Project Summary Sheet

Study Title: South Florida Landscape Dynamics
Study Start Date: 2006   Study End Date: 2008
Web Sites: www.sofia.gov
Location (Subregions, Counties, Park or Refuge): Total System
Funding Source: USGS GE PES; USGS Land Remote Sensing Program
Principal Investigator(s): John W. Jones, Ph.D., Research Geographer, Eastern Geographic Science Center
Study Personnel: John W. Jones, Susan Price, and Gail Winters
Supporting Organizations: USGS
Associated / Linked Studies: SOFIA; High Accuracy Elevation; Everglades Depth Estimation Network (EDEN); POBS.

Overview & Objective(s): The primary goal of this study is to provide restoration-critical information regarding past and current characteristics of the Greater Everglades land surface (i.e., 'landscape dynamics') for improved landscape-scale modeling and restoration monitoring. The study develops innovative methods for geospatial data production and analysis of land surface characteristics over space and through time. The generated data provide baseline information necessary to begin monitoring the effects of restoration actions. Results of study landscape analyses facilitate more efficient and effective sampling strategies and improve field instrument placement. Structured study experiments increase our understanding of the relationships among surface features (e.g., vegetation and water) within the context of hydrologic, ecologic, and climate processes.

Status: FY06 work focused on high accuracy elevation database development, digital elevation model research and development, and temporal, moderate resolution satellite database calibration. These activities produced several products that are currently in operational use for EDEN and/or form the basis for FY07 research.

Recent Products:

• A single, region-wide geodatabase of high accuracy elevation data.
• Atlas/Data: The High Accuracy Elevation Data Electronic Atlas.
• EDEN DEMs versions 1 and 2.
• Open File Report: Initial Everglades Depth Estimation Network (EDEN) digital elevation model research and development.
• Reports: On the use of remote sensing to characterize Rocky Glade solution holes and EDEN development.

Planned Products:

• Journal publications on Solution hole refuge identification and characterization using remote sensing and Everglades Elevation Modeling.
• A synthetic digital elevation model for EDEN applications.

Specific Relevance to Identified Information Needs: [See DOI's Everglades Science Plan on SOFIA's Web site: http://sofia.usgs.gov/publications/reports/doi-science-plan/]:

Study data collection and analyses supports several projects including: (a) WCA 3 Decompartmentalization and sheetflow enhancement, (b) baseline studies and monitoring of plant community species composition, cover, and density in various project areas, and (c) Biscayne Bay Coastal Wetlands research to understand the links between hydrology and ecology. Data and change detection methods developed through this research can also contribute to fire management and invasive species detection/monitoring needs. This study responds to DOI science needs to improve the quantity, quality, timing, and distribution of water and provide landscape-scale science needed to support multiple CERP activities through the development of: (a) techniques and protocols for scaling, (b) well-calibrated data for biophysical analyses and monitoring, and (c) tools and information for vegetation, water, and habitat assessment and monitoring at regional scales. Study activities are often technique-development oriented, but are conducted with applications foci that meet specific information needs of the MAP. For example, solution hole mapping research is developing a needed performance measure (GE-A4) identified in the MAP (section 3.1.4.7). Similarly, study is directly responsive to trophic systems monitoring requirements (MAP Section 3.1.4.5) and is developing "hyperspectral systems as a cost-effective way of mapping Everglades landscape and water quality patterns". CESI restoration goals are also directly supported by developing synergistic use of in-situ and remotely sensed vegetation data.

Key Findings:

1. Solution hole refuges can be identified and characterized using airborne remote sensing data. However, both LIDAR and air photo data are needed. Imagery must also be collected during specific environmental conditions.
2. We have developed a conservative means of producing regional elevation models of the Everglades that yield root-mean-squared-errors below 12 cm for highly accurate points with-held from model development.