1.1 Abstract

This project aims to develop a precision forecast model for land cover change at the Chesapeake Watershed. By leveraging high-resolution longitudinal land cover data provided by the Chesapeake Conservancy, the model will predict land cover conversions from pervious to impervious surfaces. This forecast will enable land use and environmental planners to identify where urban growth will occur, propose green infrastructure accordingly, and prioritize lands for protection. The model will be generalizable to the county level, incorporating only widely available inputs, thus allowing any municipality within the Chesapeake basin to replicate the analysis. This proof-of-concept project will demonstrate the utility of precision conservation in land protection and green infrastructure planning and provide a valuable tool for planners and policymakers across the region.

1.2 Background

The Chesapeake Bay watershed is an ecologically and economically significant resource, encompassing diverse ecosystems and supporting a multitude of industries, including agriculture, tourism, and fisheries. However, the region is facing increasing environmental challenges due to the combined effects of sea-level rise and land subsidence. As a result, the area has become the second-most vulnerable region in the nation to flooding and storm surge, only after New Orleans. Predicting land cover changes, particularly the conversion from pervious to impervious surfaces, is crucial in addressing these challenges and informing climate adaptation and mitigation planning.

Our project focuses on three distinct counties within the Chesapeake Bay watershed, representing varying development contexts. Portsmouth is the urban prototype characterized by its dense residential, commercial, and industrial areas. James City County exemplifies a suburban context, with a mix of rural, suburban, and urban development and a diverse landscape encompassing forests, wetlands, and historic sites. Lastly, Isle of Wight County represents the rural aspect, predominantly characterized by agriculture, forestry, and extensive natural habitats. By considering these diverse counties, we can develop a comprehensive and generalizable model to predict land cover changes across various regional development scenarios.

1.3 Motivation & Use Case

Building resilient communities is a top priority for the Hampton Roads Planning District Commission (HRPDC). To support this goal, the HRPDC has established a green infrastructure plan that seeks to identify and prioritize a network of valuable conservation lands. This plan aims to achieve multiple benefits, such as habitat protection, drinking water supply protection, stormwater management, and recreational opportunities.

A crucial component of this plan involves developing a model to forecast potential future growth and identify areas of the green infrastructure network that are most at risk for development. Our project aims to create a forecast that enables land use and environmental planners to pinpoint where urban growth is likely to occur, propose green infrastructure accordingly, and prioritize lands for protection.

This proof-of-concept project demonstrates the utility of precision conservation in land protection and green infrastructure planning, providing a valuable tool for planners and policymakers across the region. For example, Andrew, the head of the Green Infrastructure Team from Chesapeake Conservancy, and his team will use our web app to make informed decisions on which regions have the highest priority to receive funding.

2.1 Understanding Land Cover data

The Chesapeake Conservancy provided high-resolution land cover data for 2013/14 and 2017/18. This vast raster dataset boasts an impressive 1-meter accuracy, offering 900 times more detail than the commonly used 30-meter resolution National Land Cover Dataset. Such a level of detail is crucial for capturing subtle changes in land cover.

The land cover classification includes pervious surfaces such as tree canopies and shrubs, which allow water to infiltrate the ground. In contrast, impervious surfaces encompass categories like roads and structures that prevent water infiltration, leading to increased runoff and potential flooding issues. Even though water and wetland are often considered impervious surfaces, in this study, we classify them as pervious surfaces due to their dynamic nature, interaction with groundwater, floodplain connectivity, and the critical functions of wetlands in water storage and infiltration.