Satellite Remote Sensing of Submerged Aquatic Vegetation Distribution and Status in Currituck Sound

In coastal regions with extensive, non-linear water bodies, large scale regional macrophyte surveys are rarely done due to logistical difficulties and high costs. This study proposes to examine whether remote sensing can be used for regional monitoring of submerged aquatic vegetation (SAV) using a field study in the Currituck Sound of North Carolina. The objectives are: (1) to determine if different levels of macrophyte cover, different growth forms or specific species could be detected using the Digital Globe Quickbird, high-resolution satellite sensor, and (2) to determine if predictions of macrophyte abundance and distribution in the sound can be improved by including sediment type or measures of water clarity (Secchi disk transparency, total nitrogen, total phosphorus, or water color) in the models. Using binomial and multinomial logistic regression models, the project will develop statistically significant relationships between SAV measures and Quickbird spectral values using multinomial and binomial logit (logistical regression) models. Significant correlations between water quality characteristics and the Quickbird spectral values within pelagic zones of the sound will be used to adjust model predictions. Model validation will be developed using SAV and water quality data not included in the SAV abundance and distribution model. The research products from this study will provide a distribution map of SAV distribution and status within the Currituck Sound of North Carolina. North Carolina Department of Transportation (NCDOT) will use the model results of this study to assess impacts to SAV from proposed projects in an effort to determine appropriate avoidance, minimization, and compensatory mitigation alternatives. Additionally, models results will reduce permit processing time, and reduce the potential for unintentional violations. The model database that will be developed in this study will further serve as a baseline database, compiled in a global information systwm (GIS) format, which is easily updated as future data becomes available. New model scenarios will have the advantage of continually improved and updated data.

• Record URL:
  https://apps.dot.state.nc.us/Projects/Research/ProjectInfo.aspx?ID=2783

Language

• English

Project

• Status: Completed
• Funding: $238278.00
• Contract Numbers:

  2010-14

• Sponsor Organizations:

  North Carolina Department of Transportation

  Research and Development
  1549 Mail Service Center
  Raleigh, NC  United States  27699-1549
• Project Managers:

  Kirby, John

• Performing Organizations:

  North Carolina State University, Raleigh

  Marine, Earth and Atmospheric Science
  Campus Box 8208
  Raleigh, NC  United States  27695-8208
• Principal Investigators:

  Nelson, Stacy

• Start Date: 20090816
• Expected Completion Date: 0
• Actual Completion Date: 20111215
• Source Data: RiP Project 28934

Subject/Index Terms

• TRT Terms: Geographic information systems; Logits; Monitoring; Regression analysis; Remote sensing; Vegetation; Water quality
• Geographic Terms: North Carolina
• Subject Areas: Planning and Forecasting; I15: Environment;

Filing Info

• Accession Number: 01482609
• Record Type: Research project
• Source Agency: North Carolina Department of Transportation
• Contract Numbers: 2010-14
• Files: RIP, STATEDOT
• Created Date: May 30 2013 1:00AM