Accuracy of Land Use and Land Cover Mapping Methods

In this chapter, we examined four land use and land cover mapping approaches, i.e., unsupervised, supervised, fuzzy supervised and GIS post-processing. Advanced Land Observing Satellite image and fieldwork data were used to predict urban land use and land cover of Tsukuba city in Japan. Geographic reference data were created applying random stratified sampling method for assessing accuracy of each map produced from the approaches. The accuracies of the maps measured using error matrices and Kappa indices. Among the approaches tested, the GIS post-processing approach improved the mapping results, showing the highest overall accuracy of 89.33%. The fuzzy supervised approach yielded a better accuracy (87.67%) than the supervised and unsupervised approaches. This chapter presents the strengths of the mapping approaches and the potentials of the sensor for mapping of urban areas, which may help urban planners to monitor and interpret complex and dynamic urban system.

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