Monitoring the population change and urban growth of four major Pakistan cities through spatial analysis of open source data

TLDR

Urban centers in Pakistan have experienced unplanned growth due to rural unemployment and infrastructure gaps, and open‑source geospatial data are increasingly used to monitor and predict such dynamic changes. The study aims to assess the use of freely available open‑source data for spatial mapping and monitoring of Pakistani cities. Using Google Earth Engine, Landsat imagery, LandScan data, and machine‑learning classification, the authors mapped built‑up areas over four decades to analyze sprawl patterns in four major Pakistani cities. Built‑up area has grown significantly over four decades, strongly correlating with population growth, offering timely, cost‑effective insights for policymakers to promote sustainable urbanization.

Abstract

Cities are complex and dynamic entities in close proximity of people, implying multi temporal observations to analyse and understand the urban context. At present, open-source data and geospatial intelligence are becoming the important means of exploring, monitoring and predicting urban status of area growth and population increase. In last few decades, unemployment and absence of infrastructures in the rural areas promoted the unplanned and haphazard urbanization across the urban centres in Pakistan. This study focuses on exploring the potential of open-source/freely available datasets for city mapping and monitoring spatially. The study gives a spatial perspective of rapidly growing cities of Pakistan using Google Earth Engine to classify Landsat images over last four decades, and discovers sprawl patterns across cities. The study works out that the built-up area is significantly increasing with population growth over four decades and there is a strong positive correlation between population growth and built-up expansion. Using Open-Source Data (Landsat images and LandScan data), this study has offered a technical solution of Google Earth Engine-supported analysis of statistics and machine learning to spatially monitoring the population change and urban growth of four major Pakistan cities. It is undoubted that our working results will provide the timely and cost-effective information to policymakers, Govt Officials and citizens for more sustainable urbanization.