Spatiotemporal pattern of forest degradation and loss of ecosystem function associated with Rohingya influx

A geospatial approach

Dados Bibliográficos

ID21649202
AutoresMohammad Emran Hasan (0000-0002-1151-8257, Key Laboratory of Digital Earth Science, Aerospace Information Research Institute Chinese Academy of Sciences Beijing PR China, autor correspondente), Li Zhang (0000-0002-4441-5131, Key Laboratory of Digital Earth Science, Aerospace Information Research Institute Chinese Academy of Sciences Beijing PR China), Ashraf Dewan (0000-0001-5594-5464, School of Earth and Planetary Sciences (EPS), Spatial Sciences Discipline Curtin University Perth Australia), Huadong Guo (0000-0003-0337-1862, Key Laboratory of Digital Earth Science, Aerospace Information Research Institute Chinese Academy of Sciences Beijing PR China), Riffat Mahmood (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute Chinese Academy of Sciences Beijing PR China)
Ano2021
Volume32
Fascículo13
Páginas3666-3683
Data de publicação2021-08-15
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoLand Degradation and Development (JOURNAL)
Identificadores do periódicoISSN: 1085-3278 • E-ISSN: 1099-145X
EditoraWiley (PUBLISHER • GB)
DOI10.1002/ldr.3821
OpenAlexW3095411692
IdiomaEN
Citações recebidas16
Referências citadas51

Violence in Rakhine State of Myanmar forcibly displaced nearly one million Rohingya. They took refuge, from August 25, 2017 to the time of writing, in Cox's Bazar – Teknaf Peninsula of Bangladesh. Initially, nearly 2,000 ha of forested lands had to be cleared to accommodate them in one of the most ecologically critical areas (ECA) in the Peninsula. To support Rohingyas livelihoods, fuelwood collection and illegal logging have become widespread since their arrival, causing severe environmental degradation, including loss of a vast amount of forest cover. To devise conservation and protection strategies for a highly sensitive ecosystem, it is imperative to understand the degree of forest cover deterioration and associated impacts related to Rohingya emigration. This study employed satellite images and collateral data to monitor and model spatiotemporal patterns of forest cover degradation and loss of ecosystem function in Cox's Bazar – Teknaf Peninsula. Supervised classification method was used to derive multi‐date land use/cover data which was then utilized to monitor spatiotemporal pattern of forest cover change from 2017 to 2019. A projection of forest cover loss was also carried out using the Markov chain with cellular automata technique. Dynamic modeling was performed to predict changes in forest covers, assuming that displaced Rohingya continues to reside in this environmentally sensitive location. The result revealed that 3,130 ha of forested lands of different categories were transformed into either refugee camps or Rohingya influenced degraded forests between 2017 and 2019. Prediction showed that around 5,115 ha of forest cover may experience loss from 2019 to 2027. Furthermore, aboveground biomass and carbon stock estimation indicated a consistent and substantial loss during the study period, which is likely to swell if present deforestation rate continues. The findings have considerable implications in developing conservation decisions, priority interventions and public policies to save the ECA of Bangladesh

Agriculture · Agroforestry · Biology · Ecosystem · Environmental protection · Environmental resource management · Geography · Geomatics · Land cover · Land use · Livelihood · Peninsula · Remote sensing · Conservation, Biodiversity, and Resource Management · Environmental Science · Rangeland Management and Livestock Ecology · Wildlife Ecology and Conservation · Ecology