Land Cover Classification and Change Detection Analyzing Multi-Temporal Landsat Data: A Case Study of Gazipur Sadar, Bangladesh between 1973 and 2017

Abstract

This paper analyzed land cover changes in Gazipur Sadar - an important urban fringe of expanding Dhaka City, Bangladesh, by leveraging remotely sensed imageries between 1973 and 2017. Landsat images of1973, 1991, 2006, and 2017 were classified using widely-preferred supervised classification method. Compared against ground-truth data, the reported classification accuracy ranges from 85% to 89%. Our classified land cover maps reveal that built-up areas in Gazipur Sadar increased by 312.9%, mostly replacing vegetation cover. An overall 199.7% decrease of vegetative covers highlights on the degree of urbanization process and increasing population pressure faced by Gazipur Sadar over the past decades. The rapid decrease of vegetative cover only 57 sq. km remains out of 344 sq. km throughout the region, including the Sal (Shorea robusta) forest and other floral species - invaluable resources for biodiversity and ecosystem health, should be taken as 'alarming' situation by the local authority responsible for promoting and managing sustainable development goals. In that light, this study emphasizes on the need for a critical assessment of future development initiatives in the Gazipur Sadar area and suggests for maintaining acceptable tradeoffs between development and environmental protection.

Keywords

• land cover (lulc) classification
• change detection
• geographic information system
• gazipur sadar (bangladesh)
• urban
• sustainability