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Project Summary Sheet

U.S. Geological Survey, Greater Everglades Priority Ecosystems Science (PES) Initiative

Fiscal Year 2004 Study Summary Report

Study Title: Land Characteristics from Remote Sensing
Study Start Date: 2000 Study End Date: 2005
Web Sites:
Location (Subregions, Counties, Park or Refuge): Total System
Funding Source: GE PES; USGS/BRD Park Oriented Biological Support Program
Principal Investigator(s): John W. Jones, Ph.D., Geographer, Eastern Region Geography
Study Personnel: John W. Jones, Susan Price, Jean-Claude Thomas, George Lemeshewsky, Robert Stevens, Gail Winters
Supporting Organizations: USGS
Associated / Linked Studies: TIME; SOFIA; High Accuracy Elevation; Metadata; Evapotranspiration

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.

Study research has established a sound foundation of data, hardware and software, methods, skills, and collaborative relationships needed to enable substantial progress in landscape-scale data production and analysis for science and restoration needs. Several study threads are nearing completion and FY05 will include foundational work to increase the contribution of Geographic Science to Everglades restoration.

Recent Products:
-Data: Big Cypress/Pine Island Image Map; TIME model-domain sub-grid vegetation; South Florida Spectral Library; Multi-temporal/Multi-resolution Image Database; Rocky Glades High Resolution (.16m) DOQ

-Fact sheet: South Florida Land Characterization (in review).

Planned Products:
- Procedures: regional vegetation density/leaf area index mapping; evapotranspiration estimates from satellite data.

-Factsheets: South Florida satellite image map series; Spectral library.

-Data: National Land Cover Database Land Cover south of Lake Okeechobee

-Reports/papers: Status and Trends Professional Paper; Solution hole mapping; Vegetation/topography.

Specific Relevance to Identified Information Needs
Study data collection and analyses at multiple scales (up to regional) 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 are also expected to contribute to fire management and invasive species detection/monitoring needs of DOI land managers. 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 Similarly, study periphyton research is directly responsive to trophic systems monitoring requirements (MAP Section as well as using "hyperspectral systems as a cost-effective way of mapping Everglades landscape and water quality patterns". CESI restoration goals are also directly supported by generated information on spatial and temporal plant community cover and density in the southern Everglades and stressing the synergistic use of in-situ and remotely-sensed vegetation data.

Key Findings:

  1. Relevant process-model information on vegetation can be derived from automated processing of satellite imagery.
  2. Information on vegetation composition at hydrodynamic model sub-grid scale improves model performance.
  3. Commonly available airborne image data are inadequate for delineating solution holes.

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