2018
DOI: 10.3390/land7010037
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Quantifying the Spatiotemporal Pattern of Urban Expansion and Hazard and Risk Area Identification in the Kaski District of Nepal

Abstract: The present study utilized time-series Landsat images to explore the spatiotemporal dynamics of urbanization and land use/land-cover (LULC) change in the Kaski District of Nepal from 1988 to 2016. For the specific overtime analysis of change, the LULC transition was clustered into six time periods:

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Cited by 49 publications
(44 citation statements)
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References 61 publications
(106 reference statements)
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“…On-ground field assessment to monitor and model LULC change in large areas is often not practical, whereas the use of remote sensing and GIS tools can be quite effective [40,41]. Spatio-temporal observations using remote sensing and GIS techniques [42] allow researchers to obtain time-sensitive data to analyze LULC change in urbanizing contexts [43] and project future land-use change [44,45].…”
Section: Methodsmentioning
confidence: 99%
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“…On-ground field assessment to monitor and model LULC change in large areas is often not practical, whereas the use of remote sensing and GIS tools can be quite effective [40,41]. Spatio-temporal observations using remote sensing and GIS techniques [42] allow researchers to obtain time-sensitive data to analyze LULC change in urbanizing contexts [43] and project future land-use change [44,45].…”
Section: Methodsmentioning
confidence: 99%
“…All Landsat scenes were obtained from the United States Geological Survey (USGS) website (https://earthexplorer.usgs.gov) ( Table 1). Landsat SR data underwent post-production processing entailing geometric rectification, atmospheric correction and other processing (for more details, http://landsat.usgs.gov/CDR_LSR.php), rendering data suitable for scientific analysis [29,40,46,47] The SR data product includes quality assessment (QA) bands used here to identify and omit pixels with snow, clouds and cloud shadows. Geometric accuracy was verified for all satellite images, which were projected to the UTM projection (datum WGS 1984).…”
Section: Data Processing and Analysismentioning
confidence: 99%
“…They are effectively used for the LULC analyses [4,[30][31][32][33][34], and flood area mapping. The Birendranagar city spans Nepal's sub-Himalayan and lesser-Himalayan zones, which are characterized by a warm-moist temperate, hot-dry sub-tropical, warm-dry sub-tropical, and cool-moist temperate climates, with annual temperatures ranging from 10 • C to 30 • C [22].…”
Section: Extraction Of Lulc Changementioning
confidence: 99%
“…Floods are the most common and devastating natural hazards [6] on a global scale and have been increasingly frequent and devastating since the mid-20th century [4]. Of all flood events recorded between 1950 and 2011, most have occurred during recent decades.…”
Section: Introductionmentioning
confidence: 99%
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