A GIS and remote sensing approach for measuring summer-winter variation of land use and land cover indices and surface temperature in Dhaka district, Bangladesh-Reference-Cited by-同舟云学术

A GIS and remote sensing approach for measuring summer-winter variation of land use and land cover indices and surface temperature in Dhaka district, Bangladesh

Published:2022-08 Issue:8 Volume:8 Page:e10309
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Sresto Mizbah Ahmed,Siddika Sharmin,Fattah Md. Abdul,Morshed Syed Riad,Morshed Md. Manjur

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference62 articles.

1. Assessment of land surface temperature and land cover variability during winter: A spatio-temporal analysis of Pabna municipality in Bangladesh;Abir;Environ. Chall.,2021

2. Investigating surface urban heat island characteristics over Abuja, Nigeria: relationship;Adeyeri;Remote Sens. Appl. Soc. Environ.,2017

3. Simulating land cover changes and their impacts on land surface temperature in Dhaka, Bangladesh;Ahmed;Rem. Sens.,2013

4. Investigative spatial distribution and modelling of existing and future urban land changes and its impact on urbanization and economy;Akbar;Rem. Sens.,2019

5. Crop Suitability Analysis in Water Resource Management of Paschim Midnapore District: a Remote Sensing Approach, Sustainable Water Resources Management;Akram,2018

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Assessing seasonal dynamics of land surface temperature (LST) and land use land cover (LULC) in Bhairab, Kishoreganj, Bangladesh: A geospatial analysis from 2008 to 2023;Case Studies in Chemical and Environmental Engineering;2024-06

2. Impact of anthropological activities on land-use and land-cover changes in the lower Okavango Delta, Botswana;Transactions of the Royal Society of South Africa;2024-01-03

3. Comparison of accuracy and reliability of random forest, support vector machine, artificial neural network and maximum likelihood method in land use/cover classification of urban setting;Environmental Challenges;2024-01

4. Spatiotemporal Characterization of LST and Analysis of Its Spatial Dependence: A Spatial Autocorrelation Approach;Lecture Notes in Civil Engineering;2023

5. A Systematic Review of Machine Learning Applications in Land Use Land Cover Change Detection using Remote Sensing;International Journal of Applied Engineering and Management Letters;2022-12-31