SIP, SOPs, and Salt Marshes: Edward Cascella’s Work Using Remote Sensing to Analyze Salt Marsh Vegetation

Wrapping up our year...

Highlighting the work of the Northeast Coastal and Barrier Network in FY24.

Salt marshes have been a key monitoring site for NCBN for several decades. Coastal salt marshes are a hub for biological diversity, and they perform a number of essential ecosystem processes, such as filtering nutrients. They are also a crucial and natural form of protection from coastal storms. However, the effects of climate change are causing rapid changes to salt marsh ecosystems within the Network, leading to critical habitat loss and other drastic environmental changes. While NCBN has monitored salt marsh vegetation in addition to tidal wetland elevation, the promises of remote sensing pose another opportunity for analyzing this vital sign of marsh health.

This summer, Scientists-in-the-Parks (SIP) intern Edward Cascella worked on expanding NCBN’s salt marsh monitoring to include using satellite imagery to track salt marsh composition changes. Through cooperating with the Southeast Coast I&M Network and researchers at the USGS Woods Hole Coastal and Marine Science Center, Cascella drafted two standard operating procedure (SOP) documents for using satellite imagery to monitor the vegetated and unvegetated areas within NCBN coastal marshes.

The crux of the analysis involves deriving the unvegetated/vegetated ratio, which relates the amount of unvegetated area to the amount of vegetated area within the area of interest in the marsh. Cascella created areas of interest for the parks and then downloaded National Agricultural Imagery Project (NAIP) imagery from USGS’s EarthExplorer to analyze change in the spatial extent of the saltmarshes. Cascella’s SOP also involves using topobathymetric digital elevation models (TDEMs) from the USGS’s Coastal National Elevation Database (CoNED). Cascella used the NAIP imagery and CoNED to run an unsupervised classification to determine vegetated and unvegetated land cover in the areas of interest. An unsupervised classification uses the spectral characteristics of each pixel in the input data to categorize them into distinct classes. Once the pixels are categorized, Cascella can run further analyses that compare vegetated area to the unvegetated area within the marsh unit. Repeating the procedure over a long period of time, such as five or ten years, will draw attention to trends in vegetation changes that will inform management decisions at each park.

Cascella’s work will extend into using satellite imagery to monitor changes in marsh edge. Although his SIP internship has ended, he is continuing work on the SOPs while completing his master’s degree in environmental science and management at the University of Rhode Island. His efforts have contributed to NCBN’s commitment to finding new and innovative approaches to monitoring that utilize advanced technology and cooperation across other networks and agencies to promote scientific excellence and integrity.