Skip to main navigation Skip to search Skip to main content

Quantifying spatiotemporal changes of the urban impervious surface of Dhaka District using Remote sensing Technology

  • Mahzabin Abbasi
  • , Samsunnahar Popy*
  • , Tan Yumin
  • *Corresponding author for this work
  • Beihang University
  • Bangabandhu Sheikh Mujibur Rahman Science and Technology University (BSMRSTU)

Research output: Contribution to journalArticlepeer-review

Abstract

Dhaka, the capital of Bangladesh, is one of the world's fastest-growing cities where imperviousness expanding in tandem. Therefore, accurate estimation of impervious surfaces is essential for urban planning and management. This paper attempts to quantify the changes of urban impervious surfaces in Dhaka district from 1990 to 2020 using remote sensing technology. Satellite images of 1990, 1995, 2000, 2005, 2010, 2015, and 2020 have been taken from the Landsat TM, ETM+, OLI sensor. Unsupervised classification with k-means clustering and three different RS indices NDVI, NDBI, and BUI was used to delineate the actual impervious area of Dhaka city. This study reveals that due to urbanization a net increase of 67.30 sq. miles impervious area is added to the existing amount over the study period. In 2020 total 300.749 sq. miles which contain 51.02% of the total land were occupied by impervious surfaces compared to the 233.446 sq. miles in 1990. Instantaneously taking appropriate strategies is crucial for sustainable urban growth.

Original languageEnglish
Pages (from-to)373-382
Number of pages10
JournalIndonesian Journal of Geography
Volume54
Issue number3
DOIs
StatePublished - 13 Oct 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • BUIIndex
  • Dhaka
  • ImperviousArea
  • Remote Sensing
  • Unsupervised classification

Fingerprint

Dive into the research topics of 'Quantifying spatiotemporal changes of the urban impervious surface of Dhaka District using Remote sensing Technology'. Together they form a unique fingerprint.

Cite this