The Day After Tomorrow, Where Will the Mangroves Be?

EarthzineDevelop Summer 2017, DEVELOP Virtual Poster Session

This article is a part of the NASA DEVELOP’s Summer 2017 Virtual Poster Session. For more articles like these, click here

Project Team: Eastern India Ecological Forecasting III

Team Location: University of Georgia ‰- Athens, Georgia

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Authors: Abhishek Kumar, Isabel Miranda, Maria Luisa Escobar Pardo, Taufiq Rashid, Shanti Shrestha

Mentors/Advisors: Dr. Deepak Mishra (University of Georgia, Department of Geography)

Past or Other Contributors: Roger Bledsoe, Christopher Cameron, Subash Dahal, Caren Remillard, MarÌ_a JosÌc Rivera Araya, Jessica Staley, Austin Stone, Patricia Stupp

Classification map of Bhitarkanika Wildlife Sanctuary (left) and corresponding Leaf Area Index, Gross Primary Productivity, and Leaf Chlorophyll content derived from Landsat 8 OLI (March 2017). Image Credit: Eastern India Ecological Forecasting III Team


Across the globe, mangroves play a major role in coastal ecosystem processes mitigating erosion and serving as barriers against storm surges. India holds approximately 5 percent of the world’s mangroves, over half of which are along its east coast. Situated in the state of Odisha, Chilika Lagoon and Bhitarkanika Wildlife Sanctuary sustain mangrove sites of local importance in need of effective management. This study demonstrated the use of Terra, Landsat, and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove health for both sites. Several indices including Normalized Difference Vegetation Index and Enhanced Vegetation Index, were examined to develop biophysical prediction tools and derive a 17-year time-series (2000 to 2016) of leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). Parallel to this assessment, a long-term (2000 to 2016) analysis of meteorological factors such as precipitation and temperature was completed to determine an association between these parameters. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity. A historical analysis of land cover maps was produced using Landsat 5 and 8 data to determine decadal changes in mangrove area estimates between 1995 and 2017. This analysis was used to predict land use-land cover change or fragmentation of Bhitarkanika mangroves. Based on Intergovernmental Panel on Climate Change (IPCC) data availability, the soft prediction map for 2050 showed the probability of mangrove risk to disturbance in the eastern part of Bhitarkanika. This study revealed the advantages of using a multi-sensor approach to monitor mangrove health and inform monitoring protocols.

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