Eco-Location: Difference between revisions

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Client: Tim Wilkinson, [[World Conservation Monitoring Centre]] <tim.wilkinson@unep-wcmc.org>
Client: Tim Wilkinson, [[UNEP World Conservation Monitoring Centre]] <tim.wilkinson@unep-wcmc.org>


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Wildlife and critical ecosystems around the world include over 230,000 legal "protected areas", ranging in size from Coldham's Common in Cambridge https://protectedplanet.net/555561770 to the Serengeti https://protectedplanet.net/555570276. Many people from tourists to researchers and conservationists need to know about these, but there is no quick way to find out whether you are near one. If one is nearby, what can be found there? Barren scrubland or dense forest? Could a park manager see evidence of agriculture where there shouldn’t be, or a visiting scientist learn that the area has been flooded? Your task is to build a mobile application that enables the user to quickly orientate themselves with nearby protected areas, and deliver contextual data by accessing other services. You should specifically include data from the European Space Agencies Global Land Cover Layer to show the percentage of cover types within the protected area (e.g. 40% Mosaic vegetation, 60% Mosaic grassland), and you may include other information such as geolocated photos from Flickr, or species from the IUCN red list of threatened species.
 
Wildlife and critical ecosystems around the world are protected by over 230,000 legally recognised zones called protected areas. These protected areas range in size from local nature reserves such as at Coldhams Common https://protectedplanet.net/555561770 through to iconic national parks like the Serengeti https://protectedplanet.net/555570276.  
 
Many user groups need access to this data. Whether they are global extractives businesses looking to avoid environmentally sensitive areas when planning concession sites, academic researchers in the field wanting to know how a specific species interacts with the protected area network, or tourists looking for a local beauty spot.
 
Whilst these areas can be visualised geospatially on https://protectedplanet.net, there’s currently no quick way to discover your current proximity to nearby protected areas. Furthermore, the data is limited to technical information about the size and classification of the site. There is no information about what’s inside any given protected area. Is it barren scrubland or dense forrest? Is there evidence of agriculture where there shouldn’t be, or has the area been flooded? This extra level of information is extremely useful for conservationists (including park managers) to track the health of a protected area.
 
Your task is to build a mobile application that enables the user to quickly orientate themselves with nearby protected areas, and serve vital contextual data about those areas by accessing other services. You should specifically include data from the European Space Agencies Global Land Cover Layer to show the percentage of cover types within the protected area (e.g. 40% Mosaic vegetation, 60% Mosaic grassland), and you may include other information such as geolocated photos from Flickr, or species from the IUCN red list of threatened species.

Latest revision as of 13:57, 9 November 2016

Client: Tim Wilkinson, UNEP World Conservation Monitoring Centre <tim.wilkinson@unep-wcmc.org>

Wildlife and critical ecosystems around the world include over 230,000 legal "protected areas", ranging in size from Coldham's Common in Cambridge https://protectedplanet.net/555561770 to the Serengeti https://protectedplanet.net/555570276. Many people from tourists to researchers and conservationists need to know about these, but there is no quick way to find out whether you are near one. If one is nearby, what can be found there? Barren scrubland or dense forest? Could a park manager see evidence of agriculture where there shouldn’t be, or a visiting scientist learn that the area has been flooded? Your task is to build a mobile application that enables the user to quickly orientate themselves with nearby protected areas, and deliver contextual data by accessing other services. You should specifically include data from the European Space Agencies Global Land Cover Layer to show the percentage of cover types within the protected area (e.g. 40% Mosaic vegetation, 60% Mosaic grassland), and you may include other information such as geolocated photos from Flickr, or species from the IUCN red list of threatened species.

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