Discipline: Ecology Environmental and Earth Sciences
Subcategory: Geosciences and Earth Sciences
Usaama Van - City College of New York
Co-Author(s): Brian Lamb, City College of New York, NY
Wetlands are biologically diverse ecosystems that provide a number of ecosystems services. These ecosystem services include flood protection, erosion prevention, and carbon sequestration. Because wetlands contain abundant plant life that is not easily broken in saturated (anoxic) conditions, carbon builds up in wetland soils, meaning that wetlands often act as carbon sinks. In tidal wetlands, the carbon built up in these wetland soils is transported as dissolved organic carbon (DOC) to connected aquatic systems through tidal motion. The goal of this project is to use remotely sensed data and in-situ measurements to understand carbon fluxes between tidal wetlands and connected aquatic systems. Our study site is in the Kirkpatrick Marsh and the adjacent Rhode River estuary, situated on the northwestern shore of the Chesapeake Bay. We have obtained satellite earth images from the Operational Land Imager (OLI) sensor aboard the Landsat 8 satellite through the USGS Earth Explorer online interface. Landsat imagery is then processed using various spatial analysis tools to calculate for vegetation indices such as Normalized Difference Vegetation Index (NDVI), Triangular Vegetation Index (TVI), and Green Normalized Difference Vegetation Index (GNDVI). We seek to use these indices to characterize vegetation on the marsh and determine if there are linkages between carbon cycling processes on the marsh and within the estuary. We are also using water quality indices derived from Landsat satellite imagery such as the Red/Green index to compare to in-situ water samples in the Rhode River. A YSI EXO2 sensor sits at the marsh-estuary interface and continuously measures water parameters such as turbidity, depth, fDOM (Fluorescent Dissolved Organic Matter (fDOM) refers to the fraction of CDOM (Colored Dissolved Organic Matter) that fluoresces) and chlorophyll-A. We are attempting to understand if the marsh vegetation indices, water quality indices (remote sensing), and in-situ measurements of water quality are related to one another. Initially using uncalibrated digital number data, we found a good comparison between remotely sensed NDVI data and in-situ fDOM data with an R-value of 0.93. Now, we would like to do the same comparisons using scientific physical quantities such as T.O.A radiance and reflectance values to see how the correlation changes as we have more precise data. Understanding the processes affecting carbon cycling within wetlands is pivotal to knowing how to manage them in the future.
Funder Acknowledgement(s): National Science Foundation Research Experience for Undergraduates Grant # 1560050; NOAA-CREST at City College of New York.
Faculty Advisor: Brian Lamb, firstname.lastname@example.org
Role: I started off by reading published research pertaining to the project to develop a methodology. Next step involved downloading Landsat 8 images from USGS Earth Explorer. Later, I developed python codes for stacking landsat bands, computing vegetation and water indices. In GIS, I extracted pixels over the designated are and converted those to excel files. I handed this data to my colleagues who used python to plot graphs and get some correlation between parameters of interest.