Delineating Drought Risk Areas Using Remote Sensing and Geographic Information Systems– A Case Study of Western Highlands Province, Papua New Guinea

Nicholas Korada, Tingneyuc Sekac, Sujoy Kumar Jana and Dilip Kumar Pal
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Nicholas Korada: Department of Surveying and Land Studies, Papua New Guinea University of Technology, Lae-411, Papua New Guinea
Tingneyuc Sekac: Department of Surveying and Land Studies, Papua New Guinea University of Technology, Lae-411, Papua New Guinea
Sujoy Kumar Jana: Dept. of Surveying & Land Studies, The Papua New Guinea University of Technology, Lae-411, Morobe Province,Papua New Guinea. Mobile:(+91) 9434509227/7872346900 (India) Mobile:(+675)72423761 / 78051214 (Papua New Guinea) Email:sujoy2007@gmail.com : sujoy_jana@yahoo.com : skjana@survey.unitech.ac.pg
Dilip Kumar Pal: Department of Surveying and Land Studies, Papua New Guinea University of Technology, Lae-411, Papua New Guinea

European Journal of Engineering and Technology Research, 2018, vol. 3, issue 10, 103-110

Abstract: In the highlands of Papua New Guinea, rain-fed subsistence farming has been the main source of food and small cash earnings for the majority of the rural population. Consequently, as a result of elongated period of drought, reduction in food and water supply bring forth starvation / malnutrition led sickness and death, especially when authorities fail to intervene because inaccessibility and remoteness of the highly dissected terrain, as a result relief and basic services don’t reach the hungry mouth on time. Such conditions were reported recently in many parts of Papua New Guinea especially prevalent in coastal regions and uplands of the highlands region. In this study, GIS and Remote Sensing (RS) technology were employed in highlighting and demarcating potential drought risk zones in Western Highlands Province. Basically, several environmental factors like; soil types, NDVI, rainfall, terrain, population demography and surface temperature were prepared and integrated in GIS environment through multi-criteria evaluation techniques where risk areas were identified. The final output generated from factors integration were then assessed and reclassified to indicate levels of drought risk zones from Low, Medium and High. Hence, several built-up areas where then marked on each risk zones in an attempt to highlight the location, distribution and accessibility in respect to the risk areas identified.

Keywords: Drought; GIS & Remote Sensing; Multi-Criteria Evaluation (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:epw:ejeng0:v:3:y:2018:i:10:id:60937

DOI: 10.24018/ejeng.2018.3.10.937

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