Litcius/Paper detail

Analyzing Ecological Environmental Quality Trends in Dhaka Through Remote Sensing Based Ecological Index (RSEI)

Md. Mahmudul Hasan, Md Tasim Ferdous, Md. Talha, Pratik Mojumder, Sujit Kumar Roy, Md. Nasim Fardous Zim, Most. Mitu Akter, N. M. Refat Nasher, Fahdah Falah Ben Hasher, Martin Boltižiar, Mohamed Zhran

2025Land16 citationsDOIOpen Access PDF

Abstract

Assessing the ecological environmental quality (EEQ) is crucial for protecting the environment. Dhaka’s rapid, unplanned urbanization, driven by economic and social growth, poses significant eco-environmental challenges. Spatiotemporal ecological and environmental quality changes were assessed using remote sensing based ecological index (RSEI) maps derived from Landsat images (1993, 2003, 2013, and 2023). RSEI was based on four indicators—greenness (NDVI), heat index (LST), dryness (NDBSI), and wetness (LSM). Landsat 5 TM and 8 OLI/TIRS images were processed on Google Earth Engine (GEE), with principal component analysis (PCA) applied to determine RSEI. The findings showed a decline in the overall RSEI (1993–2023), with low- and very low-quality areas increasing by about 39% and high- and very high-quality areas decreasing by 24% of the total area. NDBSI and LST were negatively correlated with RSEI, except in 1993, while NDVI and LSM were generally positive but negative in 1993. The global Moran’s I (0.88–0.93) indicated strong spatial correlation in the distribution of EEQ across Dhaka. LISA cluster maps showed high-high clusters in the northeast and east, while low-low clusters were concentrated in the northwest. This research examines the degradation of ecological conditions over time in Dhaka and provides valuable insights for policymakers to address environmental issues and improve future ecological management.

Topics & Concepts

Index (typography)EcologyRemote sensingQuality (philosophy)GeographyEnvironmental scienceEnvironmental qualityEnvironmental resource managementComputer scienceBiologyWorld Wide WebEpistemologyPhilosophyLand Use and Ecosystem ServicesRemote Sensing in AgricultureRemote-Sensing Image Classification