A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Effect of Urban Land Use on Agriculture, Forest, and River Beds: A Case Study of Dehradun City, Uttarakhand, India
Urbanization has led to a tremendous pressure on available land in Dehradun, Uttarakhand, India. Therefore, proper land planning measures are required to mitigate the effect of urbanization on agriculture, forest, and water bodies. This study illustrates the use of remote sensing and GIS to detect the change in urban sprawl of Dehradun region during the period 2013–18 and its effect on agriculture, forest, and water bodies. Landsat 8 imagery has been used in this study. Supervised classification has been adopted in Landsat 8 images of the study area. Four different land cover classes have been considered in classification stage. These are urban, forests, agriculture and vegetation, and seasonal river beds. The accuracy obtained for both the images after classification was above 85% for good change detection results. The change detection technique used is post-classification comparison method which is the matrix union method. The study has shown that the built-up area in Dehradun city has expanded from 75.07 km2 in 2013 to 105.51 km2 in 2018 and 0.26 km2 of forest area, 34.40 km2 of agricultural land, and 2.56 km2 of water beds have been converted into built-up area in the duration of 5 years. The increase in built-up area from 2013 to 2018 is 40.54%.
Effect of Urban Land Use on Agriculture, Forest, and River Beds: A Case Study of Dehradun City, Uttarakhand, India
Urbanization has led to a tremendous pressure on available land in Dehradun, Uttarakhand, India. Therefore, proper land planning measures are required to mitigate the effect of urbanization on agriculture, forest, and water bodies. This study illustrates the use of remote sensing and GIS to detect the change in urban sprawl of Dehradun region during the period 2013–18 and its effect on agriculture, forest, and water bodies. Landsat 8 imagery has been used in this study. Supervised classification has been adopted in Landsat 8 images of the study area. Four different land cover classes have been considered in classification stage. These are urban, forests, agriculture and vegetation, and seasonal river beds. The accuracy obtained for both the images after classification was above 85% for good change detection results. The change detection technique used is post-classification comparison method which is the matrix union method. The study has shown that the built-up area in Dehradun city has expanded from 75.07 km2 in 2013 to 105.51 km2 in 2018 and 0.26 km2 of forest area, 34.40 km2 of agricultural land, and 2.56 km2 of water beds have been converted into built-up area in the duration of 5 years. The increase in built-up area from 2013 to 2018 is 40.54%.
Effect of Urban Land Use on Agriculture, Forest, and River Beds: A Case Study of Dehradun City, Uttarakhand, India
Lecture Notes in Civil Engineering
Gupta, Laxmikant Madanmanohar (editor) / Ray, Maya Rajnarayan (editor) / Labhasetwar, Pawan Kumar (editor) / Sawant, Kunal (author) / Prakash, Rishi (author) / Mishra, Nitin (author)
2020-11-14
10 pages
Article/Chapter (Book)
Electronic Resource
English
Landsat 8 , Change detection , Recoding , Supervised classification Engineering , Transportation Technology and Traffic Engineering , Building Materials , Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution , Sustainable Architecture/Green Buildings , Landscape/Regional and Urban Planning , Water Quality/Water Pollution
An artificial neural network based approach for urban growth zonation in Dehradun city, India
| Online Contents | 2010