MangMap: a new platform for mangrove mapping and monitoring using Earth Observation data
Résumé
Mangroves represent a vital natural heritage and our capacity to ensure their preservation is a key issue for fighting against global warming, preserving biodiversity and ensuring the way of life and subsistence of the increasing human population concentrated along the coasts. Over the last half century, however, mangroves have suffered an alarming loss of global cover. In order to improve the understanding of the
dynamics and functioning of mangroves, up to date and recurrent mangrove mapping and monitoring tools are crucial assets. MangMap, a new online platform based on Sentinel-2 time series starting in 2018, renewed every 5 days, offers a complementary approach to existing tools. The platform provides an interactive dashboard dedicated to the production of enduser driven products useful to mangrove monitoring at local scales. Each image transformed in reflectance levels (2A) is available for downloading
along with 11 automatically processed spectral indexes characterising mangrove environments. An automated vector contour of mangrove spatial distribution is calculated every quarter. Temporal composites of all indexes are processed monthly, quarterly, semesterly and yearly. Endusers can browse and import all data sets with simple tools. They can set specific on-demand analysis inside their own areas of interested, uploaded to the platform or drawn over the products on screen, for a chosen period of time: indicator of mangroves spatial evolution; calculation of index differences; statistics on index evolutions. The platform gathers 16 pilot sites spread over South America, Africa, Asia and Oceania regions. MangMap was designed to sustain and document scientific studies as well as to help institutional actors and stakeholders invested in the preservation and management of mangroves. Further up-grades in preparation with first users will seek to enhance enduser experience and to offer new Earth Observation products and services based on very high spatial resolution imagery and radar data time series.