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Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques

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Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques. / Bhattacharjee, Shwarnali ; Islam, Md Tariqul ; Kabir, Ehsan et al.
In: Earth Systems and Environment, Vol. 5, No. 2, 30.06.2021, p. 319-340.

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Bhattacharjee S, Islam MT, Kabir E, Kabir MM. Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques. Earth Systems and Environment. 2021 Jun 30;5(2):319-340. Epub 2021 Jun 4. doi: 10.1007/s41748-021-00228-3

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Bhattacharjee, Shwarnali ; Islam, Md Tariqul ; Kabir, Ehsan et al. / Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques. In: Earth Systems and Environment. 2021 ; Vol. 5, No. 2. pp. 319-340.

Bibtex

@article{be5d8cda499d4e63885654825f13c8bb,
title = "Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques",
abstract = "Lakshmibaur-Nalair Haor, a freshwater wetland ecosystem is situated in the north-eastern region of Bangladesh. This place hosts the second largest freshwater swamp forest in Bangladesh. Containing rich biodiversity, this unique area experiences significant landscape changes. This study examines land-use and land-cover (LULC) changes between 1989 and 2019 in the Lakshmibaur-Nalair Haor area by operating Landsat multispectral imageries through remote sensing (RS) and geographic information system (GIS) techniques. The changing status of the haor was analyzed by initiating normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI). The unsupervised classification technique was implemented to classify these images into five major classes (vegetation, cropland, bare soil, shallow water, and deep water bodies) using threshold values of NDVI and MNDWI. After accuracy assessment, the post-classification comparison method was performed to evaluate the change detection. This study demonstrates that this valuable area lost ~ 2208.6 ha (37.54%) of the deep water body and 489.6 ha (8.34%) of vegetation over the last 3 decades. However, it has gained about 1729 ha (29.39%) of cropland, 2673 ha (45.44%) of shallow water and 1124 ha (28%) of bare soil. Such changes indicate significant human interventions such as expansion of croplands with increased population pressure. Gradual change of deep water into shallow water over time is enabling local community to expand agricultural lands and activities during the dry season. This study{\textquoteright}s findings are useful in understanding and tracking changes in wetlands in Bangladesh and other similar settings.",
keywords = "LULC, NDVI, MNDWI, Haors, Bangladesh",
author = "Shwarnali Bhattacharjee and Islam, {Md Tariqul} and Ehsan Kabir and Kabir, {Md Muhib}",
year = "2021",
month = jun,
day = "30",
doi = "10.1007/s41748-021-00228-3",
language = "English",
volume = "5",
pages = "319--340",
journal = "Earth Systems and Environment",
publisher = "Springer International Publishing AG",
number = "2",

}

RIS

TY - JOUR

T1 - Land-Use and Land-Cover Change Detection in a North-Eastern Wetland Ecosystem of Bangladesh Using Remote Sensing and GIS Techniques

AU - Bhattacharjee, Shwarnali

AU - Islam, Md Tariqul

AU - Kabir, Ehsan

AU - Kabir, Md Muhib

PY - 2021/6/30

Y1 - 2021/6/30

N2 - Lakshmibaur-Nalair Haor, a freshwater wetland ecosystem is situated in the north-eastern region of Bangladesh. This place hosts the second largest freshwater swamp forest in Bangladesh. Containing rich biodiversity, this unique area experiences significant landscape changes. This study examines land-use and land-cover (LULC) changes between 1989 and 2019 in the Lakshmibaur-Nalair Haor area by operating Landsat multispectral imageries through remote sensing (RS) and geographic information system (GIS) techniques. The changing status of the haor was analyzed by initiating normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI). The unsupervised classification technique was implemented to classify these images into five major classes (vegetation, cropland, bare soil, shallow water, and deep water bodies) using threshold values of NDVI and MNDWI. After accuracy assessment, the post-classification comparison method was performed to evaluate the change detection. This study demonstrates that this valuable area lost ~ 2208.6 ha (37.54%) of the deep water body and 489.6 ha (8.34%) of vegetation over the last 3 decades. However, it has gained about 1729 ha (29.39%) of cropland, 2673 ha (45.44%) of shallow water and 1124 ha (28%) of bare soil. Such changes indicate significant human interventions such as expansion of croplands with increased population pressure. Gradual change of deep water into shallow water over time is enabling local community to expand agricultural lands and activities during the dry season. This study’s findings are useful in understanding and tracking changes in wetlands in Bangladesh and other similar settings.

AB - Lakshmibaur-Nalair Haor, a freshwater wetland ecosystem is situated in the north-eastern region of Bangladesh. This place hosts the second largest freshwater swamp forest in Bangladesh. Containing rich biodiversity, this unique area experiences significant landscape changes. This study examines land-use and land-cover (LULC) changes between 1989 and 2019 in the Lakshmibaur-Nalair Haor area by operating Landsat multispectral imageries through remote sensing (RS) and geographic information system (GIS) techniques. The changing status of the haor was analyzed by initiating normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI). The unsupervised classification technique was implemented to classify these images into five major classes (vegetation, cropland, bare soil, shallow water, and deep water bodies) using threshold values of NDVI and MNDWI. After accuracy assessment, the post-classification comparison method was performed to evaluate the change detection. This study demonstrates that this valuable area lost ~ 2208.6 ha (37.54%) of the deep water body and 489.6 ha (8.34%) of vegetation over the last 3 decades. However, it has gained about 1729 ha (29.39%) of cropland, 2673 ha (45.44%) of shallow water and 1124 ha (28%) of bare soil. Such changes indicate significant human interventions such as expansion of croplands with increased population pressure. Gradual change of deep water into shallow water over time is enabling local community to expand agricultural lands and activities during the dry season. This study’s findings are useful in understanding and tracking changes in wetlands in Bangladesh and other similar settings.

KW - LULC

KW - NDVI

KW - MNDWI

KW - Haors

KW - Bangladesh

U2 - 10.1007/s41748-021-00228-3

DO - 10.1007/s41748-021-00228-3

M3 - Journal article

VL - 5

SP - 319

EP - 340

JO - Earth Systems and Environment

JF - Earth Systems and Environment

IS - 2

ER -