Half of all world mangroves have been lost over the past 50 years due to a variety of both anthropogenic and natural disturbances. To prevent these dieoffs from continuing, it is necessary to develop a system to monitor and predict regions under highest vulnerability from these various loss drivers.
EcoMap , Electronic Coastal Monitoring and Assessment Program, seeks to establish an interactive, user-friendly portal that can be used by stakeholders and coastal communities to map the world’s most vulnerable regions of mangroves, identify the proximity and urgency of various loss drivers, and provide real-time alerts about local mangrove health.
Our team member, Liza, has been working on this project with member Dr. Lagomasino. Their work has been presented at this year’s AGU conference and is gaining a lot of interest among our colleagues. Here is a link to her presentation.
* EcoMap Video Demo 2018
( Project Name Has recently changed. Updated video Demo coming soon)*
Summary of Activities to Date:
Landsat NDVI Anomalies
LANDSAT 5,7, and 8 imagery from calendar year 1984-2017 was used in developing NDVI anomalies for all mangrove regions on a global scale. In doing so, regions that have experienced mangrove gain, no mangrove change, and mangrove loss were identified.
Individual Risk Factor and Total Vulnerability Mapping
Erosion risk could be determined by evaluation of the extent of NDVI losses that have occurred in the past; no NDVI change signified no risk of erosion, NDVI loss from 0.3 to 0.1 signified a medium risk of erosion and a conversion to mudflat, and NDVI loss from 0.3 to <0 signified a high risk of erosion and a conversion to open water.
Evaluation of risk for a variety of other loss drivers, including agricultural expansion, urban expansion, and distance to rivers and the coast were also evaluated through first identifying the location of the specific land types that were the source of the mangrove vulnerability. NOAA VIIRS nightlights imagery was used in identifying the world’s most urbanized regions, and distance buffers were placed around the urban areas to create levels of risk. This method of applying distance buffers to various land types was also applied for agricultural areas, coastlines, and rivers.
Each risk factor was assigned a risk level on a vulnerability scale, and each of these risk levels were aggregated to equal a total risk estimate for future loss for all global mangrove regions.
Individual risk factor and total vulnerability maps were combined in the Google Earth Engine platform to allow users to examine various risk map layers, analyze risk at any point on the map, and plot NDVI changes from 1984 to 2017.
EcoMap is currently being transferred from using static data to using real-time data in its risk detection algorithms. Real-time alerts for local risk of mangrove loss may then be sent to coastal communities in order enable preventative action in the case of high vulnerability in a particular region.
Structural modeling using LIDAR, TanDEM-X, and SRTM data may also be incorporated into EcoMap ’s risk determination software in order to correlate any changes in mangrove structure or biomass with any observed NDVI changes. These correlations will allow for a more accurate representation of any degradation seen around the world.
In the future, we hope to establish a global network of mangrove monitoring in coastal communities, through equipping schools, decision-makers, and local citizens with the EcoMap software. By giving coastal communities access to the tools needed to detect and predict loss in local mangroves, mangrove resources allocation, policy, and restoration efforts can proceed in a more informed manner.