Published August 2021 | Version v1
Journal article

Satellite analysis of the environmental impacts of armed-conflict in Rakhine, Myanmar

  • 1. Asia Center, Faculty of Arts and Sciences, Harvard University, Cgis South, 1730 Cambridge St., Cambridge, MA, 02138 (United States)

Description

Highlights: • Rohingya conflict is one of the worst humanitarian crises of the 21st Century. • Satellite-based machine-learning estimates LULCC in conflict-zone. • Investigated the environmental conditions pre-, during, and post-conflict. • Google Earth Engine (GEE) cloud-based computing platform was used. • Found demolition of inhabited region, increase in burning areas, and deforestation. The impacts of armed conflict on the environment are extremely complex and difficult to investigate, given the impossibility of accessing the affected area and reliable data limitation. Very-high-resolution satellite imageries and highly reliable machine learning algorithms become very useful in studying direct and indirect impacts of war on the ecosystem, in addition to connected effects on human lives. The Rohingya conflict is described as one of the worst humanitarian crises and human-made disasters of the 21st Century. Quantification of damage due to the conflict and the suitability of human resettlement has been lacking despite the ongoing agreements to repatriate refugees and the importance of ecosystem services for the communities' survival. In this work, the investigation of environmental conditions pre-, during, and post-conflict in the conflict zone was carried out using satellite data. The Google Earth Engine (GEE) cloud-based computing platform with a widely applied algorithm, the Random Forest (RF) classifier was implemented and experienced. Striking near-complete demolition of inhabited regions, dramatic and highly significant increase in burning areas, and substantial deforestation were found. The study discusses the reasons behind such findings from the Rakhine case and debates some general conservation lessons applicable to other countries undergoing post-conflict transitions.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.scitotenv.2021.146758

Additional details

Identifiers

DOI
10.1016/j.scitotenv.2021.146758;
PII
S004896972101826X;

Publishing Information

Journal Title
Science of the Total Environment
Journal Volume
781
Journal Page Range
vp.
ISSN
0048-9697
CODEN
STENDL

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
54057698
Subject category
S54: ENVIRONMENTAL SCIENCES; S47: OTHER INSTRUMENTATION;
Descriptors DEI
DEFORESTATION; ECOSYSTEMS; ENVIRONMENTAL IMPACTS; FORESTS; MACHINE LEARNING; NATURAL DISASTERS; RANDOMNESS; REMOTE SENSING; RESOLUTION
Descriptors DEC
ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING; MATHEMATICAL LOGIC

Optional Information

Copyright
Copyright (c) 2021 Elsevier B.V. All rights reserved.