Spatio-Temporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries
Over the last two decades, many researchers have focused on developing countries' urbanization patterns and processes. In this context, the scarcity of spatial data has been an obstacle to studying urbanization quantitatively, especially in Asian and African cities. The use of remote sensing da...
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Format: | Electronic Book Chapter |
Language: | English |
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Basel, Switzerland
MDPI - Multidisciplinary Digital Publishing Institute
2021
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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072 | 7 | |a GP |2 bicssc | |
072 | 7 | |a RG |2 bicssc | |
100 | 1 | |a Murayama, Yuji |4 edt | |
700 | 1 | |a Simwanda, Matamyo |4 edt | |
700 | 1 | |a Ranagalage, Manjula |4 edt | |
700 | 1 | |a Murayama, Yuji |4 oth | |
700 | 1 | |a Simwanda, Matamyo |4 oth | |
700 | 1 | |a Ranagalage, Manjula |4 oth | |
245 | 1 | 0 | |a Spatio-Temporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries |
260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
300 | |a 1 electronic resource (304 p.) | ||
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506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |a Over the last two decades, many researchers have focused on developing countries' urbanization patterns and processes. In this context, the scarcity of spatial data has been an obstacle to studying urbanization quantitatively, especially in Asian and African cities. The use of remote sensing data and geographical information systems (GIS) techniques can overcome the above limitations. Data on land use and land cover, land surface temperature, population density, and energy consumption can be extracted based on remote sensing at various spatial and temporal resolutions. GIS techniques can be used to analyze urbanization patterns and predict future patterns. Thus, the link between urbanization and sustainable urban development has increasingly become a principal issue in designing and developing sustainable cities at the local, regional, and global levels. This volume shows the spatiotemporal analysis of urbanization using GIS and remote sensing in developing countries, with a special emphasis on future urban sustainability in Asia and Africa. Capturing the spatial-temporal variation of urbanization patterns will help introduce proper sustainable urban planning in developing countries, especially for Asian and African cities. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Research & information: general |2 bicssc | |
650 | 7 | |a Geography |2 bicssc | |
653 | |a LST | ||
653 | |a urban-rural gradient | ||
653 | |a sub-Saharan region | ||
653 | |a Addis Ababa | ||
653 | |a Ethiopia | ||
653 | |a cellular automata | ||
653 | |a spatial layout | ||
653 | |a transportation infrastructure | ||
653 | |a LUCC | ||
653 | |a spatial patterns | ||
653 | |a spatial differences | ||
653 | |a DMSP-OLS | ||
653 | |a China | ||
653 | |a India | ||
653 | |a landscape pattern | ||
653 | |a industrial rural area | ||
653 | |a rural landscape | ||
653 | |a landscape ecology | ||
653 | |a southern Jiangsu | ||
653 | |a land use and cover | ||
653 | |a land surface temperature | ||
653 | |a built-up land | ||
653 | |a agricultural land | ||
653 | |a gradient analysis | ||
653 | |a Nuwara Eliya | ||
653 | |a Sri Lanka | ||
653 | |a urban public space | ||
653 | |a environment | ||
653 | |a check-in data | ||
653 | |a social media platform | ||
653 | |a point of interest | ||
653 | |a urbanization | ||
653 | |a GIS | ||
653 | |a urban development zones | ||
653 | |a urban sustainability | ||
653 | |a regression analysis | ||
653 | |a GWR | ||
653 | |a fragmentation | ||
653 | |a non-agricultural conversion of rural land | ||
653 | |a urban green space | ||
653 | |a RSEI | ||
653 | |a remote sensing | ||
653 | |a ecological status | ||
653 | |a dynamic motoring | ||
653 | |a Pingtan Island | ||
653 | |a urban land expansion | ||
653 | |a spatial pattern | ||
653 | |a driving forces | ||
653 | |a Pearl River Delta | ||
653 | |a urban agglomeration | ||
653 | |a urban heat island | ||
653 | |a impervious surface area | ||
653 | |a biophysical composition index | ||
653 | |a coastal city | ||
653 | |a Xiamen | ||
653 | |a surface urban heat island | ||
653 | |a MODIS | ||
653 | |a land cover | ||
653 | |a habitat quality | ||
653 | |a spatiotemporal analysis | ||
653 | |a Yangtze River Delta Urban Agglomeration | ||
653 | |a urban planning | ||
653 | |a LULC change | ||
653 | |a transition matrix | ||
653 | |a systematic transition | ||
653 | |a Blantyre city | ||
653 | |a life quality index (LQI) | ||
653 | |a Kandy city | ||
653 | |a AHP | ||
653 | |a MCDM | ||
653 | |a COVID-19 pandemic | ||
653 | |a environmental quality | ||
653 | |a PM10 concentration | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/4701 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/77082 |7 0 |z DOAB: description of the publication |