About the Project

After completing my first GIS project examining wetland coverage across New Jersey, I wanted to take the analysis a step further by exploring the types of wetlands found throughout the state. New Jersey contains a wide variety of wetland environments, from freshwater forested wetlands to coastal salt marshes and estuarine habitats. I was interested in understanding how these environments vary geographically and which wetland types are most prevalent in each county.

Building on my previous project also gave me an opportunity to develop my GIS skills further by working with categorical data and performing more detailed spatial and statistical analyses.

Process

I created this map in ArcGIS Pro using wetland data from the U.S. Fish & Wildlife Service National Wetlands Inventory (NWI) and county boundary data from the New Jersey Office of GIS (NJGIN).

Using the spatial intersection dataset from my previous project, I calculated the total area occupied by each NWI wetland type within each county. I then used summary statistics and attribute joins to identify the wetland type covering the greatest total area in each of New Jersey's 21 counties.

Each county was assigned its dominant wetland classification and symbolized using a distinct color to illustrate geographic patterns across the state. I then created a map layout with county labels, a legend, and supporting information to communicate the results clearly.

What I Learned

This project helped me build on my existing ArcGIS Pro skills, particularly through the use of summary statistics, attribute joins, table selections, and categorical symbology. I gained a better understanding of how to organize and manipulate spatial data to answer more specific geographic questions.

The results were also interesting from an ecological perspective. Freshwater forested and shrub wetlands dominated most New Jersey counties, while estuarine and marine habitats were more prominent in certain coastal counties. One particularly surprising result was Passaic County, where lakes represented the largest mapped NWI habitat category.

I also gained a better understanding of the National Wetlands Inventory classification system, including its coverage of both wetlands and associated deepwater habitats. This highlighted the importance of understanding how a dataset defines and categorizes features when interpreting GIS results.