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  • 标题:Integrating MODIS and Landsat Data for Land Cover Classification by Multilevel Decision Rule
  • 本地全文:下载
  • 作者:Xudong Guan ; Chong Huang ; Rui Zhang
  • 期刊名称:Land
  • 印刷版ISSN:2073-445X
  • 出版年度:2021
  • 卷号:10
  • 期号:2
  • 页码:208
  • DOI:10.3390/land10020208
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:In some cloudy and rainy regions, the cloud cover is high in moderate-high resolution remote sensing images collected by satellites with a low revisit cycle, such as Landsat. This presents an obstacle for classifying land cover in cloud-covered parts of the image. A decision fusion scheme is proposed for improving land cover classification accuracy by integrating the complementary information of MODIS (Moderate-resolution Imaging Spectroradiometer) time series data with Landsat moderate-high spatial resolution data. The multilevel decision fusion method includes two processes. First, MODIS and Landsat data are pre-classified by fuzzy classifiers. Second, the pre-classified results are assembled according to their assessed performance. Thus, better pre-classified results are retained and worse pre-classified results are restrained. For the purpose of solving the resolution difference between MODIS and Landsat data, the proposed fusion scheme employs an object-oriented weight assignment method. A decision rule based on a compromise operator is applied to assemble pre-classified results. Three levels of data containing different types of information are combined, namely the MODIS pixel-level and object-level data, and the Landsat pixel-level data. The multilevel decision fusion scheme was tested on a site in northeast Thailand. The fusion results were compared with the single data source classification results, showing that the multilevel decision fusion results had a higher overall accuracy. The overall accuracy is improved by more than 5 percent. The method was also compared to the two-level combination results and a weighted sum decision rule-based approach. A comparison experiment showed that the multilevel decision fusion rule had a higher overall accuracy than the weighted sum decision rule-based approach and the low-level combination approach. A major limitation of the method is that the accuracy of some of the land covers, where areas are small, are not as improved as the overall accuracy.
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