Assessment of Urban Patterns Using Spatial Metrics and Prediction of Urban Growth A Case Study of Kabul, Afghanistan

Vineet Chaturvedi, Walter Timo de Vries

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


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.

Original languageEnglish
Title of host publicationGeospatial Science for Smart Land Management
Subtitle of host publicationAn Asian Context
PublisherCRC Press
Number of pages17
ISBN (Electronic)9781000996456
ISBN (Print)9781032393896
StatePublished - 1 Jan 2023


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