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ReliefWeb - Updates

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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: American Samoa, Australia, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cook Islands, Democratic People's Republic of Korea, Fiji, French Polynesia (France), Guam, India, Indonesia, Japan, Kiribati, Lao People's Democratic Republic (the), Malaysia, Maldives, Marshall Islands, Micronesia (Federated States of), Mongolia, Myanmar, Nauru, Nepal, New Caledonia (France), New Zealand, Niue (New Zealand), Norfolk Island (Australia), Northern Mariana Islands (The United States of America), Palau, Papua New Guinea, Philippines, Pitcairn Islands, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tuvalu, Vanuatu, Viet Nam, Wallis and Futuna (France), World

    Maximum Temperature

    Temperatures in the Asia-Pacific region can go very high with central India reaching 50oC or more. The Tibetan plateau rarely exceeds 20oC because of its high elevation.

    These temperatures are based on average highs over a period of approximately 50 years. Maximum temperatures in the region may therefore be from different months of the year and a temperature in any given location may exceed these maximums.

    The WORLDCLIM dataset consists of interpolated climate surface data on monthly precipitation and mean, minimum, and maximum temperature at a spatial resolution of 30 arc seconds (approximately 1km spatial resolution).

    Input data were gathered from a variety of sources and, where possible, restricted to records between 1950 and 2000.

    The data are described in: Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25: 1965-1978 which can be downloaded at http://www.worldclim.org/.


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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: American Samoa, Australia, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cook Islands, Democratic People's Republic of Korea, Fiji, French Polynesia (France), Guam, India, Indonesia, Japan, Kiribati, Lao People's Democratic Republic (the), Malaysia, Maldives, Marshall Islands, Micronesia (Federated States of), Mongolia, Myanmar, Nauru, Nepal, New Caledonia (France), New Zealand, Niue (New Zealand), Norfolk Island (Australia), Northern Mariana Islands (The United States of America), Palau, Papua New Guinea, Philippines, Pitcairn Islands, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu, Viet Nam, Wallis and Futuna (France), World

    The Human Footprint

    Human influence on the earth’s land surface is a global driver of ecological processes on the planet, en par with climatic trends, geological forces and astronomical variations. The Wildlife Conservation Society (WCS) and the Center for International Earth Science Information Network (CIESIN) at Columbia University joined together to systematically map and measure the human influence on the earth’s land surface today.

    The analysis indicates that 83 per cent of the earth's land surface is influenced directly by human beings, whether through human land uses, human access from roads, railways or major rivers, electrical infrastructure (indicated by lights detected at night), or direct occupancy by human beings at densities above 1 person per KM². The authours refer to the human influence on the land’s surface measure as the "Human Footprint.


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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: American Samoa, Australia, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cook Islands, Democratic People's Republic of Korea, Fiji, French Polynesia (France), Guam, India, Indonesia, Japan, Lao People's Democratic Republic (the), Malaysia, Maldives, Marshall Islands, Micronesia (Federated States of), Mongolia, Myanmar, Nauru, Nepal, New Caledonia (France), New Zealand, Niue (New Zealand), Norfolk Island (Australia), Northern Mariana Islands (The United States of America), Palau, Papua New Guinea, Philippines, Pitcairn Islands, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Vanuatu, Viet Nam, Wallis and Futuna (France), World

    Population Density

    Using an innovative approach with GIS and remote sensing, the Oak Ridge National Laboratory LandScanTM is the community standard for global population distribution. At approximately 1 km resolution LandScan is the finest resolution global population distribution data available and represents an ambient population (average over 24 hours).

    The LandScan algorithm uses spatial data,imagery analysis technologies and a multi-variable modeling approach to disaggregate census counts within an administrative boundary. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution models are tailored to match the data conditions and geographical nature of each individual country and region.

    Oak Ridge National Laboratory: http://web.ornl.gov/sci/landscan/


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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: American Samoa, Australia, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cook Islands, Democratic People's Republic of Korea, Fiji, French Polynesia (France), Guam, India, Indonesia, Japan, Kiribati, Lao People's Democratic Republic (the), Malaysia, Maldives, Marshall Islands, Micronesia (Federated States of), Mongolia, Myanmar, Nauru, Nepal, New Caledonia (France), New Zealand, Niue (New Zealand), Norfolk Island (Australia), Northern Mariana Islands (The United States of America), Palau, Papua New Guinea, Philippines, Pitcairn Islands, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu, Viet Nam, Wallis and Futuna (France), World

    Köppen-Geiger Climate Classification

    The highly referenced climate classification map of Wladimir Köppen was published for the first time in 1900 and updated in its latest version by Rudolf Geiger in 1961.

    Climate classification is applied to a broad range of topics in climate and climate change research as well as in physical geography, hydrology, agriculture, biology and educational aspects.

    Based on recent data from the Climatic Research Unit (CRU) of the University of East Anglia and the Global Precipitation Climatology Centre (GPCC) at the German Weather Service, this map presents a new digital Köppen-Geiger world map on climate classification for the second half of the 20th century.


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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: Afghanistan, Bangladesh, Bhutan, Cambodia, China, Fiji, Georgia, India, Indonesia, Kazakhstan, Kyrgyzstan, Malaysia, Philippines, Singapore, Thailand, World


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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: Afghanistan, Australia, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Democratic People's Republic of Korea, Fiji, India, Indonesia, Japan, Kiribati, Lao People's Democratic Republic (the), Malaysia, Maldives, Marshall Islands, Micronesia (Federated States of), Mongolia, Myanmar, Nauru, Nepal, New Zealand, Pakistan, Palau, Papua New Guinea, Philippines, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu, Viet Nam, World

    WHY A REGIONAL FOCUS MODEL?

    A key challenge faced by humanitarian agencies is how to ensure that limited available resources are allocated where they are most needed and are efficiently delivered in a principled manner. Decisions to allocate resources must strike a balance between meeting the immediate needs of crisis affected communities and supporting efforts to strengthen resilience and response preparedness to future emergencies.

    To support humanitarian partners address some of these challenges, the OCHA Regional Office for Asia and the Pacific (ROAP) produces the Regional Focus Model (RFM) similar to previous analyses in 2015 and 2016, the model is based on INFORM (http://www.inform-index.org/), a global risk index that identifies and analyze where crises requiring international assistance may occur. It can be used to support decisions about disaster risk reduction, emergency preparedness and response.

    The model identifies hazard-prone countries that combine high vulnerability to hazards and low capacity to respond and are therefore more likely to accept or request support from the international community. The model also includes a "Humanitarian" component reflecting issues more directly related to OCHA's coordination work. It is designed to be a practical tool to inform and guide disaster managers. The tool is also used by OCHA to guide its regional strategic framework and annual work plan.

    In 2017, the RFM covers analysis of 38 countries in the Asia-Pacific region under ROAP in Bangkok, Thailand and Office of the Pacific in Suva, Fiji.


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    Source: UN Office for the Coordination of Humanitarian Affairs
    Country: Afghanistan, Australia, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Democratic People's Republic of Korea, Fiji, India, Indonesia, Japan, Kiribati, Lao People's Democratic Republic (the), Malaysia, Maldives, Micronesia (Federated States of), Mongolia, Myanmar, Nepal, Pakistan, Palau, Papua New Guinea, Philippines, Republic of Korea, Samoa, Singapore, Solomon Islands, Sri Lanka, Thailand, Timor-Leste, Tonga, Tuvalu, Vanuatu, Viet Nam, World


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