Sailesh Samanta¹, Sammy S. Aiau²

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¹ Department of Surveying and Land Studies, PNG University of Technology, Lae, Papua New Guinea.
² Department of Electrical and Communications Engineering, PNG University of Technology, Lae, Papua New Guinea.
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Abstract: Electrification and sustainable energy uses are increasing in Papua New Guinea (PNG) over the last few decades. The bulk of PNG’s population (85%) lives in isolated and dispersed villages in the rural areas. Most of these isolated and dispersed areas are still yet to be connected to an electricity supply. Papua New Guinea (PNG) is richly endowed with natural resources, but exploitation has been hampered by rugged terrain, land tenure issues, and the high cost of developing infrastructure. The study is focused on mapping of enriched renewable energy zones of the entire country. Different variables related to renewable, like surface albedo index, earth skin temperature, solar insolation incident, and wind speed are used for this purpose. Three interpolation approaches, like inverse distance weighted averaging, thin-plate smoothing splines, and kriging, are evaluated to interpolate all variables. Rating and weight sum overlay operation is applied to derive potential renewable energy zones in this equatorial country. Results show that potential renewable energy distribution is high in Papua New Guinea on the March and September equinoxes. Yearly average distribution of renewable energy source variables is significantly higher in most areas of Manus, New Ireland, North Solomon, West New Britain, Northern, Central and Milne Bay; a larger portion of East New Britain; the northern part of West and East Sepik, Central, Morobe and eastern part of Madang province. The potential renewable energy distribution data can help to establish sustainable energy production in the country.

Keywords: GIS, Spatial Interpolation, Spatial Analysis, Renewable Energy and Mapping

Cite this paper: Samanta, S. and Aiau, S. (2015) Spatial Analysis of Renewable Energy in Papua New Guinea through Remote Sensing and GIS. International Journal of Geosciences, 6, 853-862. doi: 10.4236/ijg.2015.68069.

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