Chesapeake Bay Long-term High-Resolution Land Cover and Land Use Monitoring Program

Authors: Rachel Soobitsky*, Chesapeake Conservancy
Topics: Land Use and Land Cover Change, Geographic Information Science and Systems
Keywords: land cover, high-resolution data, Chesapeake Bay, conservation
Session Type: Paper
Day: 4/5/2019
Start / End Time: 1:10 PM / 2:50 PM
Room: Buchanan, Marriott, Mezzanine Level
Presentation File: No File Uploaded

The 2013 Chesapeake Bay High-Resolution Land Cover dataset classifies natural and human-made features on the landscape at a 1-meter resolution, providing 900 times the amount of information as the conventional 30-meter resolution land cover data. This allows users to practice “precision conservation”- getting projects the right size, in the right places, at the right scale, and making sure they are working. We are creating new high-resolution land cover and land use maps for the Chesapeake Bay watershed. This data will be used to describe land use and land cover change and inform best management practices to work towards the 2025 Total Maximum Daily Load (TMDL) goals. The TMDL is a pollution diet that was established in 2010 by the Environmental Protection Agency, with a goal to restore clean water in the Chesapeake Bay. The first step of this project is to update the 2013 High-Resolution Land Cover dataset for 2017/18. To do so, we use spectral and spatial characteristics from the most up-to-date National Agriculture Imagery Program (NAIP) aerial imagery, along with height values from the most available Light Detection and Ranging (LiDAR) data. Second, we perform a change detection analysis between the two datasets to analyze how land in the Chesapeake is evolving. Last, we execute a land use conversion from the land cover. These updated datasets will be helpful for local and state governments and organizations to better target and implement on-the-ground agricultural and conservation best management practices to meet TMDL goals and improve prioritization for precision conservation.

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