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_(Abstract):_ Project overview describing rationale, products and partners of the UNEP/GEF Solar and Wind Energy Resource Assessment project. _(Purpose):_ Project overview for presentation at the Asia regional meeting at the Second International Conference on Renewable Energy Technology for Rural Development (RETRUD-03) in Katmandu on 12-14 October 2003 ### License Info Please cite as follows Renn?, D. 2003, Overview of the United Nations Environment Programme's Solar and Wind Energy Resource Assessment (SWERA) Project, Second International Conference on Renewable Energy Technology for Rural Development. 12-14 October 2003. Dathmandu, Nepal. Available from http://swera.unep.net/ on 2 December 2003.

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Efficient Air Traffic Scenario Generation Project

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The Floodplain Mapping/Redelineation study deliverables depict and quantify the flood risks for the study area. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The Floodplain Mapping/Redelineation flood risk boundaries are derived from the engineering information Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA).

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BPI Zones are derived from a focal mean analysis on bathymetry and slope. The grid is based on gridded (5 m cell size) multibeam bathymetry, collected aboard NOAA Ship Hi'ialakai and R/V AHI, and it was creating using the Benthic Terrain Modeler (http://www.csc.noaa.gov/products/btm/). Cell values represent one of 4 classes in an index of seafloor terrains. This data set is for the shelf and slope environments of Tutuila Island, American Samoa, South Pacific.

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The Side-Looking Airborne Radar (SLAR) is an image-producing system that derives its name from the fact that the radar beam is transmitted from the side of the aircraft during data acquisition SLAR is an active sensor; the system provides its own source of illumination in the form of microwave energy. Consequently, imagery can be obtained either day or night. Since microwave energy penetrates most clouds, SLAR can be used to prepare image maps of cloud-covered areas. Data are X-band synthetic aperture radar (horizontally transmitted, horizontally received) with the exception of some test sites. Since the radar signal is transmitted at a depressional angle below the horizontal plane in which the aircraft is flying, the signal strikes the terrain at an oblique angle, and the surficial expression of the geologic structure may thus be enhanced. The topographic expression of some surface features, such as subtle faults and folds, may be more clearly seen on radar imagery than on conventional aerial photographs or satellite images.

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The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual- chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the Universal Transverse Mercator Zone 18 North. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:12,000. Coastal study data as defined in FEMA Gudelines and Specifications, Appendix D: Guidance for Coastal Flooding Analyses and Mapping, submitted as a result of a coastal study. Appendix D notes that a variety of analytical methodologies may be used to establish Base (1-percent-annual-chance) Flood Elevations (BFEs) and floodplains throughout coastal areas of the United States. Appendix D itemizes references for the methodologies currently in use by FEMA for specific coastal flood hazards, provides general guidance for documentation of a coastal flood hazard analysis, specifies flood hazard analysis procedures for the Great Lakes coasts, and outlines intermediate data submissions for coastal flood hazard analyses with new storm surge modeling and revised stillwater flood level (SWFL). (Source: FEMA Guidelines and Specs, Appendix D Guidance for Coastal Flooding Analyses and Mapping, Section D.1)

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Mean annual revenue for commercial fisheries during the period of 2007-2012. Each cell represents U.S. dollars.

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Onemetersquare 1 meter x 1 meter benthic substrate at Baker Island, site 5P 00 11.781N, 176 29.176W, between 5 and 6 meters along a permanent transect.

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Mean annual revenue for commercial fisheries during the period of 2007-2012. Each cell represents U.S. dollars.

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ML2CO is the EOS Aura Microwave Limb Sounder (MLS) standard product for carbon monoxide derived from radiances measured by the 640 GHz radiometer. The current version is 2.2. Data coverage is complete from August 8, 2004 to current. Spatial coverage is near-global (-82° to +82° latitude), with each profile spaced 1.5° or ~165 km along the orbit track (roughly 15 orbits per day). The recommended useful vertical range is between 215 and 0.00464 hPa, and the vertical resolution is about 6 km. Users of the ML2CO data product should read section 3.5 of the EOS MLS Level 2 Version 2.2 Quality Document for more information (http://mls.jpl.nasa.gov/data/v2-2_data_quality_document.pdf). Users are encouraged to register with the MLS science team at https://mls.jpl.nasa.gov/forms/reguser.php to obtain updates and information about this data product. The data are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5), which is based on the version 5 Hierarchical Data Format, or HDF5. Each file contains two swath objects (one with profile data, the other with column data), each with a set of data and geolocation fields, swath attributes, and metadata. The data fields include the geophysical parameter values and precision (standard deviation), convergence values, data quality, and a status flag. The geolocation fields include a time stamp in TAI-93 format (seconds since January 1, 1993), geodetic latitude and longitude, and pressure level values, as well as local solar time, solar zenith angle, line of sight angle, and orbit geodetic angle. There is one file per day.

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LiDAR Bare-Earth Grid - Minnehaha Creek Watershed District. The Minnehaha Creek watershed is located primarily in Hennepin County, Minnesota. The watershed covers approximately 181 square miles in the western suburbs and Minneapolis, Minnesota, metropolitan area. It drains into the Mississippi River. It includes important natural resources such as Lake Minnetonka, Christmas Lake, Lake Nokomis, and Minnehaha Creek. The feasibility study has developed a Comprehensive Watershed Management Plan to assist in identifying project areas with a Federal and local interest. The focus of the remainder of the feasibility study will be on the following objectives: - Determine the flow regime in Minnehaha Creek that meets both human and ecosystem needs through a highly involved stakeholder process. - Modify the Gray’s Bay Dam Operating plan to incorporate the revised flow regime. - Improve the chemical and physical quality of surface water both in creeks and lakes. Investigate options for improving the water quality in 6-Mile Creek/Halsted Bay. - Preserve and enhance connective ecosystems (greenway corridors) on creeks leading to Lake Minnetonka and along Minnehaha Creek. - Minimize man-made obstructions to recreational boating and fish passage along the creek. - Integrate public recreation features into multipurpose project formulation whenever possible. - Preserve, protect, and restore the natural appearance and function of riparian/shoreline ecosystems throughout the watershed. - Reduce the severity and frequency of flooding along Minnehaha Creek.

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The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe navigation and to provide background data for engineers, scientific, and other commercial and industrial activities. Hydrographic survey data primarily consist of water depths, but may also include features (e.g. rocks, wrecks), navigation aids, shoreline identification, and bottom type information. NOAA is responsible for archiving and distributing the source data as described in this metadata record.

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The Youth Risk Behavior Surveillance System (YRBSS) monitors six types of health-risk behaviors that contribute to the leading causes of death and disability among youth and adults. This file contains state-level results for 13 tobacco-use variables by sex and grade for 2013.

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Survey data includes spatial datasets and data tables necessary to digitally represent data collected in the survey phase of the study. (Source: FEMA Guidelines and Specs, Appendix N)

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ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. The ESI data were collected, mapped, and digitized to provide environmental data for oil spill planning and response. The Clean Water Act with amendments by the Oil Pollution Act of 1990 requires response plans for immediate and effective protection of sensitive resources. Hydrological data range from 1950-2000, biological data range from 1998-2004 and were compiled in 2003-2004. Data are presented as GIS and associated files, with included MOSS and .PDF files for non-GIS users. Extensive documentation is included with the data. Updates to these data were received as DVD in 2008, including the Northwest Arctic, Western Alaska, and North Slope and were archived at the NODC under accession number 0049913.

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Mean annual revenue for commercial fisheries during the period of 2007-2012. Each cell represents U.S. dollars.

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Debt referrals to credit reporting agencies and the treasury offset program.

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Report to the Appropriations Committee of the United States House of Representatives in Response to Conference Committee Report to PL 110-186. In an effort to provide a snapshot of the quality of care provided at VA health care facilities, this report includes information about waiting times, staffing level, infection rates, surgical volumes, quality measures, patient satisfaction, service availability and complexity, accreditation status, and patient safety. The data in this report have been drawn from multiple sources across VHA. This dataset contains the data about staffing for Nurses, Physicians, and other Healthcare Professionals.

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Coastal study data as defined in FEMA Guidelines and Specifications, Appendix D: Guidance for Coastal Flooding Analyses and Mapping, submitted as a result of a coastal study. Appendix D notes that a variety of analytical methodologies may be used to establish Base (1-percent-annual-chance) Flood Elevations (BFEs) and floodplains throughout coastal areas of the United States. Appendix D itemizes references for the methodologies currently in use by FEMA for specific coastal flood hazards, provides general guidance for documentation of a coastal flood hazard analysis, specifies flood hazard analysis procedures for the Great Lakes coasts, and outlines intermediate data submissions for coastal flood hazard analyses with new storm surge modeling and revised stillwater flood level (SWFL). (Source: FEMA Guidelines and Specs, Appendix D Guidance for Coastal Flooding Analyses and Mapping, Section D.1)

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The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe navigation and to provide background data for engineers, scientific, and other commercial and industrial activities. Hydrographic survey data primarily consist of water depths, but may also include features (e.g. rocks, wrecks), navigation aids, shoreline identification, and bottom type information. NOAA is responsible for archiving and distributing the source data as described in this metadata record.

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This database includes information on small carrier flights performed in scheduled, non-scheduled, and charter service. The data is used to produce air carrier load-factors. It also contains data on scheduled departures, completed departures, revenue passenger miles, revenue ton miles, available seat miles, and available ton miles. It is collected by the Office of Airline Information of the Bureau of Transportation Statistics.

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Mean annual revenue for commercial fisheries during the period of 2007-2012. Each cell represents U.S. dollars.

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Federal outer Continental Shelf (OCS) Sand and Gravel Borrow Areas (Lease Areas) are polygons which are maintained by the Bureau of Ocean Energy Management (BOEM), part of the U.S. Department of the Interior. The polygons define areas where entities that have entered into a Negotiated Non-Competitive Lease or Memorandum of Agreement with BOEM can dredge sand, gravel or shell resources from the OCS. Section 8 (k) of the OCS Lands Act (OCSLA), as amended by Public Law 103-426 (enacted in 1994), provides BOEM the authority to negotiate an agreement for the use of OCS sand, gravel, and shell resources for use in: (1) a project for shore protection, beach restoration, or coastal restoration under taken by a Federal, State, or local government agency; or (2) for use in a construction project funded in whole or in part by, or authorized by, the Federal government. This dataset is a collection of previous and current authorized lease areas under BOEM's purview. The intent is to update the dataset when leases are added or renewed. Attribution consists of state, sand volume, and dates and identification properties associated with the lease. Revisions to the data, which would most often be to attribution, will occur regularly.

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Atlantic OCS aliquots (sub-blocks) for BOEM renewable energy leasing in the Atlantic.