Hanif, M.F. and Ul Mustafa, M.R. and Hashim, A.M. and Yusof, K.W. (2015) Spatio-temporal change analysis of Perak river basin using remote sensing and GIS. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Modernization in industry and urban expansion has led to serious landscape problems and increased pressure on several environmental features i.e. deforestation, climate change etc. Therefore, it is necessary to identify the land use change to minimize the input of the transformation. Remote sensing and GIS considered as one of the potential methods to monitor the land use changes. This study investigate the spatio-temporal changes within the Perak river basin from 2001-2010. Landsat ETM images were utilized for the quantification of land use changes. The data were obtained from the United States Geological Survey (USGS) Department's website. Maximum likelihood supervised classification was applied for the classification of images. Change detection was being measured by using post-classification methods. High resolution imagery were being utilized for training as well as testing purposes to assess the accuracy of the land use classes. Broad classification (level 1) reveal four major land cover categories in the state as i) forest, ii) water bodies, iii) agricultural lands and light forest, and iv) urban and barren lands. The results showed significant decrease in the areas of agricultural lands and thick forest whereas the urban land use has shown swift increase. The study provides a baseline information about the trend of land use changes in Perak Malaysia to the land use managers for the development of reliable land use policies. © 2015 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Impact Factor: | cited By 4 |
Uncontrolled Keywords: | Agriculture; Climate change; Deforestation; Forestry; Geographic information systems; Image classification; Maximum likelihood; Remote sensing; Rivers; Signal detection; Space optics; Watersheds, Change detection; Environmental features; High resolution imagery; Maximum likelihood supervised classifications; Remote sensing and GIS; River basins; Spatio-temporal changes; United states geological surveys, Land use |
Depositing User: | Ms Sharifah Fahimah Saiyed Yeop |
Date Deposited: | 30 Aug 2021 08:54 |
Last Modified: | 30 Aug 2021 08:54 |
URI: | http://scholars.utp.edu.my/id/eprint/26208 |