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Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning

SERASINGHE PATHIRANAGE Inoka Sandamali Lakshmi N. KANTAKUMAR SUNDARAMOORTHY Sivanantharajah

SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. 中国地理科学, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
引用本文: SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. 中国地理科学, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. Chinese Geographical Science, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
Citation: SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. Chinese Geographical Science, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6

Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning

doi: 10.1007/s11769-018-0946-6

Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning

  • 摘要: Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions (GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority (UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.
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Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning

doi: 10.1007/s11769-018-0946-6

摘要: Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions (GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority (UDA) of Sri Lanka. The results show that the UDA's city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.

English Abstract

SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. 中国地理科学, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
引用本文: SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. 中国地理科学, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. Chinese Geographical Science, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
Citation: SERASINGHE PATHIRANAGE Inoka Sandamali, Lakshmi N. KANTAKUMAR, SUNDARAMOORTHY Sivanantharajah. Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning[J]. Chinese Geographical Science, 2018, 28(2): 274-286. doi: 10.1007/s11769-018-0946-6
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