Simulating Land Cover Changes and Their Impacts on Land Surface Temperature in Dhaka, Bangladesh

Remote Sensing

Bayes Ahmed¹  Md. Kamruzzaman³  Xuan Zhu²  Md. Shahinoor Rahman⁴ 

[1] Institute for Risk and Disaster Reduction (IRDR), Department of Earth Sciences, University College London (UCL), Gower Street, London WC1E 6BT, UK;School of Geography & Environmental Science, Building 11, Clayton Campus, Monash University, Melbourne, VIC 3800, Australia; E-Mail:;School of Civil Engineering and the Built Environment, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia; E-Mail:;BUET-Japan Institute of Disaster Prevention and Urban Safety (BUET-JIDPUS), Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh; E-Mail:

关键词: land cover change;    land surface temperature;    urban heat island effect;    NDVI;    artificial neural network;    Markov chain;    Dhaka;   

DOI  :  10.3390/rs5115969

来源: mdpi

【 摘 要 】

Despite research that has been conducted elsewhere, little is known, to-date, about land cover dynamics and their impacts on land surface temperature (LST) in fast growing mega cities of developing countries. Landsat satellite images of 1989, 1999, and 2009 of Dhaka Metropolitan (DMP) area were used for analysis. This study first identified patterns of land cover changes between the periods and investigated their impacts on LST; second, applied artificial neural network to simulate land cover changes for 2019 and 2029; and finally, estimated their impacts on LST in respective periods. Simulation results show that if the current trend continues, 56% and 87% of the DMP area will likely to experience temperatures in the range of greater than or equal to 30 °C in 2019 and 2029, respectively. The findings possess a major challenge for urban planners working in similar contexts. However, the technique presented in this paper would help them to quantify the impacts of different scenarios (e.g., vegetation loss to accommodate urban growth) on LST and consequently to devise appropriate policy measures.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland