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

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 km2 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 km2. 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 km2 and 66 km2, respectively. This study recommends the consideration of ecological approaches during the planning process.