The North Pacific ACP (African, Caribbean and Pacific) Renewable Energy and Energy Efficiency Project (North-REP) is a unique project aimed at developing the energy sectors of the Federated States of Micronesia, The Republic of the Marshall Islands and Palau. These three SPC members have pooled the combined € 14,4 million from European Development Fund 10 resources and entrusted SPC to manage the project. This highlights the special partnership between a provider of technical assistance and services and its recipient member countries and territories. It also highlights the collaboration and vision in working together for the betterment of livelihoods in the north Pacific region. http://www.spc.int/edd/fr/section-01/energy-overview/energy/77-north-pacific-acp-renewable-energy-and-energy-efficiency-project-north-rep Copyright: SolarGIS © 2013 GeoModel Solar.

DNI Namibia (SolarGIS) Direct Normal Irradiation (c) 2012 GeoModel Solar http://solargis.info Annual Solar DNI Values. Units: kWh/m2/month Annual and monthly long-term average representing years 1994-2011.

Protected area of the EU and MENA regions.

Global Land Cover 2000 (GLC2000) Global Land Cover 2000 © 2003 European Communities Resolution: 0:00:32.142857 Values / definition 1 evergreen broadleaved forests 2 deciduous broadleaved forests, closed (> 40%) 3 deciduous broadleaved forests, open (15-40%) 4 evergreen needle-leaved forest 5 deciduous needle-leaved forest 6 mixed forest 7 evergreen broadleaved - swamp forest 8 evergreen broadleaved - mangrove forest 9 mosaic - tree cover dominant with other vegetation component (natural, crop component) 10 burnt tree cover 11 evergreen shrubland 12 deciduous shrubland 13 grassland 14 sparsely vegetated cover 15 wetlands 16 croplands 17 mosaic - cropland dominant / tree cover, other natural vegetation 18 mosaic - cropland dominant / shrub, grass cover 19 bare areas 20 water bodies 21 snow and ice 22 artificial surfaces and associated areas 23 cover unknown, no data

Global Land Cover 2000 (GLC2000) Global Land Cover 2000 © 2003 European Communities Resolution: 0:00:32.142857 Values / definition 1 evergreen broadleaved forests 2 deciduous broadleaved forests, closed (> 40%) 3 deciduous broadleaved forests, open (15-40%) 4 evergreen needle-leaved forest 5 deciduous needle-leaved forest 6 mixed forest 7 evergreen broadleaved - swamp forest 8 evergreen broadleaved - mangrove forest 9 mosaic - tree cover dominant with other vegetation component (natural, crop component) 10 burnt tree cover 11 evergreen shrubland 12 deciduous shrubland 13 grassland 14 sparsely vegetated cover 15 wetlands 16 croplands 17 mosaic - cropland dominant / tree cover, other natural vegetation 18 mosaic - cropland dominant / shrub, grass cover 19 bare areas 20 water bodies 21 snow and ice 22 artificial surfaces and associated areas 23 cover unknown, no data

Map does not include shallow Deep Enhanced Geothermal Systems (EGS) resources located near hydrothermal sites or USGS assessment of undiscovered hydrothermal resources. Source data for deep EGS includes temperature at depth from 3 to 10 km provided by Southern Methodist University Geothermal Laboratory (Blackwell & Richards, 2009) and analyses (for regions with temperatures ≥150°C) performed by NREL (2009). N/A regions have temperatures less than 150°C at 10 km depth and were not assessed for deep EGS potential. Temperature at depth data for deep EGS in Alaska and Hawaii not available. Qualitative classes are based on temperature and depth ranges. Temperature values are not exclusive to any single class and may be located at different depths from one class to the next. Classes express approximate favorability for geothermal resource, with a lower number indicating the possibility of a higher potential value.

Harmonised WFS Download service for Low Voltage Transformer. While all reasonable steps have been taken to ensure the accuracy, completeness and reliability of the information provided, Enemalta assumes no responsibility for any errors, inaccuracies or missing information. In no event shall Enemalta be liable for any direct, indirect, special or incidental damage resulting from, arising out of or in connection with the use of the information being provided.

The Business as Usual (BAU) scenario projects a future in which historical trends in yield levels and livestock productivity are continued, resulting in a low agricultural productivity. The progressive scenario assumes the implementation of improved agricultural management resulting in a high agricultural productivity. The land use changes for each year towards 2030 were modelled on high resolution by allocating land to a land use class based on the suitability for the specific land use classes. Areas that are not suitable (such as steep slopes) or not allowed (such as conservation areas) to be converted to agricultural land, were excluded. Based on the allocation of land use classes and the maps of excluded areas for bioenergy production (such as forest areas), the land availability for bioenergy crops is determined. Reference van der Hilst et al, 2012 and Verstegen et al 2012 Contacts Dr. F. van der Hilst, Copernicus Institute of Sustainable Development, Utrecht University, Section Energy & Resources.

The second version of Uruguay's Solar Map provides annual and monthly averages of daily global irradiation at an horizontal surface. A statistical satellite based model is used to obtain hourly solar irradiation from GOES-East's visible channel imagery. This hourly information is used to compute the monthly and annual averages using a 14 years' local database of satellite images. The coeficients of the statistical model are tunned using the data from the National Solar Measurements' Network administrated by the National Public University's Solar Energy Laboratory (LES/UdelaR, Uruguay). The network is equipped with first class field pyranometers according to ISO 9060:1990 (Kipp & Zonen CMP6 or higher quality). Pyranometers are regularly calibrated against a secondary standard Kipp & Zonen CMP22 that the Solar Energy Laboratory keeps calibrated against the primary standard in the World Radiation Center in Davos, Switzerland. For more information check the website: http://les.edu.uy. Resume of the metadata: Name: Uruguay's Solar Map Version 2.0. Component: Solar Global irradiation at an horizontal plane. Temporal resolution: annual and monthly averages of daily irradiation in kWh/m2. Spatial resolution: about 1 km. Origin: satellite irradiation data based on GOES-East imagery. Satellite Statistic: GOES-East images from 01/01/2000 to 31/13/2013. Credits: Laboratorio de Energía Solar, Universidad de la República, Uruguay (http://les.edu.uy). Citation and methodology: ALONSO SUÃREZ, R.; ABAL, G.; SIRI, R.; MUSÉ, P. Brightness-dependent Tarpley model for global solar radiation estimation using GOES satellite images: application to Uruguay. Solar Energy 86, pag. 3205-3215, 2012.

Elevation (SRTM-30) Shuttle Radar Topography Mission version 2 © 2000-2006 SRTM Mission SRTM30 plus © 2008 Joseph J. Becker, David T. Sandwell CleanTOPO2 © 2008 Tom Patterson Post-processing and cartography by GeoModel Solar Resolution: 00:00:30 Terrain maps show the elevation above sea level on the land and depth of the ocean and sea bottom. The slope inclination and azimuth are calculated on-the-fly. The map is developed from Shuttle Radar Topography Mission (SRTM) and SRTM Water Body Dataset (SWBD). The detailed SRTM3 data with grid resolution of 3 arcsec (~90 m at the equator) are available between the latitudes 60N and 50S, which represents the most of the continental parts of the Earth. For regions north from 60N and south from 50S, only the elevation data from GTOPO30 (SRTM30) are available. The original grid resolution of the GTOPO30 dataset is 30 arcsec (~1000 m at the equator). The bathymetry has been created from two different sources: SRTM30 plus dataset and CleanTOPO2 dataset, in which a few inconsitencies of SRTM30 plus are resolved. The fusion of these datasets has been done and the new map of bathymetry has been created. Terrain shading has been derived from GTOPO30 and SRTM-3 data.