Scrutinizing Urbanization in Kathmandu Using Google Earth Engine Together with Proximity-Based Scenario Modelling

Anisha Aryal (), Kishor Prasad Bhatta, Sanot Adhikari and Himlal Baral
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Anisha Aryal: Youth Alliance for Environment, Baluwatar, Kathmandu 44600, Nepal
Kishor Prasad Bhatta: Research and Development Centre, Durbar Marg, Kathmandu 44600, Nepal
Sanot Adhikari: Youth Alliance for Environment, Baluwatar, Kathmandu 44600, Nepal
Himlal Baral: Center for International Forestry Research (CIFOR), Bogor 16115, Indonesia

Land, 2022, vol. 12, issue 1, 1-16

Abstract: ‘Urbanization’ refers to the expansion of built-up areas caused by several factors. This study focuses on the urbanization process in Kathmandu, the capital of Nepal. Supervised classification was conducted in Google Earth Engine by using Landsat data for years 2001, 2011 and 2021. The random forest classifier with 250 trees was used for classification to generate land-cover map. A land-cover map of 2021 was used as base map in the InVEST tool for scenario modelling. An accuracy assessment with 20% of sample points was conducted with different metrics, such as overall accuracy, kappa coefficient, producer accuracy, and consumer accuracy. The results show an increment of built-up areas by around 67 km 2 over 20 years in a centrifugal pattern from the core district, converting agricultural and forest land. ‘Forest’ is still dominant land-use class, with an area of 177.97 km 2 . Agricultural land was highly converted to urban area. The overall accuracy of this classification process ranged 0.96–1.00 for different years. The scenario modelling further elaborated an amiability of drastic shift in land-use classes to ‘built-up’, especially forest and agriculture, by around 33 km 2 and 66 km 2 , respectively. This study recommends the consideration of ecological approaches during the planning process.

Keywords: land use; built-up areas; urbanization; classification; Landsat; transition (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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