Mangrove Mapper

The Problem

Mangroves are one of the most threatened ecosystems on the planet. Globally, we have already lost 40% of all mangroves, with countries like India having lost more than 50% (WWF Intl) of their mangrove forests. Mangroves are biodiversity hotspots supporting 4107 recorded species (Kathisaran 2018) just in India. In Goa, it is estimated that with every hectare of mangrove forest cleared, there is a loss of 480kg (Dhargalkar et al.) of fish captured in nearby fisheries, indicating the central role of mangroves in the local environment as well as their significance for local livelihood and culture. Mangroves also provide flood protection and water filtration services. Further they are major sources of carbon sequestration both in the atmosphere as well as in oceans. Combined, mangroves have the highest area rates of carbon sequestration (Alongi 2012) among any ecosystem, terrestrial or marine. Destruction of mangroves released more than 220 million tonnes of CO2 between 2000-2015 in Africa and Brazil alone. Mangrove deforestation costs up to 42 billion dollars (UNEP) globally every year. Despite this, mangroves continue to be cut at rates 3-5 times higher than terrestrial forests every year.

Our Proposal

One reason for the continued degradation of our ecosystems is that the current economic system does not adequately account for ecosystem services, hence leaving them undervalued and vulnerable. There is a need to widely and uniformly measure ecosystem services, in order to incorporate them into public policy and market functions. We are helping fill this gap by creating an accurate and effective method of estimating carbon stock of mangrove forests by replacing the current time and labour intensive methods which have held back the large scale carbon estimation of mangroves. By using Unmanned Aerial Vehicles data collection and combining this data with satellite imagery and allometric equations, carbon stock estimation of mangroves can be scaled and made uniform. Further, we want to contribute to the body of existing data by calculating carbon stock for the entire Western coast of India. This would be invaluable data for policy and conservation in India. Further, it would allow us to cover enough area and mangrove species to develop formulae to be used by other conservationists and policy makers around the world. We want to use this time to develop a work flow, equations and codes so accessible that estimating carbon stock of mangroves around the world will just become a matter of plugging in a few details. This will help develop a system of uniform, accurate and accessible quantification of carbon sequestration of mangroves globally.

We Assume that...

We are assuming that anyone wishing to replicate our study will be able to access a UAV for their work.

We are assuming that the current amount of field based data on mangroves is adequate to develop our equations.

We are assuming that the availability of an open source, accessible method will generate help data on mangroves

We are assuming that availability of good quality data will help shape policy in the future.

Constraints to Overcome

Undervaluing ecosystem services is universal but more relevant for mangroves where calculating carbon stock is still complicated and more labour intensive. Field work with mangroves is harder to conduct in these wetlands and calculating below ground carbon stock of the species still involves destructive methods. This has prevented large scale estimation of carbon stock in mangrove forests which are not even included in the UN RED++ program. We want to change this by using unmanned Aerial Vehicles to replace field based surveys. This will create larger sample units of data and lend greater accuracy to the process which can then be extrapolated to satellite imagery for large scale estimation. This would mean developing a uniform and effective method of calculating carbon stock of mangrove forests which would allow programs, policy and markets to better value and protect them.

Current Work

1. To collect aerial imagery of a sample area, starting with a mangrove forest in one Island in Goa. 2. To generate 3D models of the data collected. 3. To combine drone data and allometric equations to define regression equations for estimating carbon stock on the island. 4. To extrapolate this data on to satellite imagery and estimate carbon stock for the entire island. 5. Depending on funding, to repeat this process in other areas, covering other mangrove species. 6. To translate the equations into an accessible work flow as well as codes for open source GIS and Statistical software free and open to use.

Current Needs

1. Funds to travel and conduct field work. 2. Funding for time dedicated to develop this methodology 3. Funds for Collaboration with other members of a scientific community working on carbon stock estimation. 4. Collaboration for collaboration with possible other drone operators in order to cover larger areas. 5. Access to a community of end users once the product has been completed.