TY - CHAP
T1 - Assessment of Urban Patterns Using Spatial Metrics and Prediction of Urban Growth A Case Study of Kabul, Afghanistan
AU - Chaturvedi, Vineet
AU - de Vries, Walter Timo
N1 - Publisher Copyright:
© 2024 selection and editorial matter Walter Timo de Vries, Iwan Rudiarto, N.M.P. Milinda Piyasena; individual chapters, the contributors.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Studying the evolution of urban patterns in data poor regions is not an easy task, and it can immensely benefit from open access data and GIS technologies. In this chapter, we analyze the composition of urban patterns in Kabul City, Afghanistan, using open access global human settlement surface layer (GHSL) of 4 different time periods from 2001, 2010, 2018, and 2030. The patterns are analyzed on the basis of the spatial arrangement of the built-up surface using the combination of GHSL and spatial metric techniques. The resulting patterns indicate a sprawling city with compact growth in the core city areas and fragmented in the fringes. The study also employs cellular automata model to predict the growth of the city in 2030. The spatial model is developed using MOLUSCE plugin in QGIS with population density, slope, and roads considered as factors of urban growth. In case of Kabul urban sprawl has both negative and positive implications on the city. On the one hand it provides security and generates employments for the ever-growing population, and on the other it is leading to a chaotic sprawl which has led to lack of civic amenities and loss of agricultural land.
AB - Studying the evolution of urban patterns in data poor regions is not an easy task, and it can immensely benefit from open access data and GIS technologies. In this chapter, we analyze the composition of urban patterns in Kabul City, Afghanistan, using open access global human settlement surface layer (GHSL) of 4 different time periods from 2001, 2010, 2018, and 2030. The patterns are analyzed on the basis of the spatial arrangement of the built-up surface using the combination of GHSL and spatial metric techniques. The resulting patterns indicate a sprawling city with compact growth in the core city areas and fragmented in the fringes. The study also employs cellular automata model to predict the growth of the city in 2030. The spatial model is developed using MOLUSCE plugin in QGIS with population density, slope, and roads considered as factors of urban growth. In case of Kabul urban sprawl has both negative and positive implications on the city. On the one hand it provides security and generates employments for the ever-growing population, and on the other it is leading to a chaotic sprawl which has led to lack of civic amenities and loss of agricultural land.
UR - http://www.scopus.com/inward/record.url?scp=85180892397&partnerID=8YFLogxK
U2 - 10.1201/9781003349518-22
DO - 10.1201/9781003349518-22
M3 - Chapter
AN - SCOPUS:85180892397
SN - 9781032393896
SP - 297
EP - 313
BT - Geospatial Science for Smart Land Management
PB - CRC Press
ER -