Spatiotemporal pattern of forest degradation and loss of ecosystem function associated with Rohingya influx: a geospatial approach

Abstract

Violence in Rakhine, Myanmar forcibly displaced nearly one million Rohingya who took refuge in Cox's Bazar-Teknaf peninsula of Bangladesh. Initially, nearly 2,000 ha of forested lands had to be cleared to accommodate them in an area, that is ecologically very sensitive. 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 strategies of 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 to monitor and model spatiotemporal pattern of forest cover degradation, and loss of ecosystem function in the peninsula. Supervised classification method was used to derive multidate land use/cover data which was then utilized to monitor spatiotemporal pattern of forest cover change from 2017-2019. Dynamic modelling was performed to predict changes in the forest covers using markov cellular automata. Analysis revealed that 3,130 ha of different forested covers were transformed into either refugee camps or degraded forest cover between 2017 and 2019. Prediction showed that around 5,115 ha of forest may experience loss from 2019-2027. Furthermore, above ground biomass and carbon stock estimation indicated a consistent loss, which is likely to swell if present rate of deforestation continues. The findings of this work have considerable implications in developing conservation decisions, priority interventions and public policies to save an ecologically sensitive area.

A Study on the Impact of Refugee Influx on the Agricultural Service, Systems and Products;

“…consumption and irrigation decreased remarkably due to the over-lifting of groundwater for the Rohingya people and the blocking of the water channel for Rohingya settlements 14,22) . All the refugee camps were established inside forest areas, resulting in deforestation 34) . IC Net (2018) 35) reported a few challenges to agriculture due to the Rohingya influx in Bangladesh, such as a decrease in cultivable land, scarcity of water supply and damage to crops.…”

“…Despite the designation of the region as an ecologically critical area in 1999 32,36) and the protective status afforded to local forests, community reliance on these resources persists with few alternative means of livelihood 28,37) . The pressures on natural resources have been accentuated by the refugee presence 33,34) , with water sources for both domestic use and irrigation being notably over-exploited to accommodate the needs of the Rohingya settlements. Additionally, the establishment of refugee camps within forested areas has led to considerable deforestation, further depleting the environmental assets that the local agricultural systems depend upon.…”

Spatio-temporal variation of land use and land cover changes and their impact on land surface temperature: A case of Kutupalong Refugee Camp, Bangladesh

“…The process of relocating refugees appears to be lengthy and complicated ( Rashid, 2020 ), but forest ecosystem integrity must be conserved to prevent further damage. Therefore, the degree of stress, level of impacts, and pattern of deforestation is critical data for the forest conservation and protection process ( Hasan et al., 2020 ) and periodic assessment of LULC changes is essential to understand the extent of human intervention in the natural settings and find out the remedy to mitigate the potential impacts of unbalanced human-environment interactions.…”

Land‐use change impacts on soil and vegetation attributes in the Kanshi River basin, Potohar Plateau, Pakistan

“…Large numbers of studies have been carried out regarding the methods of LULCC over Asian regions (Hasan et al, 2021; Lin et al, 2021; Malek & Verburg, 2020; Ullah et al, 2019; Yohannes et al, 2021). Ullah et al (2019) used the remote sensing and geographical information system (RS/GIS)‐based classification of the LANDSAT satellite images for the detection of the land cover changes over the Himalayan regions of Pakistan.…”

“…Ullah et al (2019) used the remote sensing and geographical information system (RS/GIS)‐based classification of the LANDSAT satellite images for the detection of the land cover changes over the Himalayan regions of Pakistan. Hasan et al (2021) detected forest patterns using the RS/GIS‐based postclassification techniques over the region of Rohingya camps. Furthermore, the land cover changes and their spatial distribution are widely shown by using the RS/GIS‐based mapping of land capability and geospatial methods (Malek & Verburg, 2020).…”