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NOAA’s COASTAL SERVICES CENTER INTEGRATED OCEAN OBSERVING SYSTEM Proposal Type: Regional Coastal Ocean Observation Coordination project for the CSC Director’s Office Program Title: Remote Sensing Coastal Ocean Observing System (RSCOOS): A Synoptic Remote Sensing Cooperative System serving the Caribbean and the East Coast of the United States Co-Investigators: Name Chuanmin Hu Frank Muller-Karger Edward Kearns Nan Walker Duration: Budget: Institution USF / IMaRS University of South Florida University of Miami Louisiana State University Telephone 727-553-3987 727-553-3335 305-361-4837 225-578-5331 03/01/2005 – 02/28/2008 (3 years) Email [email protected] [email protected] [email protected] [email protected] Project Summary This program proposes to develop a working prototype of a Remote Sensing Coastal Ocean Observing System (RSCOOS) which will foster a cooperative arrangement among 3 existing academic satellite downlink facilities to provide redundant near-realtime data access for the coastal IOOS community. The Regional Associations (RAs) of the planned Integrated Ocean Observing System (IOOS) – which include academic, federal and commercial partners – must engage the existing satellite remote sensing scientific research community which maintains significant infrastructure and capability for truly synoptic observation of the coastal waters of the Caribbean and the East Coast of the United States. This prototype activity links 3 such academic entities, the University of Miami, the University of South Florida, and Louisiana State University, in a co-operative effort. The goals of the proposed effort are to: - Collect repeated, synoptic observations from existing polar-orbiting and geostationary earth-observing satellites via a network of existing downlink facilities - Process and distribute in near-realtime (<2 hours after collection) multiple parameters required by the operational costal management, education, commercial, and research communities - Establish this proto-operational system as a redundant data collection and distribution network to support continuous operation in spite of hurricanes, power or network outages, etc. - Implement distributed data dissemination technology and shared processing capabilities among partners using tools such as OpenDAP and grid computing technology 1 Real-time applications will be served that require ocean color, sea surface temperature, and altimeter data. Among the platforms/sensors targeted for this effort are Terra/MODIS, Aqua/MODIS, and ERS-1. The proposed activity will provide critical quantitative information on coastal and oceanic waters of the Caribbean Sea, the U.S. East Coast, and the Gulf of Mexico. Techniques that are developed as part of this effort will be extendible to other satellite downlink facilities within the same regional scope, as well as portable to other RAs outside the region (e.g. U.S. West Coast). The proposed activity builds cooperative partnerships that will contribute timely and appropriate information to public mission agencies, in particular those of NOAA’s Coastal Services Center. 2 Background The United States coastline alone exceeds 19,900 km in length and defines an Exclusive Economic Zone (EEZ) that encompasses over 11 million square kilometers. The productive and diverse environments found along the U.S. coastline and throughout the Caribbean Sea are intimately tied to commerce, transportation, and recreation activities. However, the close proximity to ever-growing urban areas, to commercial agriculture interests, and exposure to sediment, nutrient or other pollutant discharges result in stress and pressures on coastal resources. Climate variability further complicates the situation. These issues present difficult challenges for stewards of the marine environment, to industry and researchers who currently have limited ways to assess conditions over these sensitive environments. Proper management of these vast areas is an important priority for local, State, Federal, and international organizations. New science-based management paradigms require accurate historical and real-time information to assess changes relative to baselines and to make decisions about the use of resources. A new infrastructure that supports this approach is emerging with the coastal module of the Integrated Ocean Observing System (IOOS). Regional Associations (RAs) of data providers and users have started to form, to contribute to and benefit from a national IOOS backbone planned by the OceanUS Office (http://www.ocean.us). Remote sensing is the best way to obtain synoptic routine, repeated, and concurrent coverage of several parameters considered critical to the IOOS. It also allows for interpretation of distributed and isolated point measurements by providing a spatial and temporal context for these in situ measurements. As various Regional Associations organize around the nation, it has become clear that the full engagement of the satellite remote sensing community is now required to properly achieve IOOS goals. The incorporation of satellite-products is a fundamental 3 element of the IOOS strategy developed under direction of the Oceans.US Office. However, assimilation of this element of the IOOS has lagged, primarily since these types of specialized activities are usually considered to be outside the realm of individual RAs and the responsibility of a Federal backbone. On a nationwide scale, the processing and distribution infrastructure, the continuity and concurrency of satellite missions, and even products and their support by NOAA and NASA historically have been taken for granted. The result of these attitudes has been lack of integration of remote sensing into the RAs, even at a time when the importance of local coastal phenomena and the timeliness of acquiring data for their assessment has been recognized. Many elements of the Federal backbone simply were not set up for real-time applications; for example, the Federal NASA Ocean Color Processing Group had a latency in obtaining any particular regional data granule from Aqua/MODIS that is 20 times longer than that at a local downlink site (100 minutes versus 5 minutes). Over the past two decades, there have been significant advances in the development of remote sensing tools that afford the assessment of environmental parameters in oceanic and adjacent land areas. The academic research community has successfully demonstrated the applicability of such tools. Coastal managers and researchers need a way to integrate their local knowledge with the knowledge achieved by the research community on meteorological and oceanographic processes over synoptic scales. They need a mechanism that consolidates multiple and voluminous data streams, and a way to control the type of information they can derive from various datasets. Finding the proper role for remote sensing experts in addressing local problems has not been easy. The variety of algorithms, data archival and delivery mechanisms, diversity in data formats, lack of information about product quality, and a distinct separation between the research, management, commercial, and public education communities have slowed down 4 migration of key technologies across communities. Continuing attempts to provide low-quality high-level products generated by a centralized Federal process, and the lack of tools tailored for use of the data by the general public, has led to lack of consistency in quality and availability of high-level products, difficulty in providing feedback and in tailoring products, and difficulty in understanding and using the information. All too typically, the satellite images that are distributed by Federal agencies are used by managers and educators as "pretty pictures", and their value as data is not properly realized. The ultimate consequence is effective inhibition of the involvement of the people who are most directly familiar with natural processes in a region, and high-quality science and proper resource management are stymied. Several institutions located in the southeastern U.S. provide significant capability in terms of expertise and infrastructure for the collection, processing and archival of data from multiple Earth observation satellites. Specifically, real-time ocean color, infrared, and altimeter data from polar-orbiting satellites are collected at Louisiana State University’s Earth Scan Lab, the University of South Florida’s Institute for Marine Remote Sensing, and at the University of Miami’s Rosenstiel School for Marine and Atmospheric Science. LSU’s facility primarily collects infrared data from the GOES geostationary platforms, which provides high temporal resolution coverage for our coasts. The University of South Florida has an archive of high resolution infrared and ocean color data that spans back to 1978, manages over 1,000 Landsat and Ikonos images of the tropical coral reefs of the globe, serves these data via the OPeNDAP/DODS protocol, and is actively engaged in sensor development programs. The University of Miami archives all of the data collected by the MODIS sensors on the AQUA and TERRA satellites, collects the 4km AVHRR GAC data, and now has the capability to collect real-time MODIS, synthetic aperture radar and other high resolution imagery at its Center for 5 Southeastern Tropical Advanced Remote Sensing (CSTARS). Each of these institutions maintains an X-band downlink capability and is already capable of downloading data from the future operational satellites (i.e. the NPP/NPOESS series). These institutions represent a substantial data processing and archival capability as well, and all are capable of sustaining a rapid, real-time processing and distribution system. It is important to nurture this regional infrastructure to enable the necessary science and education processes required to support good management practices and a public stewardship ethic. Ultimately as an operational element of the IOOS, it is important that these institutions operate in a redundant and cooperative fashion, so that the flow of data is not compromised during the types of catastrophic events – e.g hurricanes making landfall, Figure 1 – during which the management community needs these data most urgently. Figure 1. A dual layer image of atmospheric pressure overlain upon MODIS color imagery received at USF. Note the large extent of Frances, which eventually impacted both St. Petersburg (USF) and Miami (UM). A third downlink site (e.g. LSU in Baton Rouge) would ensure continued realtime data access as Frances impacted the Florida coastal waters. Image courtesy of SEACOOS (www.seacoos.org). 6 Benefits This RSCOOS proposal seeks to coordinate existing satellite remote sensing infrastructure and products to serve the Caribbean and US East Coast in a redundant and distributed fashion. As such, the project serves ocean research, education, industry, and operations groups, and capitalizes on existing infrastructure already developed by NOAA’s Coastal Services Center, NOAA’s Harmful Algal Blooms Observing System (HABSOS), NASA, the Office of Naval Research, the research institutions, and the RAs such as SEACOOS and GCOOS. Other remote sensing infrastructure available at various research institutions and in the commercial sector eventually needs to be identified, linked, and coordinated, and this will be facilitated by the development of RSCOOS. The greatest benefits will be realized when this infrastructure is teamed up with the national public infrastructure that flies the satellites. Orchestrating this infrastructure will promote: - Critical redundancy required for 24/7 coverage of coastal zones in emergency situations - Synergy to maximize the processing power and information distribution infrastructure - Decentralization and outsourcing to increase efficiency and ensure high scientific quality - Effective linkage with regional COSEE and Sea Grant programs - Implementing a strategy for commercial providers of value-added products and users RSCOOS will contribute timely and appropriate information to public mission agencies, ensure a data stream to the RAs even during emergencies that incapacitate one or two of the systems, and provide a path to integration of the future operational satellites (NPP/NPOESS) into the IOOS. 7 Objectives The RSCOOS seeks to integrate satellite data (Table 1) into the information assessment and dissemination strategies already adopted by GCOOS, SEACOOS, and SCOOP. These include common data standards, OpenDAP data servers, WMS servers, and grid computing (e.g. globus). The main objectives of this project are to: - Collect repeated, synoptic observations from existing polar-orbiting and geostationary earth-observing satellites via a network of existing downlink facilities - Process and distribute in near-realtime (<30 minutes after collection) multiple parameters required by the operational costal management, education, commercial, and research communities - Establish this proto-operational system as a redundant data collection and distribution network to support continuous operation in spite of hurricanes, power or network outages, etc. - Implement distributed data dissemination technology and shared processing capabilities among partners using tools such as OpenDAP and grid computing technology - Link the prime regional remote sensing experts and the infrastructure they manage - Promote this expertise and infrastructure for inclusion into the RAs - Identify future needs for products and sensors for coastal applications. The successful development of RSCOOS will pave the way for commercial and educational applications and promote a dialog between the RAs and these important IOOS partners. 8 Table 1. Sensors to be integrated within the RSCOOS data processing and distribution systems. Moderate Resolution Imaging Spectrometer (MODIS Terra/morning pass and Aqua/afternoon pass): Sea Surface Temperature (1x1 km2 pixels; Infrared (IR)) Ocean Color (1x1 km2 pixels; 12 bits, bands 8-16; Visible) “Sharpening” bands: 250 x 250 m2 pix. (bands 1-2, Visible and Near-IR) 500 x 500 m2 pix. (bands 3-7, Visible and Near-IR) AVHRR (Advanced Very High Reolution Radiometer) estimates: Sea Surface Temperature A rough estimate of nearshore water transparency. GOES (Geostationary Orbiting Earth Satellite) Sea Surface Temperature TOPEX / Jason, ERS-1 (satellite altimeters): Sea Surface Height Estimates of wave height QuikSCAT / SeaWinds (satellite scatterometers): Wind speed and direction Estimates of wave height Approach This effort will use the collegial relationship established between ocean remote sensing experts in the region as the basis of its development. The partners will exploit their functional links with SEACOOS, GCOOS, SCOOP, the COSEE network, and industry to achieve its goals. The USF IMaRS collects and processes AVHRR, SeaWiFS, and MODIS data and generates ocean products within one half hour of each pass. LSU’s Earth Scan Lab has similar infrastructure and also collects and processes GOES IR data into SST images with one half hour or better temporal resolution. The UM RSMAS group archives the global ocean MODIS data to reprocess products and generate Climate Data Records (CDRs) as it is engaged in the calibration of these devices, and collects and processes direct-broadcast MODIS imagery within a half-hour at its CSTARS facility. In addition, experts in radar altimetry and scatterometry are closely linked with these groups. 9 Raw (L0) data collected at these sites will be processed to georeferenced L2 (swath) data in EOS-DIS compatible formats with their currently installed systems. Processing capabilities among the sites will be shared through the implementation of the Globus Toolkit which enables grid computing, which will primarily serve as a backup in case processing capability at any one center is compromised. L3 (mapped) products will also be produced and distributed. The multi-scale remote sensing products from sensors listed in Table 1 will assembled for dissemination in a distributed fashion. The interface developed at IMaRS for WMS image distribution, web-based raster data analysis, and the IMaRS capability to generate vector data from real-time NOAA NDBC and satellite scatterometer and altimeter data streams, will be leveraged. The enhanced RAs will then be able to offer combined satellite data, meteorological analyses, in situ time series, and numerical model results (as demonstrated by the experimental SEACOOS interface at http://nautilus.baruch.sc.edu/rs/ ) Multiple delivery mechanisms and forms will promote the use of the data collected. The USF IMaRS site presently delivers products not only in simple imagery format, as many others do (i.e. the “pretty picture” syndrome), but also as actual data. A prototype is presently implemented at http://imars.usf.edu to enable users to “measure” temperature and ocean color parameters at any given location, interactively and without knowing much about data formats or programming. The application is fully OPeNDAP/DODS compliant; reviewers are encouraged to test this simple tool. As part of the process of interacting with SEACOOS, GCOOS, SCOOP, etc., we will help define and adopt proper data exchange protocols, archive strategies, and web-based OGCcompliant GIS standards (e.g. WMS). Following the coordination among partner institutions, including sharing data stores seamlessly across the sites, we will implement the viewing and 10 analyzing of separate or fused data streams using graphs, images, or animations. It would allow users to render the environment at low (synoptic) resolution or at higher (local) resolution. Of particular benefit will be the ability to overlay other data (e.g. in situ data, hurricane trajectories) at the user’s local client machine. The customer interacts through platform-independent web browser technologies. SST data suffers from cloud contamination, especially for night-time passes. The pathfinder algorithm developed at UM/RSMAS has been used to generate global SST maps at 4-km resolution. We propose to transport such an algorithm to process real-time AVHRR and MODIS data, from which more reliable retrievals can be obtained and distributed. Product delivery strategy We seek to develop an efficient distribution system that delivers the right product, to the right customer, at the right time. To accomplish this task, the applications will use several existing tools, outlined below. In addition to placing information in the GCMD, RSCOOS will build on our Virtual Ocean Distributed Oceanographic Data System (VO-DODS) implementation to migrate data directly to the SEACOOS and GCOOS servers. DODS, also known as OPeNDAP (Open source Project for a Network Data Access Protocol), is a software framework used for data networking (http://www.unidata.ucar.edu/packages/dods/). DODS provides tools for making local data accessible to remote locations, regardless of local storage format, and for transforming existing applications into DODS clients. DODS software is free and its use has grown 11 significantly among Federal entities over the past couple of years. The GrADS-DODS Server (GDS) is a stable, secure data server that provides Internet subsetting and analysis services. The project will further take particular advantage of the features of MapServer, an OpenSource development environment for building spatially enabled Internet applications which is fully compatible with ESRI’s ArcIMS. MapServer will provide the framework to publish on the web series of remote sensing maps. We have an ongoing relationship with MapServer developers intended to lead to full raster display and data retention capabilities as a result of our interest to serve satellite products via the RAs. The MapServer maps will be augmented with hyperlinks to the archived and real-time data for each of the sampling locations visible on the maps. Similarly, the images will be presented with overlays of animated vectors for winds and currents, and animated bar graphs for ecological indices, using shape-files presently being generated at IMaRS. Data and Information Policy Our objective is to make the data public as quickly as possible, at least within 2 hours of data acquisition. We believe that our data should be openly shared. Data will be posted immediately upon completion of processing and quality control procedures, and will be shared freely. We encourage scientific parties using the proposed applications to consider joint analysis efforts with those members of the RSCOOS team responsible for the observations of interest. 12 Program Management Plan To ensure that the program objectives are met USF has assembled an experienced management team (F. Muller-Karger, and C. Hu). Frank Muller-Karger, founder of the Institute for Marine Remote Sensing within USF, will lead the Project Team. Muller-Karger has extensive experience in managing multi-institutional oceanographic programs and interacting with large groups of PI's. Specifically, Muller-Karger has served as leader of the multidisciplinary oceanographic time series (NSF CARIACO) with funding of ~$1.2M per year. He served as Program Scientist (Program Manager) for the Ocean Biogeochemistry Program at NASA Headquarters between 1992 and 1994. Muller-Karger has further participated in several large multi-PI teams, including the SeaWiFS Science Team, the NASA SIMBIOS Team, and the Landsat Science Team, among others. He serves on the U.S. Commission on Ocean Policy by appointment of President G. W. Bush. C. Hu has extensive experience both in field data collection, developing and implementing satellite data processing software schemes, and in the scientific analysis and interpretation of results obtained with a variety of sensors including Landsat, Ikonos, CZCS, SeaWiFS, MODIS over coastal and turbid aquatic environments. He has participated in many NASA and USGS funded projects using NASA EOS data to study coastal oceans, deltas, and river plumes. He has played a leading role in monitoring events on the West Florida Shelf. E. Kearns will lead the data management and IT development. He has extensive experience with the development of data standards, QA/QC protocols, and data transport methods through his involvement with the SEACOOS, SCOOP, and MODIS programs. He is part of the Miami team that had corrected, calibrated and validated the data from the MODIS instruments for the first 3 years of MODIS in-flight operation. 13 Major decision about scheduling, deadlines, composition of focus teams, assignment of overall tasks, and planning to ensure the timely, efficient, and competent accomplishment of all work for this project will be the responsibility of Frank Muller-Karger. However the project strategy will be guided through consultations of the management team. Milestone Schedule Within 30 days of award, we will prepare a project plan, an initial list of metrics and list of 6month milestones. This information and supporting data will be sent to the appropriate NOAA CSC official. An important aspect of the schedule will be to identify critical paths involving linked tasks that need to be completed simultaneously. During Year 1 we will define redundant data collection channels and processing schemes. All metadata and component data will be reported. Processing schema will be developed and compared to ensure compatibility among the partners. The activity builds on the Virtual Ocean Distributed Oceanographic Data System (OPeNDAP/DODS) project, funded by the National Oceanographic Partnership Program (NOPP), meets or exceed national standards (FGDC compliant), will conform to the objectives and requirements of the National Spatial Data Infrastructure (NSDI), is connected with the Global Change Master Directory (GCMD) and ensures accuracy and interoperability with the IOOS. During Year 2, similar data types will be cross-referenced, validated, and aggregated into like-products. Distributed processing (the grid) will be enabled to enable resource sharing among partners. Year 3 will be a period of transition 14 to operations, with an emphasis on robustness and QA/QC procedures. The team will publish results in the peer-reviewed literature. 15 16 Project Budget 17 References Andréfouët S. Kramer, P., Torres-Pulliza, D., Joyce, K. E., Hochberg, E. J., Garza-Perez, R., Mumby, P. J., Riegl, B., Yamano, H., White, W. H., Zubia, M., Brock, J. C., Phinn, S. R., & Muller-Karger, F. E. (2002a. In press.) Multi-sites evaluation of IKONOS data for classification of tropical coral reef environments. Remote Sensing of Environment. Special Ikonos issue. Andréfouët S., E. J. Hochberg, C. Payri, M.J. Atkinson, F.E. Muller-Karger, H. Ripley. 2002b (In press). Multi-scale remote sensing of microbial mats in atolls environment International Journal of Remote Sensing (Special issue: Remote Sensing of the Coastal Marine Environment). Andréfouët S., Robinson, J., Hu, C., Feldman, G., Salvat, B., Payri, C., FE Muller-Karger. 2002c (In press). Influence of the spatial resolution of SeaWiFS, Landsat 7, SPOT and International Space Station data on determination of landscape parameters of Pacific Ocean atolls. Canadian Journal of remote sensing. Special issue on "Synergistic Utilisation of Landsat 7". Andréfouet, S., P. J. Mumby, M. McField, C. Hu, F. E. Muller-Karger. 2002d. Revisiting coral reef connectivity. Coral Reefs. 21:43-48. Birkeland, C., Life and death of coral reefs, 536 pp., Chapman&Hall, New-York, 1997. Bontempi, P. S. and J. A. Yoder. Bio-optical water mass and phytoplankton feature definition by frontal edge detection algorithms in ocean color satellite imagery. SPIE Ocean Optics XV (CD-ROM), Musée Océanographique, Monaco, 16-20 October 2000. Boyer, J. N., J. W. Fourqurean, and R. D. Jones, R. D. Seasonal and long-term trends in the water quality of Florida Bay (1989-1997). Estuaries, 22(2B):417-430, 1999. Carder, K. L., Chen, F. R., Lee, Z. P., Hawes, S. K., and KamyKowski, D. (1999). Semianalytic moderate-resolution imaging spectrometer algorithms for chlorophyll a and absorption with Bio-optical domains based on nitrate depletion temperatures. J. Geophys. Res. 104:5403-5421. Costanza, R., R. d'Arge, R. deGroot, S. Farber, M. Grasso, B. Hannon, K. Limburg, S. Naeem, R.V. O'Neill, J. Paruelo, R.G. raskin, P. Sutton, and M. VanDenBelt, The value of the world's ecosystem services and natural capital. Nature, 387:253-260, 1997. EPA. A framework for an integrated and comprehensive monitoring plan for the estuaries of the Gulf of Mexico. Environmental Protection Agency, GMP Monitoring Subcommittee Report. EPA/620/R-00/006. 87 pp, 2000. Fourqurean, J. W., and M B. Robblee. Florida Bay: A history of recent ecological changes. Estuaries, 22:345-357, 1999. Hodgson, G. A global assessment of human effects on coral reefs. Marine Pollution Bulletin, 38:345-355, 1999. Hu, C., F. E. Muller-Karger, J. Taylor, D. Myhre, B. Murch, A. L. Odriozola, and G. Godoy, 2003a. MODIS detects oil spills in Lake Maracaibo, Venezuela. EOS AGU Trans. 84(33):313,319. Hu, C., F. E. Muller-Karger, D. C. Biggs, K. L. Carder, B. Nababan, D. Nadeau, and J. Vanderbloemen. 2003b. Comparison of ship and satellite bio-optical measurements on the continental margin of the NE Gulf of Mexico. Int. J. Remote Sens. 24:2597-2612. 18 Hu, C., K. E. Hackett, M. K. Callahan, S. Andréfouët, J. L. Wheaton, J. W. Porter, F. E. MullerKarger. 2003c. The 2002 ocean color anomaly in the Florida Bight : a cause of local coral reef decline? Geophys. Res. Lett. 30(3), 1151, doi:10.1029/2002GL016479. Jameson, J. W., J. W. McManus, and M. D. Spalding. State of the Reefs: Regional and Global Perspectives, U. S. Department of State, Washington, D.C., 1995. Kleypas, J. A. Modeled estimates of global reef habitat and carbonate production since the last glacial maximum. Paleoceanography, 12(4): 533-545, 1997. Liu, A. K., Y. Zhao, W. E. Esaias, J. W. Campbell, and T. S. Moore. Ocean surface layer drift revealed by satellite data. EOS, Transactions, AGU, 83(7):61-62,64, 12 February 2002. Ogden, J. C. Marine managers look upstream for connections, Science, 278:1414-1415, 1997. Palandro D, S. Andréfouët, P. Dustan, FE Muller-Karger. (In press, 2002). Change detection in coral reef communities using the Ikonos sensor and historic aerial photographs. Int. J. Remote Sensing. Palandro D., S. Andréfouët, FE Muller-Karger, P Dustan, C. Hu, P. Hallock (In press, 2002). Detection of changes in coral communities using Landsat 5/TM and Landsat 7/ETM+ data. Canadian Journal of Remote Sensing. Special issue on "Synergistic Utilisation of Landsat 7". Paulay, G. In Life and Death of Coral Reefs (Chapman and Hall, New York, 1997), pp. 298-353, 1997. Rabalais, N. N., R. E. Turner, D. Justic, Q. Dortch, W. J. Wiseman, Jr., and B. K. Sen Gupta. Nutrient changes in the Mississippi River and system responses on the adjacent continental shelf. Estuaries, 19:286-407, 1996. Rawlins, B. G., A. J. Ferguson, P. J. Chilton, R. S. Arthurtons, and J. G. Grees. Review of agricultural pollution in the Caribbean with particular emphasis on small island developing states. Marine Pollution Bulletin, 36(9):658-668, 1998. Rudnick, D. T., Z. Chen, D. L. Childers, J. N. Boyer, and T. D. Fontaine, III. Phosphorus and Nitrogen inputs to Florida Bay: The importance of the Everglades watershed. Estuaries, 22:398-416, 1999. Spinrad, R. 2002. Testimony before the U.S. Commission on Ocean Policy. 30 October 2002. (http://oceancommission.gov/meetings/oct30_02/oct30_02.html). Spalding, M. D., and A. M. Grenfell. New estimates of global and regional coral reef areas. Coral Reefs, 16:225-230, 1997. Southwest Florida Dark Water Observations Group (SWFDOG). Satellite images track "black water" event off Florida coast", EOS, Trans. AGU, 83(26):281,285, 25 June 2002. SWFDOG (2002). Satellite images track ‘black water’ event off Florida coast. EOS Trans. AGU 83:281, 285. Taylor, C. J. Parallelization and Load Balancing of the Simple, Scalable, Script-Based Science Processor (S4P) with a Dynamic Job Router. USF Honor’s College Thesis, 2002. Vermote, E. F., N. El. Saleous, C. O, Justice, Y. J. Kaufman, J. L. Privette, L. Remer, J. C. Roger, and D. Tanré (1997a). Atmospheric correction of visible to middle-infrared EOSMODIS data over land surfaces: Background, operational algorithm and validation. J. Geophys. Res. 102:17,131-17,141. Vermote, E. F., D. Tanré, J. L. Deuzé, M. Herman, and J-J Morcrette (1997b). Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: An Overview. IEEE Transactions on Geoscience and Remote Sensing, 35:675-686. Walsh, J. J. 1988. On the nature of continental shelves. Academic Press, San Diego. pp. 1-520. 19 Wilkinson, C., O. Linden, H. Cesar, G. Hodgson, J. Rubens, and A.E. Strong. Ecological and socioeconomic impacts of 1998 coral mortality in the Indian Ocean: an ENSO impact and a warning of future change? Ambio, 28(2):188-196, 1999. Zhang, H. Detecting red tides on the west Florida shelf by classification of SeaWiFS satellite imagery. USF Master’s Thesis, 2002. 20 Resumes Frank Muller-Karger Institute for Marine Remote Sensing (IMaRS), College of Marine Science, University of South Florida, 140 Seventh Avenue South, St. Petersburg, FL 33701; Phone: (727) 553-3335 and FAX: (727) 553-1103 / 1189; e-mail: [email protected] / http://imars.usf.edu Education: Ph.D. 1988 (UMD), MS in Management 2001 (USF), MS Biological Oceanography 1984 (UAK), BS Biological Oceanography 1979 (FIT). Professional: Commissioner, U.S. Commission on Ocean Policy (2001-present); Full Professor (tenured 1994): University of South Florida; 1994-present; Program Scientist, Ocean Biogeochemistry: NASA Headquarters, 1992-1994; Program Scientist, SeaWiFS, 1992-1994; Assistant Professor: University of South Florida, 1989-1994. Selected Publications (not a complete list): Muller-Karger, F. E., R. Varela, R. C. Thunell, M. I. Scranton, G. T. Taylor, Y. Astor, E. Tappa, M. A. Goñi, R. N. Sambrotto, H. Zhang, M. McIntyre, B. Marin, C. Hu, M. Iabichella, T.-Y. Ho, and R. H. Weisberg. (2003, in press). CARIACO: A Time Series of Primary Production and Vertical Export in the Cariaco Basin. In: JGOFS CMTT Synthesis. Muller-Karger, F. E., R. Varela, R. Thunell, Y. Astor, H. Zhang, and C. Hu. (In press, 2003). Processes of Coastal Upwelling and Carbon Flux in the Cariaco Basin. Deep-Sea Research II. Chuanmin Hu Institute for Marine Remote Sensing (IMaRS), College of Marine Science, University of South Florida, 140 Seventh Ave. South, St. Petersburg, FL 33701; Phone: (727)553-3987; Fax: (727)553-1103; Email: [email protected]; Internet: http://imars.usf.edu Education: Ph.D. Physics, 1997, UMiami. MS Physics 1992, Academia Sinica, BS Physics 1989, University of Sci. and Tech. of China Professional: Research Associate/Assistant Professor, IMaRS, USF/CMS (1998 – present); Research Assistant, UMiami, Physics Department (1993 – 1997) Selected Related Publications (not a complete list): Hu, C., F. E. Muller-Karger, J. Taylor, D. Myhre, B. Murch, A. L. Odriozola, and G. Godoy, 2003. MODIS detects oil spills in Lake Maracaibo, Venezuela. EOS AGU Trans. 84(33):313,319. Hu, C., K. E. Hackett, M. K. Callahan, S. Andréfouët, J. L. Wheaton, J. W. Porter, F. E. MullerKarger. 2003. The 2002 ocean color anomaly in the Florida Bight : a cause of local coral reef decline? Geophys. Res. Lett. 30(3), 1151, doi:10.1029/2002GL016479. The South West Florida Dark Water Observation Group (SWFDOG, Hu, C., and 26 others), 2002. Satellite images track 'black water' event off Florida coast. Eos. AGU Trans. 83(26):281,285. Hu, C., E. Montgomery, R. Schmitt, and F. E. Muller-Karger. The Amazon and Orinoco River plumes in the tropical Atlantic: Observation from space and S-Floats. Deep Sea Res.-II, in press (http://imars.usf.edu/~hu/river/amazon/Amazon_DSR_revision_Jul2003.doc) Hu, C., F. E. Muller-Karger, D. C. Biggs, K. L. Carder, B. Nababan, D. Nadeau, and J. Vanderbloemen. 2003. Comparison of ship and satellite bio-optical measurements on the continental margin of the NE Gulf of Mexico. Int. J. Remote Sens. 24:2597-2612. Hu, C., F. E. Muller-Karger, and R. G. Zepp. 2002. Absorbance, absorption coefficient, and apparent quantum yield: A comment on common ambiguity in the use of these optical concepts. Limnol. Oceanogr. 47:1261-1267. 21 22 Nan Walker College of Marine Science, University of South Florida, 140 Seventh Avenue South, St. Petersburg, FL 33701; (727)553-1631; (727)553-1189 FAX; [email protected] Ed Kearns College of Marine Science, University of South Florida, 140 Seventh Avenue South, St. Petersburg, FL 33701; (727)553-1631; (727)553-1189 FAX; [email protected] 23 LETTERS OF SUPPORT _______________________________________________________________________ From: [email protected] Date: Wed, 22 Oct 2003 13:53:33 -0500 To: [email protected] Subject: Letter of Support _______________________________________________________________________ To Whom It May Concern: The U.S. Environmental Protection Agency’s Gulf of Mexico Program has had the unique opportunity to work both directly and indirectly with the University of South Florida’s Institute for Marine Remote Sensing (IMaRS) on a number of highly successful efforts to providing science-based information and tools to coastal managers. As you are aware, we currently cooperate with IMaRS on a number of important projects involving the advanced development and deployment of the Harmful Algal Bloom Observing System (HABSOS). In recent months we have begun to expand the HABSOS pilot to include the six states of Mexico that border the Gulf. IMaRS will serve a critical role in supporting the technical capacity needed to carryout both the domestic as well as the binational structure of the HABSOS system. Integrating IMaRS’ remote sensing information with other HABSOS capabilities will ultimately lead to an improved ability to study, understand, monitor, and eventually forecast the coastal water quality conditions that are critical to the sustainable utilization of the Gulf. I therefore fully support this proposal to NOAA to develop a formal set of products, protocols, and interfaces to the various IOOS/COOS regional associations. Success in this work will result in essential improvements in our abilities to develop and deploy applications within these observing system structures. /s/ Bryon O. Griffith Acting Director Gulf of Mexico Program Office U.S. Environmental Protection Agency 2 Subject: Support for NOAA Coastal Ocean Remote Sensing Proposal From: "Kovach, Charles" <[email protected]> Date: Tue, 21 Oct 2003 11:58:00 -0400 To: <[email protected]> Subject: Support for NOAA Coastal Ocean Remote Sensing Proposal Dr. Muller-Karger, It is particularly timely to hear of your efforts to integrate remote sensing observations with regional observing systems. This communication is being sent to express our support and ability to participate in your continuing development of applications for resource management using remote sensing data, with a focus on estuarine and coral reef environments. As you are aware, we have been working here on developing regionally appropriate indices for various water quality parameters (e.g., chlorophyll, dissolved organic carbon, total suspended solids) in conjunction with our assessment of water quality in the State of Florida. This has been primarily through the use of airborne remote sensing. We are also currently working on a project with LANDSAT 7 imagery and ground truthing in Tampa Bay, including some collaborative efforts with USGS and local governments. We have also found great utility in using remotely sensed data for some permit-related monitoring and tracking the impacts of major meteorological and oceanographic events that affect the coast of Florida. Sincerely, Charles Kovach Florida Department of Environmental Protection, SWD Watershed Management, Env. Mngr. 3804 Coconut Palm Drive Tampa Florida 33619-1352 USA 813-744-6100 x329 740-3906 fax SC 512-1042 x329 514-1799 fax [email protected] 3 U.S. DEPARTMENT OF COMMERCE National Oceanic and Atmospheric Administration Atlantic Oceanographic and Meteorological Laboratory 4301 Rickenbacker Causeway Miami FL 33149 November 15, 2002 October 25, 2003 Dear Frank, Thank you for inviting me to collaborate with you in your NOAA Coastal Ocean Remote Sensing project. The kind of approach that you describe in your proposal is exactly what is needed to merge cutting edge science and coastal ocean resource management in a way that will aid in NOAA's mission of better stewardship of our coastal marine and estuarine environments. I am particularly excited about the possibility of incorporating real-time remotely-sensed ocean color and water quality observations into the South Florida Ecosystem Restoration program. I believe that this is a critical yet underutilized data source that will be of great value to the resource managers of the Florida Keys National Marine Sanctuary, the Tortugas Ecological Reserve, and Florida and Biscayne Bays. Towards your stated goals of establishing regional algorithms for estuarine systems to accurately estimate the optically-important constituents and to obtain reliable water quality indices, I would like to offer (at no additional cost to NOAA) any resources and/or data that you would find helpful. For example, in collaboration with my colleagues at AOML and the University of Miami, I conduct bimonthly interdisciplinary research cruises covering the region from the Caloosahatchee River to the Dry Tortugas to Miami, encompassing the Florida Keys. I also conduct monthly surveys of the shallow waters of Florida Bay and Biscayne Bay. In addition to our standard in-situ shipboard observations of temperature, salinity, dissolved oxygen, chl_a fluorescence, CDOM, turbidity, etc., we would be willing to add additional optical measurements during these cruises at your suggestion. We also maintain moored arrays in the vicinity of the river mouths of the southwest Florida shelf and on the Atlantic side of the Florida Keys. We deploy satellite-tracked surface drifters near the Shark River and in the Dry Tortugas regularly and provide their trajectories in real-time, and are in the process of converting some of our moorings to real-time communications as well. I would be happy to make these data available to you for ground-truthing of your satellite observations and for assisting in their interpretation. Finally, I look forward very much to working with you and your associates in the analysis of the combined remote sensing and in-situ data, and in the development of applications that will be welcomed and really put to use by resource managers of the South Florida coastal ocean ecosystems. Thank you for including me. Sincerely, Elizabeth Johns, Physical Oceanographer NOAA/AOML/PhOD