Very High Resolution Satellites: A New Source of Information In Humanitarian Relief Operations

Bjørgo, Einar

doi:10.1002/bult.138

Cited by 7 publications

(5 citation statements)

References 91 publications

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“…Notably, they are unable to show factors responsible for forest degradation, help prediction of forest degradation (assuming a business‐as‐usual scenario), and most importantly, assess loss of ecosystem function over space and time. Planning and efficient management of meagre natural resources requires up ‐ to ‐ date data, therefore, availability of existing forest resources and potential loss in relation to refugee migration is expected to provide crucial information to managers and policymakers (Bjørgo, 1999; Bouchardy, 1995; Morales‐Hidalgo, Oswalt, & Somanathan, 2015; Romijn et al, 2015). Our work attempts to answer two research questions: (i) What is the extent of forest degradation in the environmentally sensitive Cox's Bazar – Teknaf Peninsula in response to Rohingya influx?…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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“…International relief organizations working globally and supporting people in need sometimes have only very limited knowledge of the prevailing circumstances in the countries and landscapes they are operating in. Thus, geographic information is one of the key factors that need to be assessed for effective humanitarian relief operations (Bouchardy 1995;Bjorgo 1999;UNHCR 2000). Especially in remote areas or regions where geospatial information and detailed map material tends to be inaccurate or even fails to exist, satellite imagery may provide objective and up-to-date information about a given area and thus complement the information about the on-ground situation, which is usually collected by field missions (Bouchardy 1995).…”

Section: The Demand For Eo-based Informationmentioning

confidence: 99%

Earth observation-based multi-scale impact assessment of internally displaced person (IDP) camps on wood resources in Zalingei, Darfur

Spröhnle

Kranz

Schöepfer

et al. 2015

Geocarto International

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This study describes the development of a semi-automatic object-based image analysis approach for the detection and quantification of deforestation in Zalingei, Darfur, in consequence of the increasing concentration of refugees or internally displaced persons (IDPs) in the region. The classification workflow is based on a multi-scale approach, ranging from the analysis of high resolution SPOT-4 to very high resolution IKONOS and QuickBird satellite imagery between 2003 and 2008. The overall accuracy rates for the classification of the SPOT 4 data ranged from 92% up to 95%, while those for the QuickBird and IKONOS classification have shown values of 88 and 87%, respectively. The resulting trends in woody vegetation cover were compared with the development of the local population and the variability of precipitation. The results show that the strong increase in human population in the Zalingei IDP camps can be associated with considerable decrease in woody vegetation in the camp vicinity.

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“…Notably, they are unable to show factors accountable for forest degradation, prediction of forest degradation (assuming business-as-usual scenario), and most importantly, loss of ecosystem function over space and time. Planning and efficient management of meagre natural resources requires up-to-date data, therefore, availability of existing forest resources and potential loss in relation to refugee migration is expected to provide crucial information to managers and policymakers (Morales-Hidalgo, 2015; Romijn et al, 2015;Bouchardy, 1995;Bjørgo, 1999). This work, thus, attempts to answer two research questions: (i) what is the extent of forest degradation in environmentally sensitive Cox's Bazar-Teknaf peninsula in response to Rohingya influx; and (ii) what is (would) be the degree of ecosystem function loss, at present and in the future, under multiple stressors and stimulus, if Rohingya issue persists.…”

Section: Introductionmentioning

confidence: 99%

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

Hasan

Zhang

Dewan

et al. 2020

Preprint

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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.

show abstract

Very High Resolution Satellites: A New Source of Information In Humanitarian Relief Operations

Cited by 7 publications

References 91 publications

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

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

Earth observation-based multi-scale impact assessment of internally displaced person (IDP) camps on wood resources in Zalingei, Darfur

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

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