
    Advances in Intelligent Systems Research
    Volume
    2013
    DOI
    https://doi.org/10.2991/rsete.2013.122
    Copyright Statement
    © The Author(s) 2013. This is an Open Access article distributed under the terms of the Creative Commons Attribution 3.0 Unported (CC BY 3.0) License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
    Subject
    Other environmental sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/56928
    Collection
    • Journal articles

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