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Article

Analysis of Vegetative Cover Vulnerability in Rohingya Refugee Camps of Bangladesh Utilizing Landsat and Per Capita Greening Area (PCGA) Datasets

by 1,2,3,4,5,6 and 1,7,*
1
School of Geospatial Engineering and Science, Sun Yat-sen University, Guangzhou 510275, China
2
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
3
School of Resource and Environmental Sciences, Wuhan University, 129 Luoyu Road, Wuhan 430079, China
4
Department of Geography and Environment, Jagannath University, 9-10 Chittaranjan Avenue, Dhaka 1100, Bangladesh
5
Shahidul Consultant Ltd., 66/D Indira Road, Farmgate, Dhaka 1215, Bangladesh
6
Network for Information, Response and Preparedness Activities on Disaster (NIRAPAD), 4/16 (1st Floor), Humayun Road, Block-B, Mohammadpur, Dhaka 1207, Bangladesh
7
Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China
*
Author to whom correspondence should be addressed.
Academic Editor: Donato Amitrano
Remote Sens. 2021, 13(23), 4922; https://doi.org/10.3390/rs13234922
Received: 27 September 2021 / Revised: 25 November 2021 / Accepted: 30 November 2021 / Published: 3 December 2021
(This article belongs to the Special Issue Remote Sensing of Anthropic Impact on the Environment)
The vegetative cover in and surrounding the Rohingya refugee camps in Ukhiya-Teknaf is highly vulnerable since millions of refugees moved into the area, which led to severe environmental degradation. In this research, we used a supervised image classification technique to quantify the vegetative cover changes both in Ukhiya-Teknaf and thirty-four refugee camps in three time-steps: one pre-refugee crisis (January 2017), and two post-refugee crisis (March 2018, and February 2019), in order to identify the factors behind the decline in vegetative cover. The vegetative cover vulnerability of the thirty-four refugee camps was assessed using the Per Capita Greening Area (PCGA) datasets and K-means classification techniques. The satellite-based monitoring result affirms a massive loss of vegetative cover, approximately 5482.2 hectares (14%), in Ukhiya-Teknaf and 1502.56 hectares (79.57%) among the thirty-four refugee camps, between 2017 and 2019. K-means classification revealed that the vegetative cover in about 82% of the refugee camps is highly vulnerable. In the end, a recommendation as to establishing the studied region as an ecological park is proposed and some guidelines discussed. This could protect and reserve forests from further deforestation in the area, and foster future discussion among policymakers and researchers. View Full-Text
Keywords: Rohingya refugee crisis; vegetative cover vulnerability analysis; Landsat; supervised image classification; per capita greening area (PCGA) datasets; K-means classification; spatiotemporal change analysis Rohingya refugee crisis; vegetative cover vulnerability analysis; Landsat; supervised image classification; per capita greening area (PCGA) datasets; K-means classification; spatiotemporal change analysis
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MDPI and ACS Style

Karim, M.F.; Zhang, X. Analysis of Vegetative Cover Vulnerability in Rohingya Refugee Camps of Bangladesh Utilizing Landsat and Per Capita Greening Area (PCGA) Datasets. Remote Sens. 2021, 13, 4922. https://doi.org/10.3390/rs13234922

AMA Style

Karim MF, Zhang X. Analysis of Vegetative Cover Vulnerability in Rohingya Refugee Camps of Bangladesh Utilizing Landsat and Per Capita Greening Area (PCGA) Datasets. Remote Sensing. 2021; 13(23):4922. https://doi.org/10.3390/rs13234922

Chicago/Turabian Style

Karim, Md F., and Xiang Zhang. 2021. "Analysis of Vegetative Cover Vulnerability in Rohingya Refugee Camps of Bangladesh Utilizing Landsat and Per Capita Greening Area (PCGA) Datasets" Remote Sensing 13, no. 23: 4922. https://doi.org/10.3390/rs13234922

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