LAND USE AND LAND COVER CHANGE DETECTION BY USING REMOTE SENSING AND GIS TECHNOLOGY IN BARISHAL DISTRICT, BANGLADESH

Md. Abdullah Salman (), Md. Saleh Shakeel Nomaan, Saifullah Sayed, Ayon Saha and Muhammad Risalat Rafiq
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Md. Abdullah Salman: Department of Geology & Mining, University of Barishal, Barishal-8200, Bangladesh
Md. Saleh Shakeel Nomaan: Department of Geology & Mining, University of Barishal, Barishal-8200, Bangladesh
Saifullah Sayed: Department of Geology & Mining, University of Barishal, Barishal-8200, Bangladesh
Ayon Saha: Department of Geology & Mining, University of Barishal, Barishal-8200, Bangladesh
Muhammad Risalat Rafiq: Department of Geology & Mining, University of Barishal, Barishal-8200, Bangladesh

Earth Sciences Malaysia (ESMY), 2021, vol. 5, issue 1, 33-40

Abstract: Barishal has recently gone through intense land use and land cover changes (LULC). This study aims to assess the changes of land use of Barishal, which were surveyed from 2000 to 2020 by utilizing Landsat TM, ETM + & OLI-TIRS imageries. The ArcGIS-10.4 & the ERDAS-14 Imagine software were used to deal with satellite images and surveyed measurable data for land cover change evaluation of the study area. Both pre- and postclassification change detection scenarios and NDVI analysis were observed to assess the change result from2000 to 2020. Maximum likelihood classification was utilized to create unsupervised land cover category(water body, urban, fallow, agriculture, vegetation and lowland). After ensuring acceptable value for each classified image (82.16% for 2020, 76.15% for 2010 & 70.96% for 2000 with Kappa values of 0.64, 0.62 & 0.62 for 2020, 2010 and 2000), a change detection study was performed. This study discovered that the highest growth 69.22% of urban area has been improved within 20 years followed by 49.75% and 21.74% of water bodies, fallow lands; whereas the annual change rate was 14.95%, 7.91% and 10.31% respectively. In contrast, 16.28%, 10.48% and 37.20% of vegetation, agriculture and lowland had been reduced and an (-) annual change rate of 16.03%, 7.15% and 9.99% respectively. In addition, NDVI analysis was also observed a decreasing trend of the vegetation and agricultural lands. The results of this assessment could be supportive to design and appliance significant managing appraisals to protect the agricultural degradation, fruitless urbanization of Barishal district.

Keywords: Accuracy Assessment; Landsat; Relative Change; Unsupervised classification. (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbesmy:v:5:y:2021:i:1:p:33-40

DOI: 10.26480/esmy.01.2021.33.40

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