Project Work Plan
Department of Interior USGS GE PES
Fiscal Year 2012 Study Work Plan
Greater Everglades Landscape Dynamics
October 1, 2006
October 31, 2014
Principal Investigator(s): John W. Jones
Email Address: firstname.lastname@example.org
Phone: 703/648-5543 Fax: 703/648-4603
Mail address: 12201 Sunrise Valley Dr., Mail Stop 521, Reston, VA 20192
Principal Investigator(s): Brenda R. Gollaher
Email Address: email@example.com
Phone: 703/648-7456 Fax: 703/648-4603
Mail address: 12201 Sunrise Valley Dr., U.S. Geological Survey, Reston, VA 20192
Principal Investigator(s): David A. Kirtland
Email Address: firstname.lastname@example.org
Phone: 703/648-4712 Fax: 703/648-4603
Mail address: 12201 Sunrise Valley Dr., U.S. Geological Survey, Reston, VA 20192
Statement of Problem:
Land managers, decision-makers, and scientists must be able to monitor land surface change, track hydroperiods, estimate water level conditions in real time, and integrate physical and biological data/information from a broad user community in order to meet not only the goals of Everglades restoration and protection, but the science and management needs for wetland resources throughout the world. The primary goal of this task is to provide restoration-critical information regarding past and current characteristics of the Greater Everglades land surface (i.e., "landscape dynamics") using remote sensing and geospatial analysis to improve landscape-scale modeling and restoration monitoring. However, the techniques and understanding developed have impact beyond the Greater Everglades system. The study develops innovative methods for land surface and land cover data production and analysis. The generated data provide baseline information necessary to monitor and begin forecasting the effects of restoration actions on vegetation composition, hydrology, and fire ecology. Project landscape studies facilitate more efficient and effective sampling strategies, improve field instrument placement/data collection campaigns, and increase our understanding of the relationships among surface features (e.g., vegetation and water) within the context of hydrologic, ecologic, and climatic processes.
The vast Everglades environment presents extreme challenges for the collection of data on ground elevation, land cover, and vegetation structure. Nondestructive, efficient, cost-effective, and comprehensive detection of subtle and important changes in Everglades vegetation condition and composition over large areas requires well-calibrated satellite image data. Also, biologists and other scientists engaged in Everglades restoration and monitoring can save time and funding resources if they have adequate information on water level conditions in real time and hydroperiods for Everglades subregions.
Research is needed to understand which remote sensing data and associated processing techniques are capable of measuring important land cover changes and environmental processes in the Everglades. And the development and evaluation of methods for extracting information through the fusion an increasing variety of remote-sensed data types requires extensive research.
Finally, the Everglades Depth Estimation Network (EDEN) is a collaboratively developed database and set of applications tools that are useful in Everglades science operations planning, habitat modeling, and adaptive management. This project provides the expertise and research resources needed to produce the digital elevation model that is the foundation for this Network and is developing remote sensing based techniques to calibrate, evaluate, and refine gage-based water surface modeling.
This task has 3 objectives:
- Develop and refine innovative, widely applicable field data collection, remote sensing, and geographic analysis techniques to characterize spatial and temporal variations in land surface features and processes. This requires the exploration, development and implementation of effective satellite data calibration and atmospheric correction techniques for a variety of satellite and airborne image data types.
- Produce data and information that is useful for Everglades-focused science and restoration activities.
- Increase our understanding of the relationships among land surface spatial and temporal variation, hydrologic, and ecologic processes. Examples include the influence of vegetation structure on surface water fluxes and habitat responses to changes in hydrology.
This research is typically conducted through consultation and collaboration with scientists from other disciplines of the USGS, the National Park Service, the South Florida Water Management District, and other institutions such as the University of Florida, Florida International University, and Ohio State University. Operational and state-of-the-art remote sensing, geostatistical, and landscape ecology techniques are combined to develop, apply, and refine restoration-targeted information products on the distribution of elevation and vegetation characteristics as well as fire ecology and compare the information they provide to hydrologic, geologic, and biologic variables through space and over time.
Up to FY 2006, project efforts significantly contributed to hydrologic modeling aimed at informing Everglades Ecosystem Restoration (which were documented under the project titled “South Florida Landscape Dynamics”). Now, project-derived spatially distributed information on vegetation grouped by impact on flow resistance is routinely employed by 3 different hydrologic modeling groups. Since 2006 the project team has played a significant part in the development of an unprecedented real-time water level monitoring GIS (the Everglades Depth Estimation Network or EDEN) for use by all biological researchers in the Everglades. Project research iteratively produced a system-wide digital elevation model that is the foundation of water depth estimates. This elevation model has undergone 3 major revisions as additional input data become available and geostatistical modeling techniques have advanced. The research and processing approach have been documented for the international geospatial research and applications communities. In addition, project research has resulted in the development of techniques for monitoring critical ecosystem habitat (such as solution hole refugia) and hydrologically important land surface characteristics such as vegetation structural change given disturbance. For example, we have established statistical linkages among field-measured vegetation flow resistance/structural characteristics and satellite derived estimates of Leaf Area Index. As a result, collaborative development of spatially distributed fields of flow resistance are now underway. Finally, the project has established procedures and capabilities for generating Everglades InSAR data to estimate absolute water level and will be used for subsidence measurement in the Greater Everglades region.
Statement of Work:
A majority of project resources will be devoted this year toward the documentation of project results in professional presentations, journal articles and reports.
For example, the project PI has organized 3, 90-minute sessions at the INTECOL meeting to stimulate broader community discussion of remote sensing for wetland monitoring and process understanding. Some project results will be presented in those sessions while other project results will be presented in sessions that will attract nonremote sensing scientists and demonstrate how USGS Greater Everglades research is producing practical solutions for monitoring, protection and restoration of wetlands as well as important information for wetland science. The results presented will also be submitted in manuscript form to various journal outlets in the remote sensing, wetland and fire ecology fields.
Four general areas will be the research foci for 2012:
- Vegetation characterization for collaborative flow resistance research and modeling. Building on FY 2011 results from the comparison of field-collected vegetation structural information with indices derived from optical remotely sensed data (in collaboration with Harvey and others in WCA-3), we will use RADAR datasets assembled through the FY 2011 RADAR pilot study to investigate RADAR-based characterization of vegetation structure for monitoring and flow resistance modeling purposes. We will also broady demonstrate and publish our development of geospatial tools for wetland vegetation model parameterization and change monitoring.
- RADAR for absolute water level monitoring as well as subsidence and sea level rise research. In FY 2012 we apply developed capabilities and lessons learned regarding Everglades RADAR analysis to the modeling of land subsidence in areas of the Greater Everglades identified through discussions with Restoration Partners.
- LiDAR analysis and advanced digital elevation modeling. Increasingly available LiDAR data for the Greater Everglades region will be evaluated through comparison against USGS collected high-accuracy elevation and other data to assess their utility in wetland environments and document the strengths and weaknesses of DEMs derived from them.
- Fire Ecology–We will use methods developed for fire scar delineation, fire severity estimation, and fire recovery mapping in FY 2011 to generate time-series data on fire occurrence and severity in select areas of the Greater Everglades to establish burn probabilities that can be used in scenario/system flow forecasting.
Databases, Delivered: John W. Jones, 2009, A revised and expanded DEM for EDEN applications, USGS.
Databases, Delivered: John W. Jones, Annette Elmore, and others, 2009, Calibrated TM time series database for change detection in WCA-3 and other GEER regions, USGS.
Databases, Delivered: John W. Jones, 2011, An updated digital elevation model (DEM) and associated metadata for EDEN applications, USGS.
Databases, Delivered: John W. Jones and Annette Elmore, 2011, Sample fire scar and recovery maps from Landsat Data, USGS.
Databases, Planned: John W. Jones, 2012, A prototype high-resolution DEM for the Everglades National Park, USGS.
Databases, Planned: John W. Jones and Ohio State Collaborators, 2012, Multitemporal and multi-instrument RADAR dataset for WCA-3 (pilot study), USGS.
Journal or Periodical Article, Planned: Jones, John W., 2011, Remote sensing of vegetation pattern and condition to monitor changes in Everglades biogeochemistry, Critical Reviews in Environmental Science and Technology, 41(S1):64–91.
Journal or Periodical Article, Delivered: Zhixiao Xie, Zhongwei Liu, John W. Jones, Aaron L. Higer, and Pamela A. Telis, 2011, Landscape unit based digital elevation model development for the freshwater wetlands within the Arthur R. Marshall Loxahatchee National Wildlife Refuge, Geography, v. 31, p. 401–412.
Journal or Periodical Article, Delivered: John W. Jones, Gregory B. Desmond, Charles Henkle, and Robert Glover, 2011, An approach to regional wetland digital elevation model (DEM) using differential GPS and a custom-built helicopter based surveying system, International Journal of Remote Sensing, 33:2, 450–465.
Journal or Periodical Article, Planned: John W. Jones, 2012, Development of a synthetic DEM through data fusion, USGS.
Journal or Periodical Article, Planned: John W. Jones and Annette E. Hall, 2012, A proposal to use semivariogram analysis to index vegetation flow resistance in hydrodynamic modeling.
Journal or Periodical Article, Planned: John W. Jones and C.K. Shum, 2012, Absolute water level estimation through combined InSAR and RADAR Altimetry: Comparison with the EDEN Network, USGS.
Journal or Periodical Article, Planned: John W. Jones and Kathleen Skalak, 2012, Satellite based estimation of wetland leaf area index for modeling of vegetation flow resistance, Remote Sensing of the Environment.
Journal or Periodical Article, Planned: John W. Jones, Annette E. Elmore, and others, 2012, Semivariogram analysis for vegetation flow resistance-application in Everglades restoration research and modeling.
Journal or Periodical Article, Planned: John W. Jones, Annette E. Hall, Thomas J. Smith, Ann M. Foster, 2012, Tracking Everglades Fire Scar Vegetation Recovery through Archival Landsat Image Interpretation, Journal of Fire Ecology.
Journal or Periodical Article, Planned: Skalak, K., J. Harvey, J. Jones, L. Larson, G. Noe, N. Rybicki, 2012, Modeling and extrapolating wetland flow resistance from wetland plant community characteristics, Journal of Ecological Engineering.
Presentations, Delivered: K. Skalak, J.W. Harvey, L.G. Larsen, G.B. Noe, N. Rybicki, and J.W. Jones, 2010, Controls on vegetative flow resistance in wetlands and low-gradient floodplains: Abstract presented at the 2010 Fall Meeting AGU, San Francisco, California, 13–17 December.
Presentations, Delivered: John W. Jones, 2008, Leveraging highly accurate elevation, field, and remotely sensed image data to enhance digital elevation models for subregions of the Everglades: GEER 2008, USGS.
Presentations, Delivered: John W. Jones, 2008, Progress and prospects for monitoring landscape-scale patterns of Everglades vegetation from satellite and airborne imagery: GEER 2008, USGS.
Presentations, Delivered: John W. Jones, 2009, EGSC Remote Sensing Research: Examples from Everglades Restoration Science, USGS.
Presentations, Delivered: John W. Jones, 2009, USGS Applied Remote Sensing Science: Everglades Case Study, USGS.
Presentations, Delivered: John W. Jones and Annette Elmore, 2010, GEER presentation on GE PES Landscape Dynamics Research: USGS.
Presentations, Planned: C.K. Shum, Hyongki Lee, John W. Jones, Jinwoo Kim, and Zhong Lu, 2012, High-Resolution Wetland Water Level Monitoring Towards Everglades Restoration Integrating Synthetic Aperture RADAR Interferometry and Satellite RADAR Altimetry (INTECOL).
Presentations, Planned: John W. Jones, Annetee E. Hall, Thomas J. Smith, and Ann M. Foster, 2012, Tracking Everglades Fire Scar Vegetation Recovery through Archival Landsat Image Interpretation (INTECOL 2012).
Presentations, Planned: T.J. Smith III, A.M. Foster, G. Tiling-Range, and J.W. Jones, 2012, Fire, Water, Soil and Sea Level Influence the Position of Mangrove–Marsh Ecotones Through Time (INTECOL) USGS.
Report, Delivered: 2007, For products produced through related research prior to FY08, see: 2782-CAK task 2, "South Florida Landscape Dynamics", in the project titled "Landscape dynamics and environmental processes", USGS.
Report, Delivered: Hyongki Lee and C.K. Shum, 2011, Satellite data fusion to measure absolute water level changes in the Everglades for restoration monitoring and sea-level rise impact assessment: A pilot project, Ohio State University.
Workshops, Planned: John W. Jones (Organizer and Chair), 2012, Advanced remote sensing for improved wetland identification, monitoring, understanding and management: 3, 90-minute sessions (INTECOL 2012), USGS.