Open AccessComparison of Resampling Methods on Different Remote Sensing Images for Vietnam’s Urban Classification
Author(s) -
Pham Tuan Dung,
Man Duc Chuc,
Nguyen Thi Nhat Thanh,
Bui Quang Hung,
Doan Minh Chung
Publication year - 2018
Publication title -
research on information comunication technology
Language(s) - English
Resource type - Journals
ISSN - 1859-3534
DOI - 10.32913/rd-ict.vol2.no15.663
Subject(s) - resampling , preprocessor , bicubic interpolation , interpolation (computer graphics) , computer science , artificial intelligence , pattern recognition (psychology) , remote sensing , data mining , geography , image (mathematics) , linear interpolation
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, data transformations during resampling have many effects on classification results. In this research, resampling methods were evaluated. The results showed that mean aggregation and bicubic interpolation methods performed better than the rest on a variety of data types. Besides, the highest overall accuracy and the F1 score for urban classification maps were 98.47% and 0.9842, respectively. DOI: 10.32913/rd-ict.vol2.no15.663