eprintid: 3130
rev_number: 7
eprint_status: archive
userid: 297
dir: disk0/00/00/31/30
datestamp: 2018-10-29 04:27:00
lastmod: 2018-10-29 04:27:00
status_changed: 2018-10-29 04:27:00
type: article
metadata_visibility: show
creators_name: Pham, Tuan Dung
creators_name: Man, Duc Chuc
creators_name: Nguyen, Thi Nhat Thanh
creators_name: Bui, Quang Hung
creators_name: Doan, Minh Chung
creators_id: chucmd@fimo.edu.vn
creators_id: thanhntn@vnu.edu.vn
creators_id: hungbq@vnu.edu.vn
title: Comparison of resampling methods on different remote sensing images for Vietnam's urban classification
ispublished: inpress
subjects: IT
divisions: FIMO
divisions: fac_fit
abstract: 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.
date: 2018
date_type: published
full_text_status: none
publication: Journal of Research, Development, and Application on Information and Communication Theory
refereed: TRUE
issn: 1859-3534
citation:   Pham, Tuan Dung and Man, Duc Chuc and Nguyen, Thi Nhat Thanh and Bui, Quang Hung and Doan, Minh Chung  (2018) Comparison of resampling methods on different remote sensing images for Vietnam's urban classification.  Journal of Research, Development, and Application on Information and Communication Theory .    ISSN 1859-3534    (In Press)