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The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis\udtool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of\uduncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems\ud(GIS) based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index\udsystem establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of\udcontinuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the\ud“Nature Breaks” method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final\udclassification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper\udindicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment.\udThe work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and\udpromotes the scientific level of the later planning and decision-making

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

THE UNCERTAINTIES ON THE GIS BASED LAND SUITABILITY ASSESSMENT FOR URBAN AND RURAL PLANNING