Scholarlink

<p>Urban growth monitoring and assessment are crucial for sustainable long-term planning and the efficient utilization of natural resources. Unplanned urbanisation poses risks such as pollution and environmental disruption, emphasizing the need for proactive management. Changes in Land Use and Land Cover (LULC) with time indicate ongoing urbanisation trends. This study aims to predict and simulate urban growth in the Asan watershed, Uttarakhand, India, through 2040 using the SLEUTH model. The SLEUTH model (Slope, Land use, Exclusion, Urban, Transportation, Hillshade) grounded in Cellular Automata (CA) principles is applied to analyse and project LULC changes from 2016 to 2040, assessing their impacts on the surrounding areas. The research utilizes primary datasets including the Digital Elevation Model (DEM) and LULC maps, to forecast future urban expansion. Recent methodologies prioritize the detection of LULC changes through multispectral satellite images, emphasizing factors like radiometric efficiency, spatial uniformity, and climatic conditions. The predicted urban growth output revealed that the projected increase of urban area by 2040 will be 67.73&#xa0;km<sup>2</sup> from 36.5&#xa0;km<sup>2</sup> in 2016 with an increment of 31.23&#xa0;km<sup>2</sup>. Additionally, by 2040, urban settlement is expected to occupy around 9.5% of the total watershed area, an increase of 4.3% from the urban area observed in 2016. The study aims to guide infrastructure planning and promote sustainable development practices by comprehending urban dynamics, growth patterns, and resource management.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Predicting and simulating urban expansion patterns in the Asan watershed, Uttarakhand, India using the SLEUTH model for sustainable land management

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月14日

查看全文
  • Ankita Sharma,
  • Himani Bisht,
  • Bhaskar R. Nikam,
  • Dhirendra Singh Bagri

摘要

Urban growth monitoring and assessment are crucial for sustainable long-term planning and the efficient utilization of natural resources. Unplanned urbanisation poses risks such as pollution and environmental disruption, emphasizing the need for proactive management. Changes in Land Use and Land Cover (LULC) with time indicate ongoing urbanisation trends. This study aims to predict and simulate urban growth in the Asan watershed, Uttarakhand, India, through 2040 using the SLEUTH model. The SLEUTH model (Slope, Land use, Exclusion, Urban, Transportation, Hillshade) grounded in Cellular Automata (CA) principles is applied to analyse and project LULC changes from 2016 to 2040, assessing their impacts on the surrounding areas. The research utilizes primary datasets including the Digital Elevation Model (DEM) and LULC maps, to forecast future urban expansion. Recent methodologies prioritize the detection of LULC changes through multispectral satellite images, emphasizing factors like radiometric efficiency, spatial uniformity, and climatic conditions. The predicted urban growth output revealed that the projected increase of urban area by 2040 will be 67.73 km2 from 36.5 km2 in 2016 with an increment of 31.23 km2. Additionally, by 2040, urban settlement is expected to occupy around 9.5% of the total watershed area, an increase of 4.3% from the urban area observed in 2016. The study aims to guide infrastructure planning and promote sustainable development practices by comprehending urban dynamics, growth patterns, and resource management.