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Volume 30 Issue 1

Jan.  2013

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2013 >  30(1): 125-141

Assessing Disagreement and Tolerance of Misclassification of Satellite-derived Land Cover Products Used in WRF Model Applications

  • 1.

    Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, University of Chinese Academy of Sciences, Beijing 100049;Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029


doi: 10.1007/s00376-012-2037-4

  • As more satellite-derived land cover products used in the study of global change, especially climate modeling, assessing their quality has become vitally important. In this study, we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme. We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products, and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model. Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes, while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes. The degree of disagreement varied significantly among seven regions of China. The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly. High accuracy and fuzzy agreement occurred in the following classes: water, grassland, cropland, and barren or sparsely vegetated. Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals. Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling. Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.
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    [3] LI Mingwei, WANG Yuxuan*, and JU Weimin, 2014: Effects of a Remotely Sensed Land Cover Dataset with High Spatial Resolution on the Simulation of Secondary Air Pollutants over China Using the Nested-grid GEOS-Chem Chemical Transport Model, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 179-187.  doi: 10.1007/s00376-013-2290-1
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    • Manuscript History

    Manuscript received: 10 January 2013
    Manuscript revised: 10 January 2013
    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Assessing Disagreement and Tolerance of Misclassification of Satellite-derived Land Cover Products Used in WRF Model Applications

    • 1. Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, University of Chinese Academy of Sciences, Beijing 100049;Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
    • Manuscript received: 2013-01-10
    • Manuscript revised: 2013-01-10

    Abstract: As more satellite-derived land cover products used in the study of global change, especially climate modeling, assessing their quality has become vitally important. In this study, we developed a distance metric based on the parameters used in weather research and forecasting (WRF) to characterize the degree of disagreement among land cover products and to identify the tolerance for misclassification within the International Geosphere Biosphere Programme (IGBP) classification scheme. We determined the spatial degree of disagreement and then created maps of misclassification of Moderate Resolution Imaging Spectoradiometer (MODIS) products, and we calculated overall and class-specific accuracy and fuzzy agreement in a WRF model. Our results show a high level of agreement and high tolerance of misclassification in the WRF model between large-scale homogeneous landscapes, while a low level of agreement and tolerance of misclassification appeared in heterogeneous landscapes. The degree of disagreement varied significantly among seven regions of China. The class-specific accuracy and fuzzy agreement in MODIS Collection 4 and 5 products varied significantly. High accuracy and fuzzy agreement occurred in the following classes: water, grassland, cropland, and barren or sparsely vegetated. Misclassification mainly occurred among specific classes with similar plant functional types and low discriminative spectro-temporal signals. Some classes need to be improved further; the quality of MODIS land cover products across China still does not meet the common requirements of climate modeling. Our findings may have important implications for improving land surface parameterization for simulating climate and for better understanding the influence of the land cover change on climate.

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