Geospatial Services Land management within the US Forest Service and on the 900,000+ acre Monongahela National Forest (NF) is driven by a wide mix of resource and societal demands that prove a challenge in fulfilling the Forest Service’s mission of “Caring for the Land and Serving the People.” Programmatically, the 2006 Land and Resource Management Plan guide natural resource management activities on lands administered by the Monongahela National Forest. The Forest Plan describes management direction and practices, resource protection methods and monitoring, desired resource conditions, and the availability and suitability of lands for resource management. Technology enables staff to address these land management issues and Forest Plan direction by using a science-based approach to facilitate effective decisions. Monongahela NF geospatial services, using enabling-technologies, incorporate key tools such as Environmental Systems Research Institute’s ArcGIS desktop suite and Trimble’s global positioning system (GPS) units to meet program and Forest needs. Geospatial Datasets The Forest has a broad set of geospatial datasets that capture geographic features across the eastern West Virginia landscape. Many of these datasets are available to the public through our download site. Selected geospatial data that encompass the Monongahela National Forest are available for download from this page. A link to the FGDC-compliant metadata is provided for each dataset. All data are in zipped format (or available from the specified source), in one of two spatial data formats, and in the following coordinate system: Coordinate System: Universal Transverse Mercator Zone: 17 Units: Meters Datum: NAD 1983 Spheroid: GRS 1980 Map files – All map files are in pdf format. These maps illustrate the correlated geospatial data. All maps are under 1 MB unless otherwise noted. Metadata file – This FGDC-compliant metadata file contains information pertaining to the specific geospatial dataset. Shapefile – This downloadable zipped file is in ESRI’s shapefile format. KML file – This downloadable zipped file is in Google Earth’s KML format. Resources in this dataset:Resource Title: Monongahela National Forest Geospatial Data. File Name: Web Page, url: https://www.fs.usda.gov/detail/mnf/landmanagement/gis/?cid=stelprdb5108081 Selected geospatial data that encompass the Monongahela National Forest are available for download from this page.

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and recreation access across the nation. The PAD-US 3.0 Combined Fee, Designation, Easement feature class (with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class) was modified to remove overlaps, avoiding overestimation in protected area statistics and to support user needs. A Python scripted process ("PADUS3_0_CreateVectorAnalysisFileScript.zip") associated with this data release prioritized overlapping designations (e.g. Wilderness within a National Forest) based upon their relative biodiversity conservation status (e.g. GAP Status Code 1 over 2), public access values (in the order of Closed, Restricted, Open, Unknown), and geodatabase load order (records are deliberately organized in the PAD-US full inventory with fee owned lands loaded before overlapping management designations, and easements). The Vector Analysis File ("PADUS3_0VectorAnalysisFile_ClipCensus.zip") associated item of PAD-US 3.0 Spatial Analysis and Statistics ( https://doi.org/10.5066/P9KLBB5D ) was clipped to the Census state boundary file to define the extent and serve as a common denominator for statistical summaries. Boundaries of interest to stakeholders (State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative) were incorporated into separate geodatabase feature classes to support various data summaries ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.zip") and Comma-separated Value (CSV) tables ("PADUS3_0SummaryStatistics_TabularData_CSV.zip") summarizing "PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.zip" are provided as an alternative format and enable users to explore and download summary statistics of interest (Comma-separated Table [CSV], Microsoft Excel Workbook [.XLSX], Portable Document Format [.PDF] Report) from the PAD-US Lands and Inland Water Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). In addition, a "flattened" version of the PAD-US 3.0 combined file without other extent boundaries ("PADUS3_0VectorAnalysisFile_ClipCensus.zip") allow for other applications that require a representation of overall protection status without overlapping designation boundaries. The "PADUS3_0VectorAnalysis_State_Clip_CENSUS2020" feature class ("PADUS3_0VectorAnalysisFileOtherExtents_Clip_Census.gdb") is the source of the PAD-US 3.0 raster files (associated item of PAD-US 3.0 Spatial Analysis and Statistics, https://doi.org/10.5066/P9KLBB5D ). Note, the PAD-US inventory is now considered functionally complete with the vast majority of land protection types represented in some manner, while work continues to maintain updates and improve data quality (see inventory completeness estimates at: http://www.protectedlands.net/data-stewards/ ). In addition, changes in protected area status between versions of the PAD-US may be attributed to improving the completeness and accuracy of the spatial data more than actual management actions or new acquisitions. USGS provides no legal warranty for the use of this data. While PAD-US is the official aggregation of protected areas ( https://www.fgdc.gov/ngda-reports/NGDA_Datasets.html ), agencies are the best source of their lands data.

Spatial analysis and statistical summaries of the Protected Areas Database of the United States (PAD-US) provide land managers and decision makers with a general assessment of management intent for biodiversity protection, natural resource management, and outdoor recreation access across the nation. This data release presents results from statistical summaries of the PAD-US 3.0 protection status (by GAP Status Code) and public access status for various land unit boundaries (Protected Areas Database of the United States 3.0 Vector Analysis and Summary Statistics). Summary statistics are also available to explore and download (Comma-separated Table [CSV], Microsoft Excel Workbook (.xlsx), Portable Document Format [.pdf] Report) from the PAD-US Lands and Inland Water Statistics Dashboard ( https://www.usgs.gov/programs/gap-analysis-project/science/pad-us-statistics ). The vector GIS analysis file, source data used to summarize statistics for areas of interest to stakeholders (National, State, Department of the Interior Region, Congressional District, County, EcoRegions I-IV, Urban Areas, Landscape Conservation Cooperative), and complete Summary Statistics Tabular Data (CSV) are included in this data release. Raster GIS analysis files are also available for combination with other raster data (Protected Areas Database of the United States (PAD-US) 3.0 Raster Analysis). The PAD-US 3.0 Combined Fee, Designation, Easement feature class in the full inventory, with Military Lands and Tribal Areas from the Proclamation and Other Planning Boundaries feature class (Protected Areas Database of the United States (PAD-US) 3.0, https://doi.org/10.5066/P9Q9LQ4B), was modified to prioritize and remove overlapping management designations, limiting overestimation in protection status or public access statistics and to support user needs for vector and raster analysis data. Analysis files in this data release were clipped to the Census State boundary file to define the extent and fill in areas (largely private land) outside the PAD-US, providing a common denominator for statistical summaries.

Treasure County Cadastral Data ResourcesA snapshot of property and parcel data for June 2022.Department of Revenue Orion SQL property record database provided as both an SQL database and as tables in a file geodatabase.File Geodatabase and Shapefile options for parcel polygon GIS data.Visit the Montana State Library Cadastral MSDI page for more information on cadastral data and Orion property database : MSDI Cadastral (mt.gov)The Montana Cadastral Framework shows the taxable parcels and tax-exempt parcels for most of Montana. The parcels contain selected information such as owner names, property and owner addresses, assessed value, agricultural use, and tax district information that were copied from the Montana Department of Revenue's ORION tax appraisal database. The data are maintained by the MT Department of Revenue, except for Ravalli, Silver Bow, Missoula, Flathead and Yellowstone counties that are maintained by the individual counties. The Revenue and county data are integrated by Montana State Library staff. Each parcel contains an attribute called ParcelID (geocode) that is the parcel identifier. View a pdf map of the counties that were updated this month here: https://ftpgeoinfo.msl.mt.gov/Data/Spatial/MSDI/Cadastral/Parcels/Statewide/MonthlyCadastralUpdateMap.pdf The parcel boundaries were aligned to fit with the Bureau of Land Management Geographic Coordinate Database (GCDB) of public land survey coordinates. Parcels whose legal descriptions consisted of aliquot parts of the public land survey system were created from the GCDB coordinates by selecting and, when necessary, subdividing public land survey entities. Other parcels were digitized from paper maps and the data from each map were transformed to fit with the appropriate GCDB boundaries.

This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

© MarineCadastre.gov This layer is a component of BOEMRE Layers.

This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.

For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov

The REST services for National Level Data can be found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer

REST services for regional level data can be found by clicking on the region of interest from the following URL: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE

Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL: http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx

Currently the following layers are available from this REST location:

OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.

OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.

OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.

BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.

BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.

Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.

Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip

BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf

description: LUP_CRNT_POLY: Land Use Planning Current Polygon describes the planning or project area for the Land Use Planning Current dataset. The LUP_CRNT dataset contains active (or current) LUPs, usually RMP and RMPA (those with a signed Record of Decision (ROD)) and extends to the adjacent Plan Area Boundaries, wall-to-wall, with no gaps or overlaps. For a more detailed description of the LUP_CRNT dataset see the Supplemental Information section in this document or follow the link to the Plan Area Boundary Spatial Data Standard below. Data Standard Linkage: http://www.blm.gov/or/datamanagement/files/LUP_Revised_Data_Standard.pdf; abstract: LUP_CRNT_POLY: Land Use Planning Current Polygon describes the planning or project area for the Land Use Planning Current dataset. The LUP_CRNT dataset contains active (or current) LUPs, usually RMP and RMPA (those with a signed Record of Decision (ROD)) and extends to the adjacent Plan Area Boundaries, wall-to-wall, with no gaps or overlaps. For a more detailed description of the LUP_CRNT dataset see the Supplemental Information section in this document or follow the link to the Plan Area Boundary Spatial Data Standard below. Data Standard Linkage: http://www.blm.gov/or/datamanagement/files/LUP_Revised_Data_Standard.pdf

LUP_HIST_POLY: Land Use Planning Historicy Polygon (LUP_HIST_POLY) describes the planning or project area for the Land Use Planning Historic (LUP_HIST) dataset. For a more detailed description of the LUP_HIST dataset see the Supplemental Information section in this document or follow the link to the Plan Area Boundary Spatial Data Standard below. Data Standard Linkage: http://www.blm.gov/or/datamanagement/files/LUP_Revised_Data_Standard.pdf

Our climate is evolving at a rapid pace, and with it comes unprecedented uncertainties through larger, and more frequent disasters. With the ever present threat of rising sea levels, droughts, wildfires, flooding, and more, we must accelerate our readiness for climate change and improve our resiliency to disasters. In order to achieve this we must enhance and improve the climate data value chain to create better climate and disaster information for decision makers.As a follow on from 5+ years of successes through the Climate Resilience Pilot and series of Disaster Pilots and forms, OGC brings you the Climate and Disaster Resilience Pilot 2024 (CDRP24). The next phase of an ongoing OGC disaster and climate initiative, CDRP24 is focused on delivering impacts through interoperable geospatial technologies and standards, all to help combat climate and disasters.CDRP24 will consist of individual threads that each work towards specific end-user, stakeholder, and technical goals that advance our climate and/or disaster understanding and readiness while also seeding collaboration between these two related domains.While building upon the knowledge gained from past pilots, the intent of the Pilot is to:Enhance climate and disaster services by moving the underpinning technical systems towards FAIR Climate & Disaster Services: collaborative and equitable Findable, Accessible, Interoperable, and Reusable systems that provide information-on-demand to understand, trace, mitigate, adapt, and respond.Build sustainable relationships between science domains, researchers, decision makers, and data & systems providers.Identify the stakeholder’s information and knowledge needs and tailor innovative solutions that promote community and environmental resilience across disparate science and social domains accordingly.Improve visualization, use-case driven simulations, and communication approaches. Improve interactivity and interchanges with OGC’s sponsors, members, and participants to ensure the greatest applicability and a broader scope and impact.The Call for Sponsors (CFS) is available here as HTML or PDF.Sponsoring the CDRP24 will directly improve Climate Resilience Information Systems and Emergency Management Systems. Sponsors benefit from having their specific requirements addressed by teams of experts in integration and interoperability. Sponsors enable organizations to collaboratively improve and enhance the sponsors’ systems, progress technical capabilities, and advance scientific reliability of Analysis Ready Data (ARD) and Decision Ready Indicators (DRI). As such, sponsors have the unique opportunity to share the newly developed interactive systems solutions to the international community working within and across the climate and disaster domains.Tags:Climate, Climate Change, Disaster Resilience, Earth Observation, Spatial Data Infrastructure

LUP_PRGS_POLY: Land Use Progress Boundary Polygon (LUP_PRGS_POLY) describes the planning or project area for the Land Use in Progress (LUP_PRGS) dataset.

The LUP_PRGS dataset contains LUPs that are in progress. There should not be more than one LUP in progress in a particular area. When an RMP or RMPA changes from in progress to active, the polygons and arcs are added to LUP_CRNT and removed from LUP_PRGS. Once an LUP becomes active, it must integrate with other active LUPs so that there will continue to be no gaps or overlaps in active LUPs.

For a more detailed description of the LUP_PRGS dataset see the Supplemental Information section in this document or follow the link to the Plan Area Boundary Spatial Data Standard below.

Data Standard Linkage: http://www.blm.gov/or/datamanagement/files/LUP_Revised_Data_Standard.pdf

SCCWRP and technical partners (Colorado School of Mines and Council for Watershed Health), worked with the State Water Resources Control Board and the Los Angeles Regional Water Quality Control Board, in cooperation with local municipalities (including City of LA Bureau of Sanitation, City of LA Department of Water and Power, LA County Department of Public Works, and LA County Sanitation Districts), to conduct the Los Angeles River Environmental Flows Project (Project). The goals of the project were to develop a process for establishing flow criteria, to apply the process to provide recommendations for flow criteria in the LA River, and to produce tools and approaches to evaluate management scenarios necessary to achieve recommended flow criteria. The project also serves as an important pilot application of the California Environmental Flows Framework (CEFF) by demonstrating how CEFF can be applied in a highly urbanized watershed where flow alteration is primarily caused by treated wastewater and stormwater discharges. The outcomes of this project may also serve as a model for assessing similar situations in other river systems.

For more information about this project, go to the project website: https://www.sccwrp.org/about/research-areas/ecohydrology/los-angeles-river-flows-project/

A full description of the methods and datasets are described in the Aquatic Life Use Assessment technical report: https://ftp.sccwrp.org/pub/download/DOCUMENTS/TechnicalReports/1154_LARiverAquaticLifeUses.pdf

This layer is the Minnesota Department of Natural Resources (DNR) 10-year stand exam list - a forest resource management plan specifying which forest stands the DNR will visit and evaluate for potential harvest during fiscal years 2021 – 2030 (actual harvest is contingent on results of a site visit, public auction, and the operational environment). The DNR Forest Inventory Module (FIM, or Forest Stand Inventory) data are the base for this dataset, which includes additional attributes used to develop the 10-year stand exam list.

For more information, visit the DNR sustainable timber harvest analysis, decisions, and planning webpage ( https://www.dnr.state.mn.us/forestry/harvest-analysis/index.html ) and review related documents:

• Sustainable Timber Harvest: Development of the DNR 10-year Stand Exam List Report ( https://files.dnr.state.mn.us/forestry/subsection/harvest-analysis/sth-10-year-stand-exam-list-report.pdf ) – this companion report to the 10-year stand exam list data communicates how the 10-year stand exam list was developed to meet decisions associated with DNR’s sustainable timber harvest analysis. It provides context for understanding the 10-year stand exam list and what it means for implementation going forward.

• Documentation of the Spatial Data used during the Sustainable Timber Harvest Projects ( https://files.dnr.state.mn.us/forestry/subsection/harvest-analysis/documentation-spatial-data-sth.pdf ) – this expanded metadata document provides more comprehensive information about the attributes in this dataset.

Supplemental Data:

The full FIM snapshot that was used to model the 10-year stand exam list, with attributes added for modeling, is also available in shapefile format from the DNR FTP site: ftp://ftp.dnr.state.mn.us/pub/SFRMPDATA/MBG_STHA/STH_FIM_1P.zip . The full modeling dataset includes all DNR-administered stands with inventory data, totaling approximately 5.4 million acres, some of which are not commercially managed. The dataset used to build the 10-year stand exam list is an extension of the data used for the DNR’s most recent sustainable timber harvest analysis (see MB&G Phase 1, Phase 2, and Final reports - https://www.dnr.state.mn.us/forestry/harvest-analysis/index.html ). Within the full modeling dataset, stands on the 10-year stand exam list are identified with a stand exam year and preliminary management prescription.

Marine conservation areas are an important tool for the sustainable management of multispecies, small-scale fisheries. Effective spatial management requires a proper understanding of the spatial distribution of target species and the identification of its environmental drivers. Small-scale fisheries, however, often face scarcity and low-quality of data. In these situations, approaches for the prioritization of conservation areas need to deal with scattered, biased, and short-term information and ideally should quantify data- and model-specific uncertainties for a better understanding of the risks related to management interventions. We used a Bayesian hierarchical species distribution modeling approach on annual landing data of the heavily exploited, small-scale, and data-poor fishery of Chwaka Bay (Zanzibar) in the Western Indian Ocean to understand the distribution of the key target species and identify potential areas for conservation. Few commonalities were found in the set of important habitat and environmental drivers among species, but temperature, depth, and seagrass cover affected the spatial distribution of three of the six analyzed species. A comparison of our results with information from ecological studies suggests that our approach predicts the distribution of the analyzed species reasonably well. Furthermore, the two main common areas of high relative abundance identified in our study have been previously suggested by the local fisher as important areas for spatial conservation. By using short-term, catch per unit of effort data in a Bayesian hierarchical framework, we quantify the associated uncertainties while accounting for spatial dependencies. More importantly, the use of accessible and interpretable tools, such as the here created spatial maps, can frame a better understanding of spatio-temporal management for local fishers. Our approach, thus, supports the operability of spatial management in small-scale fisheries suffering from a general lack of long-term fisheries information and fisheries independent data.

A long-term study of the geomorphic history of the lower Rio Puerco arroyo in north-central New Mexico included the collection of high-precision (Real-time kinematic) GPS survey data (2002, 2007, 2010, and 2014), registration and rectification of historical aerial photographs (1935, 1950s, 1970s, and 1996), an aerial LiDAR survey (2005) with collection of digital imagery, and acquisition of post-flood (2006) satellite imagery. The Rio Puerco is a single-thread, meandering stream inset within an arroyo located in semiarid north-central New Mexico. The study reach extent is from the confluence with the Rio San Jose 67 km downvalley to the Rio Puerco streamgage near Bernardo, NM. Arroyo and channel geomorphic features in 1935, 1950s, 1970s, 1996, 2005, and 2006 were mapped from imagery and are provided here as shapefiles. Features mapped for the purpose of assessing spatial and temporal geomorphic change include tops of the arroyo walls, edges of the arroyo bottom, tops of the channel banks, channel centerline, arroyo centerline, and canopy coverage. All of these data are provided here except for the November and December 2006 high-resolution Quickbird II satellite imagery (DigitalGlobe, Inc.), which is proprietary and, therefore, cannot be served here. Publications: Griffin, E.R., Kean, J.W., Vincent, K.R., Smith, J.D., and Friedman, J.M., 2005, Modeling effects of bank friction and woody bank vegetation on channel flow and boundary shear stress in the Rio Puerco, New Mexico, Journal of Geophysical Research, 110, F04023. doi: 10.1029/2005JF000322 Vincent, K.R., Friedman, J.M., and Griffin, E.R., 2009, Erosional consequence of saltcedar control, Environmental Management, 44, 218-227. doi: 10.1007/s00267-009-9314-8 Griffin, E.R., Smith, J.D., Friedman, J.M., and Vincent, K.R., 2010, Progression of streambank erosion during a large flood, Rio Puerco arroyo, New Mexico, Proceedings of the 2nd Joint Federal Interagency Conference, Las Vegas, NV, June 27 – July 1, 2010, 12 p. Perignon, M.C., Tucker, G.E., Griffin, E.R., and Friedman, J.M., 2013, Effects of riparian vegetation on topographic change during a large flood event, Rio Puerco, New Mexico, USA, Journal of Geophysical Research: Earth Surface, 118, 1193-1209. doi: 10.1002/jgrf.20073 Griffin, E.R., Perignon, M.C., Friedman, J.M., and Tucker, G.E., 2014, Effects of woody vegetation on overbank sand transport during a large flood, Rio Puerco, New Mexico, Geomorphology, 207, 30-50. doi: 10.1016/j.geomorph.2013.10.025 Friedman, J.M., Vincent, K.R., Griffin, E.R., Scott, M.L., Shafroth, P.B., and Auble, G.T., 2015, Processes of arroyo filling in northern New Mexico, USA, GSA Bulletin, 127(3/4), 621-640. doi: 10.1130/B31046.1 Griffin, E.R., and Friedman, J.M., 2015, Processes limiting depth of arroyo incision: examples from the Rio Puerco, New Mexico, in Proceedings of the 3rd Joint Federal Interagency Conference (10th Federal Interagency Sedimentation Conference and 5th Federal Interagency Hydrologic Modeling Conference), Reno, Nevada, April 19 – 23, 2015, 797-808. http://acwi.gov/sos/pubs/3rdJFIC/Contents/5A-Griffin.pdf

This new data class brings over data from the Waste Management Information System (WMIS), which is an MS Access based database used by MNR to track Waste Management Sites. This was married with the spatial data from Waste Disposal Sites where possible. Different Waste Disposal Site types collected by the Ministry of Natural Resources include: Compost Disposal Hazardous Waste Disposal Household Waste Disposal Industrial Waste Disposal Septic Drying Bed Septic Field Sewage Disposal Tile Bed Transfer Station

This class has related tables. Waste Management Site related tables

Additional Documentation

Waste Management Site - User Guide (PDF) Waste Management Site - Data Description (PDF) Waste Management Site - Documentation (Word) Status Under development: data is currently in the process of being created

Maintenance and Update Frequency

Not Stated Contact Ryan Lenethen, Ryan.Lenethen@ontario.ca

Missoula County Cadastral Data ResourcesA snapshot of property and parcel data for July 2022.Department of Revenue Orion SQL property record database provided as both an SQL database and as tables in a file geodatabase.File Geodatabase and Shapefile options for parcel polygon GIS data.Visit the Montana State Library Cadastral MSDI page for more information on cadastral data and Orion property database : MSDI Cadastral (mt.gov)The Montana Cadastral Framework shows the taxable parcels and tax-exempt parcels for most of Montana. The parcels contain selected information such as owner names, property and owner addresses, assessed value, agricultural use, and tax district information that were copied from the Montana Department of Revenue's ORION tax appraisal database. The data are maintained by the MT Department of Revenue, except for Ravalli, Silver Bow, Missoula, Flathead and Yellowstone counties that are maintained by the individual counties. The Revenue and county data are integrated by Montana State Library staff. Each parcel contains an attribute called ParcelID (geocode) that is the parcel identifier. View a pdf map of the counties that were updated this month here: https://ftpgeoinfo.msl.mt.gov/Data/Spatial/MSDI/Cadastral/Parcels/Statewide/MonthlyCadastralUpdateMap.pdf The parcel boundaries were aligned to fit with the Bureau of Land Management Geographic Coordinate Database (GCDB) of public land survey coordinates. Parcels whose legal descriptions consisted of aliquot parts of the public land survey system were created from the GCDB coordinates by selecting and, when necessary, subdividing public land survey entities. Other parcels were digitized from paper maps and the data from each map were transformed to fit with the appropriate GCDB boundaries.

The data included in this publication depict the 2024 version of components of wildfire risk for all lands in the United States that: 1) are landscape-wide (i.e., measurable at every pixel across the landscape); and 2) represent in situ risk - risk at the location where the adverse effects take place on the landscape.

National wildfire hazard datasets of annual burn probability and fire intensity, generated by the USDA Forest Service, Rocky Mountain Research Station and Pyrologix LLC, form the foundation of the Wildfire Risk to Communities data. Vegetation and wildland fuels data from LANDFIRE 2020 (version 2.2.0) were used as input to two different but related geospatial fire simulation systems. Annual burn probability was produced with the USFS geospatial fire simulator (FSim) at a relatively coarse cell size of 270 meters (m). To bring the burn probability raster data down to a finer resolution more useful for assessing hazard and risk to communities, we upsampled them to the native 30 m resolution of the LANDFIRE fuel and vegetation data. In this upsampling process, we also spread values of modeled burn probability into developed areas represented in LANDFIRE fuels data as non-burnable. Burn probability rasters represent landscape conditions as of the end of 2020. Fire intensity characteristics were modeled at 30 m resolution using a process that performs a comprehensive set of FlamMap runs spanning the full range of weather-related characteristics that occur during a fire season and then integrates those runs into a variety of results based on the likelihood of those weather types occurring. Before the fire intensity modeling, the LANDFIRE 2020 data were updated to reflect fuels disturbances occurring in 2021 and 2022. As such, the fire intensity datasets represent landscape conditions as of the end of 2022. Additional methodology documentation is provided in a methods document (\Supplements\WRC_V2_Methods_Landscape-wideRisk.pdf) packaged in the data download.

The specific raster datasets in this publication include:

Risk to Potential Structures (RPS): A measure that integrates wildfire likelihood and intensity with generalized consequences to a home on every pixel. For every place on the landscape, it poses the hypothetical question, "What would be the relative risk to a house if one existed here?" This allows comparison of wildfire risk in places where homes already exist to places where new construction may be proposed. This dataset is referred to as Risk to Homes in the Wildfire Risk to Communities web application.

Conditional Risk to Potential Structures (cRPS): The potential consequences of fire to a home at a given location, if a fire occurs there and if a home were located there. Referred to as Wildfire Consequence in the Wildfire Risk to Communities web application.

Exposure Type: Exposure is the spatial coincidence of wildfire likelihood and intensity with communities. This layer delineates where homes are directly exposed to wildfire from adjacent wildland vegetation, indirectly exposed to wildfire from indirect sources such as embers and home-to-home ignition, or not exposed to wildfire due to distance from direct and indirect ignition sources.

Burn Probability (BP): The annual probability of wildfire burning in a specific location. Referred to as Wildfire Likelihood in the Wildfire Risk to Communities web application.

Conditional Flame Length (CFL): The mean flame length for a fire burning in the direction of maximum spread (headfire) at a given location if a fire were to occur; an average measure of wildfire intensity.

Flame Length Exceedance Probability - 4 ft (FLEP4): The conditional probability that flame length at a pixel will exceed 4 feet if a fire occurs; indicates the potential for moderate to high wildfire intensity.

Flame Length Exceedance Probability - 8 ft (FLEP8): the conditional probability that flame length at a pixel will exceed 8 feet if a fire occurs; indicates the potential for high wildfire intensity.

Wildfire Hazard Potential (WHP): An index that quantifies the relative potential for wildfire that may be difficult to manage, used as a measure to help prioritize where fuel treatments may be needed.The geospatial data products described and distributed here are part of the Wildfire Risk to Communities project. This project was directed by Congress in the 2018 Consolidated Appropriations Act (i.e., 2018 Omnibus Act, H.R. 1625, Section 210: Wildfire Hazard Severity Mapping) to help U.S. communities understand components of their relative wildfire risk profile, the nature and effects of wildfire risk, and actions communities can take to mitigate risk. The first edition of these data represented the first time wildfire risk to communities had been mapped nationally with consistent methodology. They provided foundational information for comparing the relative wildfire risk among populated communities in the United States. In this version, the 2nd edition, we use improved modeling and mapping methodology and updated input data to generate the current suite of products.See the Wildfire Risk to Communities website at https://www.wildfirerisk.org for complete project information and an interactive web application for exploring some of the datasets published here. We deliver the data here as zip files by U.S. state (including AK and HI), and for the full extent of the continental U.S.

This data publication is a second edition and represents an update to any previous versions of Wildfire Risk to Communities risk datasets published by the USDA Forest Service. There are two companion data publications that are part of the WRC 2.0 data update: one that includes datasets of wildfire hazard and risk for populated areas of the nation, where housing units are currently present (Jaffe et al. 2024, https://doi.org/10.2737/RDS-2020-0060-2), and one that delineates wildfire risk reduction zones and provides tabular summaries of wildfire hazard and risk raster datasets (Dillon et al. 2024, https://doi.org/10.2737/RDS-2024-0030).

The Central Valley Flood Protection Plan (CVFPP) recommends that the California Department of Water Resources (DWR) develop a system for tracking performance of the flood system, including the following actions:• Track the outcomes from flood investments to demonstrate value.• Monitor and track outcomes of multi-benefit projects over time.• Create a tracking system of operations and maintenance investments and outcomes to demonstrate the value that Local Maintaining Agencies attain for their investments.• Track and report changes in the hydrologic and sea level rise conditions and subsidence over time through updates to the Flood System Status Report (FSSR)These recommendations stem from progressive work during the development of the 2012 CVFPP and subsequent 2017 CVFPP update. The DWR Flood Performance Tracking System tracks the CVFPP outcomes related to: (1) improving flood risk management and (2) enhancing ecosystem vitality. This tracking system has the ability to track the status, trends, and changes over time of the ecosystem (including the Conservation Strategy’s Measurable Objectives [CSMOs] as of 2016) outlined in the Conservation Strategy document here: https://cawaterlibrary.net/wp-content/uploads/2017/10/ConservStrat-Nov2016.pdf along with the Flood System metrics outlined in the Flood System Status Report here: https://water.ca.gov/Programs/Flood-Management/Flood-Planning-and-Studies/Central-Valley-Flood-Protection-Plan.The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.1, dated September 11, 2019.This data set was not produced by DWR. Data were originally developed and supplied by ESA, under contract to California Department of Water Resources. DWR makes no warranties or guarantees — either expressed or implied — as to the completeness, accuracy, or correctness of the data. DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data.Comments, problems, improvements, updates, or suggestions should be forwarded to gis@water.ca.gov.

This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

© MarineCadastre.gov This layer is a component of BOEMRE Layers.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

Dataset WM1127 contains all the water resource plan (WRP) areas in Queensland that are in force in legislation currently, except for the Great Artesian Basin (GAB) WRP area (dataset WM0702). (For more information see http://www.dnrm.qld.gov.au/water/catchments-planning ). WM1127

replaced WM0924v2 due to the "Water Resource (Burnett Basin) Plan 2014" (Burnett 2014 WRP) coming into force (mapping accuracy improvements were applied for part of the Burnett WRP area).

(Reference: CAS1881, 2026.)

Purpose

Legislation: 2000 Act Number 34, "Water Act 2000", Part 3 "Water planning", Division 2 "Water resource plans", Subdivision 1 "Power to prepare water resource plans", section 38 "Minister may prepare water resource plans" and section 55 "When water resource plans may be amended or replaced" (http://www.legislation.qld.gov.au/OQPChome.htm http://www.legislation.qld.gov.au/LEGISLTN/CURRENT/W/WaterA00.pdf ).

Subordinate legislation: "Water Resource (title) Plan year" (http://www.legislation.qld.gov.au/Acts_SLs/Acts_SL_W.htm ).

Dataset History

Metadata format: Esri ArcGIS v10+ Style: ISO 19139. (Open Data metadata is supplied in three formats: HyperText Markup Language (.htm file), Esri ArcGIS v10+ ArcGIS metadata (.shp.xml file), and International Standards Organisation (ISO) 19139 "Geographic Information - Metadata

• XML schema implementation" of ISO 19115 "Geographic Information - Metadata" (_ISO19139.xml file). View the .htm file in a web browser,

the .shp.xml file in Esri ArcGIS v10+, and the ISO19139 file in other GIS applications. The ArcGIS metadata format is editable in ArcGIS and has

live hyperlinks.) Mapping scale is generally 1:100,000 and enhanced in places with larger scale mapping (for example 1:25,000) and in places by

ground truthing by visiting the location. If required, more information should be obtained from the department where an area of interest is near

to or crossing a boundary. Information asset theme "water management", subtheme "management area", "water resource plan". Attributes: SDI

Spatial Data Index, departmental internal unique identifier for a Feature Object and Feature Class. TITLE Title (name). COMMENCE Commencement date "in force". COMMENCESL Subordinate legislation number. INTERNET Uniform Resource Locator (URL, web address) of

department webpage for the object.

Dataset Citation

Queensland Government (2015) Water resource plan areas - Queensland. Bioregional Assessment Source Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/d2fe0619-4545-4bd0-b983-5cbb4e9399be.

This spatial dataset represents the locations of aquatic resource area (ARA) survey points. ARA survey points may represent a portion of a water body or an entire water body (such as a lake, river or stream). Attributes for each location may include:physical characteristics such as water temperature and depthfish speciesThe ARA data classes are the authoritative source for generic spatial data related to fish species in Ontario. The data can be used for:forest and fisheries management planningmunicipal planningnatural heritage and land use planningissuing work permits under the Public Lands Act, 1990issuing licenses under the Fish and Wildlife Conservation Act, 1997fulfilling public information requestsThere are additional sensitive data related to provincially tracked species and species at risk that are not available as part of this open data package. Distribution of sensitive species data is approved on a need-to-know basis. Requests should be sent to geospatial@ontario.ca.Additional DocumentationARA Survey Point - User Guide (PDF)ARA Survey Point - Data Description (PDF)Aquatic Resource Area Survey Point - Documentation (Word)StatusOn going: data is being continually updatedMaintenance and Update FrequencyAs needed: data is updated as deemed necessaryContactMae Rannells-Warren, Fisheries Section, Fish and Wildlife Policy Branch, mae.rannells-warren@ontario.ca