Abstract
The Rohingya refugee influx to Bangladesh in 2017 was a historical incident; the number of refugees was so massive that significant impacts to local communities was inevitable. The Bangladesh government provided land in a preserved area for constructing makeshift camps for the refugees. Previous studies have revealed the land cover changes and impacts of the refugee influx around campsites, especially with regard to local forest resources. Our aim is to establish a convenient approach of providing up-to-date information to monitor holistic local situations. We employed a classic unsupervised technique—a combination of k-means clustering and maximum likelihood estimation—with the latest rich time-series satellite images of Sentinal-1 and Sentinal-2. A combination of VV and normalized difference water index (NDWI) images was successful in identifying built-up/disturbed areas, and a combination of VH and NDWI images was successful in differentiating wetland/saltpan, agriculture /open field, degraded forest/bush, and forest areas. By doing this, we provided annual land cover classification maps for the entire Teknaf peninsula for the pre- and post-influx periods with both fair quality and without prior training data. Our analyses revealed that on-going impacts were still observed by May 2021. As a simple estimation of the intervention consequence, the built-up/disturbed areas increased 6825 ha (compared with the 2015–17 period). However, while the impacts on the original forest were not found to be significant, the degraded forest/bush areas were largely degraded by 4606 ha. These cultivated lands would be used for agricultural activities. This is in line with the reported farmers’ increased income, despite local people with other occupations that are all equally facing the decreases in income. The convenience of our unsupervised classification approach would help keep accumulating a time-series land cover classification, which is important in monitoring impacts on local communities.
Highlights
In August 2017, the massive Rohingya refugee influx to Cox’s Bazar, Bangladesh fromRakhine state, Myanmar shocked the world
We demonstrate that the larger number of input images can compensate for prior training data by using all available free S1 and
Regarding the images for the post-influx period, our aim was for a yearly classification, so about one year after 25 August 2017 was excluded from the analysis; this is because the campsite construction was on-going and the land cover was assumed unstable
Summary
In August 2017, the massive Rohingya refugee influx to Cox’s Bazar, Bangladesh fromRakhine state, Myanmar shocked the world. The Bangladesh government provided the land for constructing makeshift camps for the estimated 671,500 refugees at that time [1]. Because of the sheer number of refugees pouring in, as well as the country itself already having a highly dense population, the government needed to clear the preserved forest area in Cox’s Bazar. Hassan et al (2020) [3] estimated that 1600 to 2200 ha of forestland was initially cleared, and 3200 ha of forest were either gone or degraded between 2017 and 2019. Hassan et al (2018) [2], as well as Barun et al (2019) [4], report the campsite specific estimation. Their findings reveal that the Kutupalong–Balukhali campsite showed
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