LAND-COVER DENSITY-BASED APPROACH TO URBAN LAND USE MAPPING USING HIGH-RESOLUTION IMAGERY

Nowadays, remote sensing imagery, especially with its high spatialresolution, has become an indispensable tool to provide timely up-gradation of urban land use andland cover information, which is a prerequisite for proper urban planning and management. Thepossible method described in the present paper to obtain urban land use types is based on theprinciple that land use can be derived from the land cover existing in a neighborhood. Here, movingwindow is used to represent the spatial pattern of land cover within a neighborhood and seven windowsizes (61mx61m, 68mx68m, 75mx75m, 87mx87m, 99mx99m, 110mx110m and 121mxl21m) are applied todetermining the most proper window size. Then, the unsupervised method of ISODATA is employed toclassify the layered land cover density maps obtained by the moving window. The results of accuracyevaluation show that the window size of 99mx99m is proper to infer urban land use categories and theproposed method has produced a land use map with a total accuracy of 85%.

Nowadays, remote sensing imagery, especially with its high spatial resolution, has become an indispensable tool to provide timely up-gradation of urban land use and land cover information, which is a prerequisite for proper urban planning and management. The possible method described in the present paper to obtain urban land use types is based on the principle that land use can be derived from the land cover existing in a neighborhood. Here, moving window is used to represent the spatial pattern of land cover within a neighborhood and seven window sizes (61m×61m, 68m×68m, 75m×75m, 87m×87m, 99m×99m, 110m×110m and 121m×121m) are applied to determining the most proper window size. Then, the unsupervised method of ISODATA is employed to classify the layered land cover density maps obtained by the moving window. The results of accuracy evaluation show that the window size of 99m×99m is proper to infer urban land use categories and the proposed method has produced a land use map with a total accuracy of 85%.