World Heritage Analyses is an online platform for work-in-progress GIS and remote sensing-based data products, analyses, and tools
Developed by IUCN, its aim is to present the latest spatial data, science and technology on natural World Heritage, and to provide a better mechanism for engaging users by delivering useful information digitally.
The initiative operates under IUCN’s Brighter Outlook for World Heritage project, which seeks to provide knowledge on natural World Heritage sites and trigger action to improve their conservation prospects, including through GIS and remote sensing tools.
A key attribute of the initiative is to apply results of existing global research to the World Heritage context and generate new insights. Amongst its many aims, the platform hopes to utilise the web as the preferred form of communication and deliver data, information and knowledge in a digital format, thus improving accessibility to people working in World Heritage conservation. In doing so, it is hoped that further development and refinement will be guided by user feedback in order to better suit their needs.
At the moment, IUCN’s World Heritage Analyses online platform includes the following set of initial products, analyses and tools:
- Near real-time satellite images (Landsat 8) for all natural World Heritage sites, powered by Esri’s Landsat Image Service, which allows for the use of petabytes of satellite data
- Surface water change analysis, based on the Google Earth Engine, a cloud computing service
- Interactive data visualisations for land cover change
- Online natural World Heritage information sheets
- Geospatial comparative analysis for identifying biogeographic representation
- Global forest loss, human footprint in natural World Heritage sites
The data products, analyses and tools presented on the platform are currently in the prototype phase, and should be seen as a set of proof-of-concept outputs, rather than final, sufficiently reviewed knowledge products. By putting these products in the public domain, we hope to generate user feedback to understand how these could be improved and refined in the future.
