%A Tuan Dung Pham
%A Duc Chuc Man
%A Thi Nhat Thanh Nguyen
%A Quang Hung Bui
%A Minh Chung Doan
%J Journal of Research, Development, and Application on Information and Communication Theory
%T Comparison of resampling methods on different remote sensing images for Vietnam's urban classification
%X Remotely-sensed data for urban classification is very diverse in data type, acquisition time and spatial resolution. Therefore, preprocessing is needed for input data, in which the spatial resolution must be changed by different resampling methods. However, during resampling progress, data transformations have many effects on classification results. In this research, resampling methods are evaluated; as a result, mean aggregation and bicubic interpolation methods had better results for a variety of data types. Besides, the highest overall accuracy and F1 score for urban classification maps are 98.47% and 0.9842, respectively.
%D 2018
%L SisLab3130