Inspiration

Mangroves play an important role for climate change mitigation by sequestering and storing significant amounts of carbon (Mcleod et al. 2011, Donato et al. 2011). Carbon from coastal ecosystem is called blue carbon. Blue carbon refers to the ability of coastal and marine ecosystems, i.e. mangroves, seagrasses, and salt marshes, in sequestering and storing carbon through their biomass (Howard et al. 2014, Donato et al. 2011).

Sadly, mangroves all over the world are degraded mostly due to anthropogenic activities, such as land conversion, logging, and coastal development (Global Forest Watch 2021). In order to project future mangrove conversions, there is a need to develop a historical map of mangrove condition, in order to manage it properly. Especially for Indonesia, projecting the future of mangroves in Indonesia is difficult because only a handful amount of data available. While the rise of blue carbon literature and projects has been extensive worldwide, Indonesia still suffers from the lack of consolidated data, making informed decision become difficult. Therefore, to support mangrove future projection, there is a need to develop a historical mangrove maps to support analysis and policy on changes in mangrove extent and associated carbon sequestrations and emissions.

There is also an increase in public participation in mangrove conservation. Community based or personal conservation projects have been carried out all over the world. The problem is how do you now your effort make an impact. While field surveys are expensive, satellite images can be obtained for free.

What it does

The first one is automatic mangrove detection with Mangrove Vegetation Index. The difference between the SWIR and green values for mangroves is relatively smaller than the difference observed in the same spectral regions of sparse to dense and very dense terrestrial vegetation. Very dense vegetation pixels commonly have high SWIR values, making it separable from the mangrove pixels. Carbon stock dataset from Soto-Navarro et al. (2020) were integrated so user can click anywhere on the area of interest to come up with carbon stock.

How we built it

This app was built using Google Earth Engine and Javascript.

Challenges we ran into

It took quite some time to code the formula in Google Earth Engine.

Accomplishments that we're proud of

Automatic mangrove detection seems to work quite well.

What we learned

App can be used to communicate research result to the general public.

What's next for Mangrove Explorer

It currently uses LANDSAT 8 but with little modification, the can also uses previous LANDSAT satellites for higher temporal coverage, and SENTINEL satellite for higher accuracy.

In the future, other vegetation indices and water indices can be used to better predict the condition of mangroves.

This app can also be modified for Disaster Response such as Flood Mapping or Landslide, or agricultural use, such as Crop Mapping.

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