100+ datasets found
  1. d

    Development of Interactive Data Visualization Tool for the Predictive...

    • search.dataone.org
    • borealisdata.ca
    • +1more
    Updated Dec 28, 2023
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    Chan, Wai Chung Wilson (2023). Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project [Dataset]. http://doi.org/10.5683/SP3/7RVB70
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    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Chan, Wai Chung Wilson
    Description

    Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

  2. Global Customer Journey Mapping Software Market Size By Functionality...

    • verifiedmarketresearch.com
    Updated Jun 28, 2024
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    VERIFIED MARKET RESEARCH (2024). Global Customer Journey Mapping Software Market Size By Functionality (Mapping and Visualization Tools, Analysis and Reporting Tools, Integration Tools), By Development Mode (Cloud-Based, On-Premises), By Organization Size (Small and Medium-sized Enterprises, Large Enterprises), By Geographic Scope And Forecast [Dataset]. https://www.verifiedmarketresearch.com/product/customer-journey-mapping-software-market/
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    Dataset updated
    Jun 28, 2024
    Dataset provided by
    Verified Market Researchhttps://www.verifiedmarketresearch.com/
    Authors
    VERIFIED MARKET RESEARCH
    License

    https://www.verifiedmarketresearch.com/privacy-policy/https://www.verifiedmarketresearch.com/privacy-policy/

    Time period covered
    2024 - 2031
    Area covered
    Global
    Description

    Customer Journey Mapping Software size was valued to be USD 10.8 Billion in the year 2023 and it is expected to reach USD 53.6 Billion in 2031, at a CAGR of 13.8% over the forecast period of 2024 to 2031.

    Customer Journey Mapping (CJM) software is a specialist application that helps organizations see and analyze the various stages of a customer’s interaction with a firm. This program delivers a full and comprehensive perspective of the customer experience from the first contact to the final encounter allowing businesses to optimize their operations and increase overall customer satisfaction

    . The essence of CJM software is its capacity to record and map out the customer journey in a visual manner such as a flowchart or diagram which aids in identifying pain points, understanding customer wants, and aligning business goals appropriately.

    The primary application of customer journey mapping software is to improve customer experience (CX). Understanding the various stages and touchpoints of the customer journey allows firms to discover pain points and areas for improvement. For example, if a customer journey map shows that consumers regularly abandon their shopping carts at the payment stage, the company can investigate and fix the problem whether by streamlining the checkout process, providing clearer instructions, or offering more payment options.

    CJMS will use advanced analytics to deliver more detailed insights into client behavior and preferences. The integration of big data and predictive analytics will enable organizations to anticipate client wants and identify possible problems before they arise. This proactive strategy will allow businesses to modify their services and interactions in real-time resulting in a smooth and rewarding consumer experience. Businesses will obtain a holistic picture of the consumer journey by analyzing massive volumes of data from multiple touchpoints revealing patterns and trends that can be used to guide strategic choices and optimize marketing efforts.

    Enhanced Attention to Customer Experience (CX): The importance of delivering superior customer experiences for sustaining brand loyalty and boosting revenue is increasingly acknowledged by businesses. The ability of customer journey mapping software to enable businesses to pinpoint and refine customer interaction points throughout their journey is leading to enhanced CX and competitive differentiation.

    Embracing Omnichannel Marketing: The engagement of modern consumers with brands through diverse platforms (including websites, social media, and mobile apps) is noted. The tracking of these multi-channel interactions and the understanding of customer behavior facilitated by customer journey mapping software assist in tailoring marketing efforts for better engagement.

    The Requirement for Insights Based on Data: The necessity for insights driven by data in comprehending customer behavior and preferences is recognized by businesses. Through the aggregation and examination of customer information from various sources, customer journey mapping software offers critical insights for augmenting customer engagement and loyalty.

    Regulatory Compliance Demands: Certain sectors are governed by regulations that enforce data privacy and security standards. Tools for meticulous tracking and management of customer information are provided by customer journey mapping software aiding businesses in meeting these regulatory requirements.

    Increased Utilization Among SMBs: The adoption of customer journey mapping software previously more common among larger corporations, is now expanding to Small and Medium Businesses (SMBs). The appeal of this technology to a broader business spectrum is being enhanced by cloud-based solutions and subscription models.

  3. NCRMP Atlantic Fish Map

    • noaa.hub.arcgis.com
    Updated May 23, 2023
    + more versions
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    NOAA GeoPlatform (2023). NCRMP Atlantic Fish Map [Dataset]. https://noaa.hub.arcgis.com/maps/7b6f1660fe974cb1becf7aab51abf625
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    Dataset updated
    May 23, 2023
    Dataset provided by
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA GeoPlatform
    Area covered
    Description

    This map contains summary data meant to be visualized within the National Coral Reef Monitoring Program's Data Visualization Tool.This map and its associated data/dashboards/hub are developed to represent data in both the Atlantic and Pacific basins and all four monitoring themes (Socioeconomic, Benthic, Fish and Climate). Each dashboard presents data at a resolution that is appropriate for the sampling method and effort for each area. Users can filter the data by a number of variables to allow them to refine the graphs and charts. Additionally, users can download the summary data tables for their own analyses. The metadata for the data in this application can be found at https://www.ncei.noaa.gov/data/oceans/coris/library/NOAA/CRCP/monitoring/metadata/This map is dependent upon the following AGOL items:NCRMP_Prod_gdb Feature Layer (hosted) NCRMP_Prod_gdb File Geodatabase The following AGOL items are dependent upon this map:NCRMP Data Visualization Tool Hub Site Application NCRMP Data Visualization Tool Hub Initiative NCRMP Atlantic Fish Dashboard Web Experience NCRMP Atlantic Fish Embed Dashboard

  4. d

    Data from: California State Waters Map Series--Offshore of Santa Cruz Web...

    • datasets.ai
    • data.usgs.gov
    • +1more
    55
    Updated Sep 21, 2024
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    Department of the Interior (2024). California State Waters Map Series--Offshore of Santa Cruz Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-santa-cruz-web-services
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    55Available download formats
    Dataset updated
    Sep 21, 2024
    Dataset authored and provided by
    Department of the Interior
    Area covered
    Santa Cruz, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Santa Cruz map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Santa Cruz map area data layers. Data layers are symbolized as shown on the associated map sheets.

  5. Digital Geologic-GIS Map of Sagamore Hill National Historic Site and...

    • s.cnmilf.com
    • gimi9.com
    • +1more
    Updated Jun 5, 2024
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    National Park Service (2024). Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York (NPS, GRD, GRI, SAHI, SAHI digital map) adapted from U.S. Geological Survey Water-Supply Paper maps by Isbister (1966) and Lubke (1964) [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/digital-geologic-gis-map-of-sagamore-hill-national-historic-site-and-vicinity-new-york-nps
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    New York
    Description

    The Digital Geologic-GIS Map of Sagamore Hill National Historic Site and Vicinity, New York is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (sahi_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (sahi_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (sahi_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (sahi_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (sahi_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (sahi_geology_metadata_faq.pdf). Please read the sahi_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (sahi_geology_metadata.txt or sahi_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual _location as presented by this dataset. Users of this data should thus not assume the _location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  6. a

    City of Atlanta Data Visualization Suite

    • hub.arcgis.com
    • opendata.atlantaregional.com
    • +1more
    Updated Apr 30, 2019
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    Georgia Association of Regional Commissions (2019). City of Atlanta Data Visualization Suite [Dataset]. https://hub.arcgis.com/documents/a71c90fbda40400592d861947691708f
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    Dataset updated
    Apr 30, 2019
    Dataset authored and provided by
    Georgia Association of Regional Commissions
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Atlanta
    Description

    The City of Atlanta data visualization suite from ARC & Neighborhood Nexus includes 400 variables all mapped to City of Atlanta neighborhoods, neighborhood planning units (NPUs), and City Council districts’ boundaries. The data includes several City-specific variables such as code enforcement, 911 calls and the results of the recently-conducted windshield survey of housing conditions, as well as hundreds of Census variables like income, poverty, health insurance coverage and disability. When we say “neighborhoods”, we actually mean “Neighborhood Statistical Areas,” which in some cases combine some of Atlanta’s smaller neighborhoods into one.The tools we built include an interactive map, which allows for a deep-dive analysis of all 400 variables, and a dashboard, which is an easy-to-use tool that provides quick comparisons of every neighborhood, neighborhood planning unit, and City Council district to the city as a whole.Visit Neighborhood Nexus and City of Atlanta’s website.

  7. Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter...

    • catalog.data.gov
    • datasets.ai
    Updated Jun 5, 2024
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    National Park Service (2024). Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida (NPS, GRD, GRI, GUIS, GUIS_geomorphology digital map) adapted from U.S. Geological Survey Open File Report maps by Morton and Rogers (2009) and Morton and Montgomery (2010) [Dataset]. https://catalog.data.gov/dataset/digital-geomorphic-gis-map-of-gulf-islands-national-seashore-5-meter-accuracy-and-1-foot-r
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    Dataset updated
    Jun 5, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Description

    The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  8. DWR's Basin Characterization Program

    • data.cnra.ca.gov
    • data.ca.gov
    .zip +3
    Updated Mar 20, 2025
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    California Department of Water Resources (2025). DWR's Basin Characterization Program [Dataset]. https://data.cnra.ca.gov/dataset/dwr-basin-characterization
    Explore at:
    pdf(51906), zip(57527036), pdf(66690), zip(1764587248), file geodatabase(44747133), zip(13492026), zip(5912544), pdf(9223451), pdf(50751), pdf(64794), pdf(64557), pdf(2543702), pdf(20357083), .zip(5376349)Available download formats
    Dataset updated
    Mar 20, 2025
    Dataset authored and provided by
    California Department of Water Resourceshttp://www.water.ca.gov/
    Description

    DWR has a long history of studying and characterizing California’s groundwater aquifers as a part of California’s Groundwater (Bulletin 118). The Basin Characterization Program provides the latest data and information about California’s groundwater basins to help local communities better understand their aquifer systems and support local and statewide groundwater management.

    Under the Basin Characterization Program, new and existing data (AEM, lithology logs, geophysical logs, etc.) will be integrated to create continuous maps and three-dimensional models. To support this effort, new data analysis tools will be developed to create texture models, hydrostratigraphic models, and aquifer flow parameters. Data collection efforts will be expanded to include advanced geologic, hydrogeologic, and geophysical data collection and data digitization and quality control efforts will continue. To continue to support data access and data equity, the Basin Characterization Program will develop new online, GIS-based, visualization tools to serve as a central hub for accessing and exploring groundwater related data in California.

    Additional information can be found on the Basin Characterization Program webpage.

    DWR's Evaluation of Groundwater Resources: Maps and Models

    DWR will undertake local and regional investigations to evaluate California's groundwater resources and develop state-stewarded maps and models. New and existing data will be combined and integrated using the analysis tools described below to develop maps and models to be developed will describe the grain size, the hydrostratigraphic properties, and hydrogeologic conceptual properties of California’s aquifers. These maps and models help groundwater managers understand how groundwater is stored and moves within the aquifer. The models will be state-stewarded, meaning that they will be regularly updated, as new data becomes available, to ensure that up-to-date information is used for groundwater management activities. The first iterations of the following maps and models will be published as they are developed:

    • Texture Models
    • Hydrostratigraphic Models
    • Aquifer Recharge Potential Maps
    • Extent of Important Aquifer Units
    • Depth to Basement
    • Depth to Freshwater

    Local Investigations:

    Regional Investigations:

    • Sacramento Valley
    • Four County Area of San Joaquin Valley (Madera, Fresno, Kings, and Tulare)
    • San Joaquin Valley

    Data Collection, Compilation, and Digitization

    Data Collection

    As a part of the Basin Characterization Program, advanced geologic, hydrogeologic, and geophysical data will be collected to improve our understanding of groundwater basins. Data collected under Basin Characterization are collected at a local, regional, or statewide scale depending on the scope of the study.

    Datasets collected under the Basin Characterization Program can be found under the following resource:

    Digitized Existing Lithology and Geophysical Logs

    Lithology and geophysical logging data have been digitized to support the Statewide AEM Survey Project and will continue to be digitized to support Basin Characterization efforts. All digitized lithology logs with Well Completion Report IDs will be imported back into the OSWCR database.

    Digitized lithology and geophysical logging can be found under the following resource:

    Analysis Tools and Process Documents

    To develop the state-stewarded maps and models outlined above, new tools and process documents will be created to integrate and analyze a wide range of data, including geologic, geophysical, and hydrogeologic information. By combining and assessing various datasets, these tools will help create a more complete picture of California's groundwater basins. All tools, along with guidance documents, will be made publicly available for local groundwater managers to use to support development of maps and models at a local scale. All tools and guidance will be updated as revisions to tools and process documents are made.

    Analysis tools and process documents can be found under the following resource:

    Data Visualization

    Data access equity is a priority for the Basin Characterization Program. To ensure data access equity, the Basin Characterization Program has developed applications and tools to allow data to be visualized without needing access to expensive data visualization software. This list below provides links and descriptions for the Basin Characterization's suite of data viewers.

    SGMA Data Viewer: Basin Characterization tab: Provides maps, depth slices, and profiles of Basin Characterization maps, models, and datasets, including the following:

    • Aquifer Recharge Potential Maps
    • Subsurface Texture Model Depth Slices
    • Statewide AEM Survey Texture Depth Slices
    • Lithology Log Location Maps
    • Geophysical Logs Location Maps
    • Statewide AEM Survey Profile Images

    3D AEM Data Viewer: Displays the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs, in a three-dimensional space.

    DWR's Subsurface Viewer: Provides a map view and profile view of the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs. The map view dynamically shows the exact location of AEM data displayed.

    Basin Characterization Exchange

    The Basin Characterization Exchange (BCX) is a meeting series and network space for the Basin Characterization community to exchange ideas, share lessons learned, define needed guidance, and highlight research topics. The BCX is open to federal, state, and local agencies, consultants, NGOs, academia, and interested parties who participate in Basin Characterization efforts. The BCX also plays a pivotal role in advancing the Basin Characterization Program’s activities and goals. BCX meetings will include regular updates from the Basin Characterization Program and participants can provide feedback and recommendations. Participants will also be provided with early opportunities to test data analysis tools and submit comments on draft process and guidance documents. BCX meetings are (generally) held the 3rd Tuesday of the month from 12:30 - 1:30 pm (PST).

    Please email your contact information to Basin.Characterization@water.ca.gov if you’re interested in attending BCX meetings and to join the BCX listserv.

  9. d

    California State Waters Map Series--Hueneme Canyon Web Services

    • datasets.ai
    • search.dataone.org
    • +1more
    55
    Updated Oct 8, 2024
    + more versions
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    Department of the Interior (2024). California State Waters Map Series--Hueneme Canyon Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-hueneme-canyon-web-services
    Explore at:
    55Available download formats
    Dataset updated
    Oct 8, 2024
    Dataset authored and provided by
    Department of the Interior
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Hueneme Canyon map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Hueneme Canyon map area data layers. Data layers are symbolized as shown on the associated map sheets.

  10. a

    Census Program Data Viewer

    • catalogue.arctic-sdi.org
    Updated Nov 11, 2020
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    Census Program Data Viewer [Dataset]. https://catalogue.arctic-sdi.org/geonetwork/srv/search?keyword=Maps
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    Dataset updated
    Nov 11, 2020
    Description

    The Census Program Data Viewer (CPDV) is an advanced web-based data visualization tool that helps make statistical information more interpretable by presenting key indicators in a statistical dashboard. It also enables users to easily compare indicator values and identify relationships between indicators.

  11. TopoBathy

    • cacgeoportal.com
    • hub.arcgis.com
    • +2more
    Updated Apr 10, 2014
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    Esri (2014). TopoBathy [Dataset]. https://www.cacgeoportal.com/datasets/c753e5bfadb54d46b69c3e68922483bc
    Explore at:
    Dataset updated
    Apr 10, 2014
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This dynamic World Elevation TopoBathy service combines topography (land elevation) and bathymetry (water depths) around the world. Heights are based on multiple sources and are orthometric (sea level = 0, and bathymetric values are negative downward from sea level). The source data of land elevation in this service is same as in the Terrain layer. When possible, the water areas are represented by the best available bathymetry. What can you do with this layer?Use for Visualization: This layer is generally not optimal for direct visualization. By default, 32 bit floating point values are returned, resulting in higher bandwidth requirements. Therefore, usage should be limited to applications requiring elevation data values. Alternatively, client applications can select additional functions, applied on the server, that return rendered data. For visualizations such as hillshade or elevation tinted hillshade, consider using the appropriate server-side function defined on this service. Use for Analysis: Yes. This layer provides data as floating point elevation values suitable for use in analysis. NOTE: This image services combine data from different sources and resample the data dynamically to the requested projection, extent and pixel size. For analyses using ArcGIS Desktop, you can filter a dataset, specify the projection, extent and cell size using the Make Image Server Layer geoprocessing tool. Server Functions: This layer has server functions defined for the following elevation derivatives. In ArcGIS desktop, server function can be invoked from Layer Properties - Processing Templates.

    Slope Degrees Slope Percentage Hillshade Multi-Directional Hillshade Elevation Tinted HillshadeSlope MapData Sources and Coverage: This layer is compiled from a variety of best available sources from several data providers. To see the coverage and extents of various datasets comprising this service in an interactive map, see Elevation Coverage Map.Mosaic Method: This image service uses a default mosaic method of "By Attribute”, using Field 'Best' and target of 0. Each of the rasters has been attributed with ‘Best’ field value that is generally a function of the pixel size such that higher resolution datasets are displayed at higher priority. Other mosaic methods can be set, but care should be taken as the order of the rasters may change. Where required, queries can also be set to display only specific datasets such as only NED or the lock raster mosaic rule used to lock to a specific dataset.Accuracy: The accuracy of these services will vary as a function of location and data source. Please refer to the metadata available in the services, and follow the links to the original sources for further details. An estimate of CE90 and LE90 is included as attributes, where available.This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single request. This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.Disclaimer: Bathymetry data sources are not to be used for navigation/safety at sea.

  12. d

    California State Waters Map Series--Offshore of Fort Ross Web Services

    • datasets.ai
    • data.usgs.gov
    • +2more
    55
    Updated Sep 23, 2024
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    Department of the Interior (2024). California State Waters Map Series--Offshore of Fort Ross Web Services [Dataset]. https://datasets.ai/datasets/california-state-waters-map-series-offshore-of-fort-ross-web-services
    Explore at:
    55Available download formats
    Dataset updated
    Sep 23, 2024
    Dataset authored and provided by
    Department of the Interior
    Area covered
    California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore Fort Ross map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore Fort Ross map area data layers. Data layers are symbolized as shown on the associated map sheets.

  13. Digital Geomorphic-GIS Map of Cape Lookout National Seashore, North Carolina...

    • catalog.data.gov
    • datasets.ai
    Updated Jun 4, 2024
    + more versions
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    National Park Service (2024). Digital Geomorphic-GIS Map of Cape Lookout National Seashore, North Carolina (1:24,000 scale 2008 mapping) (NPS, GRD, GRI, CALO, CALO_geomorphology digital map) adapted from North Carolina Geological Survey unpublished digital data and maps by Coffey and Nickerson (2008) [Dataset]. https://catalog.data.gov/dataset/digital-geomorphic-gis-map-of-cape-lookout-national-seashore-north-carolina-1-24000-scale-
    Explore at:
    Dataset updated
    Jun 4, 2024
    Dataset provided by
    National Park Servicehttp://www.nps.gov/
    Area covered
    Cape Lookout, North Carolina
    Description

    The Digital Geomorphic-GIS Map of Cape Lookout National Seashore, North Carolina (1:24,000 scale 2008 mapping) is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) an ESRI file geodatabase (calo_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro 3.X map file (.mapx) file (calo_geomorphology.mapx) and individual Pro 3.X layer (.lyrx) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (calo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (calo_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (calo_geomorphology_metadata_faq.pdf). Please read the calo_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: North Carolina Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (calo_geomorphology_metadata.txt or calo_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS Pro, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

  14. a

    Global Visualization Viewer (GloVis

    • hub.arcgis.com
    • data.amerigeoss.org
    • +7more
    Updated Nov 9, 2018
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    AmeriGEOSS (2018). Global Visualization Viewer (GloVis [Dataset]. https://hub.arcgis.com/datasets/c8997996dba34793911305ef46b7b45b
    Explore at:
    Dataset updated
    Nov 9, 2018
    Dataset authored and provided by
    AmeriGEOSS
    Description

    GloVisThe USGS Global Visualization Viewer (GloVis) is an online search and order tool for selected satellite data. Through a graphic map display, the user can select any area of interest and immediately view all available browse images for the specified location. From the browse image viewer page, the user may either navigate to view adjacent scene locations or select a new area of interest. GloVis also offers additional features such as cloud cover limits, date limits, user-specified map layer displays, scene list curation, and access to metadata. The viewer provides access to Thermal Infrared (TIR) and Visible and Near Infrared (VNIR) data from the LP DAAC’s ASTER L1T data product. A selection of data collected by Landsat satellites and other remote sensing instruments are also available. A full listing of available data products can be found in the GloVis FAQ’s.Guide · Launch GloVis

  15. Data for: Assessing the Cognition of Movement Trajectory Visualizations:...

    • data.niaid.nih.gov
    • search.dataone.org
    • +2more
    zip
    Updated Apr 11, 2023
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    Crystal Bae; Somayeh Dodge; Teresa Gonzalez (2023). Data for: Assessing the Cognition of Movement Trajectory Visualizations: Interpreting Speed and Direction [Dataset]. http://doi.org/10.25349/D9BC9V
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    zipAvailable download formats
    Dataset updated
    Apr 11, 2023
    Dataset provided by
    University of California, Santa Barbara
    Authors
    Crystal Bae; Somayeh Dodge; Teresa Gonzalez
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Description

    This paper evaluates cognitively plausible geovisualization techniques for mapping movement data. With the widespread increase in the availability and quality of space-time data capturing movement trajectories of individuals, meaningful representations are needed to properly visualize and communicate trajectory data and complex movement patterns using geographic displays. Many visualization and visual analytics approaches have been proposed to map movement trajectories (e.g. space-time paths, animations, trajectory lines, etc.). However, little is known about how effective these complex visualizations are in capturing important aspects of movement data. Given the complexity of movement data which involves space, time, and context dimensions, it is essential to evaluate the communicative efficiency and efficacy of various visualization forms in helping people understand movement data. This study assesses the effectiveness of static and dynamic movement displays as well as visual variables in communicating movement parameters along trajectories, such as speed and direction. To do so, a web-based survey is conducted to evaluate the understanding of movement visualizations by a non-specialist audience. This and future studies contribute fundamental insights into the cognition of movement visualizations and inspire new methods for the empirical evaluation of geovisualizations. Methods The movement visualization files used in the study were generated using the DynamoVis desktop software, available on Github: https://github.com/move-ucsb/DynamoVis Static visualizations were generated as exported screenshots from the software. Dynamic visualizations were generated as exported videos from the software (animated screenshots). Both types of visualizations were created using the built-in export features of DynamoVis. After export, images and videos were edited to add further contextual information, including start and stop icons on the static images, as well as scale bars on all visualizations for contextual information. The survey study design and data collection and analysis methods are described in the associated manuscript. A copy of the survey instrument and an anonymized survey report are included in the data folder.

  16. a

    HOU-UASI MCU Dashboard Map

    • uasi-gis-wg-houuasi.hub.arcgis.com
    Updated Jan 11, 2024
    + more versions
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    Houston UASI (2024). HOU-UASI MCU Dashboard Map [Dataset]. https://uasi-gis-wg-houuasi.hub.arcgis.com/maps/e9d217dcf8b84c58af54bebce4d25d72
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    Dataset updated
    Jan 11, 2024
    Dataset authored and provided by
    Houston UASI
    Area covered
    Description

    WEB MAP: DASHBOARD This is a web map. This is the main web map used in the Mobile Command Unit Survey Dashboard application.This survey is conducted by the Houston UASI Mobile Command Unit Work Group, dedicated to advancing emergency response capabilities in our region. The data provided will be accessible through a comprehensive dashboard, empowering each member with dynamic visualization tools for informed decision-making.

  17. H

    SWOT Data Visualization tool for developing synthetic SWOT discharges based...

    • hydroshare.org
    • beta.hydroshare.org
    zip
    Updated Apr 14, 2021
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    SWOT Data Visualization tool for developing synthetic SWOT discharges based on spatial-temporal sampling and estimated discharge uncertainty [Dataset]. https://www.hydroshare.org/resource/d9d2f636f64944f79f2bcb54e7fbfc4c
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    zip(44.9 MB)Available download formats
    Dataset updated
    Apr 14, 2021
    Dataset provided by
    HydroShare
    Authors
    Bhavya Duvvuri
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Interactive map to view SWOT river reaches, USGS gauges, SWOT orbit, and generate, analyze synthetic SWOT data

  18. d

    California State Waters Map Series--Offshore of Point Conception Web...

    • catalog.data.gov
    • data.usgs.gov
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). California State Waters Map Series--Offshore of Point Conception Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-offshore-of-point-conception-web-services
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    Point Conception, California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Point Conception map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Point Conception map area data layers. Data layers are symbolized as shown on the associated map sheets.

  19. d

    Data from: California State Waters Map Series--Offshore of Tomales Point Web...

    • catalog.data.gov
    • search.dataone.org
    • +2more
    Updated Jul 6, 2024
    + more versions
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    U.S. Geological Survey (2024). California State Waters Map Series--Offshore of Tomales Point Web Services [Dataset]. https://catalog.data.gov/dataset/california-state-waters-map-series-offshore-of-tomales-point-web-services
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    Dataset updated
    Jul 6, 2024
    Dataset provided by
    United States Geological Surveyhttp://www.usgs.gov/
    Area covered
    California
    Description

    In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The program supports a large number of coastal-zone- and ocean-management issues, including the California Marine Life Protection Act (MLPA) (California Department of Fish and Wildlife, 2008), which requires information about the distribution of ecosystems as part of the design and proposal process for the establishment of Marine Protected Areas. A focus of CSMP is to map California’s State Waters with consistent methods at a consistent scale. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. It is emphasized that the more interpretive habitat and geology data rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. This approach and CSMP planning is based in part on recommendations of the Marine Mapping Planning Workshop (Kvitek and others, 2006), attended by coastal and marine managers and scientists from around the state. That workshop established geographic priorities for a coastal mapping project and identified the need for coverage of “lands” from the shore strand line (defined as Mean Higher High Water; MHHW) out to the 3-nautical-mile (5.6-km) limit of California’s State Waters. Unfortunately, surveying the zone from MHHW out to 10-m water depth is not consistently possible using ship-based surveying methods, owing to sea state (for example, waves, wind, or currents), kelp coverage, and shallow rock outcrops. Accordingly, some of the data presented in this series commonly do not cover the zone from the shore out to 10-m depth. This data is part of a series of online U.S. Geological Survey (USGS) publications, each of which includes several map sheets, some explanatory text, and a descriptive pamphlet. Each map sheet is published as a PDF file. Geographic information system (GIS) files that contain both ESRI ArcGIS raster grids (for example, bathymetry, seafloor character) and geotiffs (for example, shaded relief) are also included for each publication. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html (last accessed September 20, 2013). The California Seafloor Mapping Program is a collaborative venture between numerous different federal and state agencies, academia, and the private sector. CSMP partners include the California Coastal Conservancy, the California Ocean Protection Council, the California Department of Fish and Wildlife, the California Geological Survey, California State University at Monterey Bay’s Seafloor Mapping Lab, Moss Landing Marine Laboratories Center for Habitat Studies, Fugro Pelagos, Pacific Gas and Electric Company, National Oceanic and Atmospheric Administration (NOAA, including National Ocean Service–Office of Coast Surveys, National Marine Sanctuaries, and National Marine Fisheries Service), U.S. Army Corps of Engineers, the Bureau of Ocean Energy Management, the National Park Service, and the U.S. Geological Survey. These web services for the Offshore of Tomales Point map area includes data layers that are associated to GIS and map sheets available from the USGS CSMP web page at https://walrus.wr.usgs.gov/mapping/csmp/index.html. Each published CSMP map area includes a data catalog of geographic information system (GIS) files; map sheets that contain explanatory text; and an associated descriptive pamphlet. This web service represents the available data layers for this map area. Data was combined from different sonar surveys to generate a comprehensive high-resolution bathymetry and acoustic-backscatter coverage of the map area. These data reveal a range of physiographic including exposed bedrock outcrops, large fields of sand waves, as well as many human impacts on the seafloor. To validate geological and biological interpretations of the sonar data, the U.S. Geological Survey towed a camera sled over specific offshore locations, collecting both video and photographic imagery; these “ground-truth” surveying data are available from the CSMP Video and Photograph Portal at https://doi.org/10.5066/F7J1015K. The “seafloor character” data layer shows classifications of the seafloor on the basis of depth, slope, rugosity (ruggedness), and backscatter intensity and which is further informed by the ground-truth-survey imagery. The “potential habitats” polygons are delineated on the basis of substrate type, geomorphology, seafloor process, or other attributes that may provide a habitat for a specific species or assemblage of organisms. Representative seismic-reflection profile data from the map area is also include and provides information on the subsurface stratigraphy and structure of the map area. The distribution and thickness of young sediment (deposited over the past about 21,000 years, during the most recent sea-level rise) is interpreted on the basis of the seismic-reflection data. The geologic polygons merge onshore geologic mapping (compiled from existing maps by the California Geological Survey) and new offshore geologic mapping that is based on integration of high-resolution bathymetry and backscatter imagery seafloor-sediment and rock samplesdigital camera and video imagery, and high-resolution seismic-reflection profiles. The information provided by the map sheets, pamphlet, and data catalog has a broad range of applications. High-resolution bathymetry, acoustic backscatter, ground-truth-surveying imagery, and habitat mapping all contribute to habitat characterization and ecosystem-based management by providing essential data for delineation of marine protected areas and ecosystem restoration. Many of the maps provide high-resolution baselines that will be critical for monitoring environmental change associated with climate change, coastal development, or other forcings. High-resolution bathymetry is a critical component for modeling coastal flooding caused by storms and tsunamis, as well as inundation associated with longer term sea-level rise. Seismic-reflection and bathymetric data help characterize earthquake and tsunami sources, critical for natural-hazard assessments of coastal zones. Information on sediment distribution and thickness is essential to the understanding of local and regional sediment transport, as well as the development of regional sediment-management plans. In addition, siting of any new offshore infrastructure (for example, pipelines, cables, or renewable-energy facilities) will depend on high-resolution mapping. Finally, this mapping will both stimulate and enable new scientific research and also raise public awareness of, and education about, coastal environments and issues. Web services were created using an ArcGIS service definition file. The ArcGIS REST service and OGC WMS service include all Offshore of Tomales Point map area data layers. Data layers are symbolized as shown on the associated map sheets.

  20. Terrain

    • opendata.rcmrd.org
    • pacificgeoportal.com
    • +11more
    Updated Jul 4, 2013
    + more versions
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    Esri (2013). Terrain [Dataset]. https://opendata.rcmrd.org/datasets/58a541efc59545e6b7137f961d7de883
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    Dataset updated
    Jul 4, 2013
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This dynamic World Elevation Terrain service provides numeric values representing ground surface heights, based on a digital terrain model (DTM). The ground heights are based on multiple sources. Heights are orthometric (sea level = 0), and water bodies that are above sea level have approximated nominal water heights.What can you do with this layer?Use for Visualization: This layer is generally not optimal for direct visualization. By default, 32 bit floating point values are returned, resulting in higher bandwidth requirements. Therefore, usage should be limited to applications requiring elevation data values. Alternatively, client applications can select from numerous additional functions, applied on the server, that return rendered data. For visualizations such as multi-directional hillshade, hillshade, elevation tinted hillshade, and slope, consider using the appropriate server-side function defined on this service.Use for Analysis: Yes. This layer provides data as floating point elevation values suitable for use in analysis.Note: This image services combine data from different sources and resample the data dynamically to the requested projection, extent and pixel size. For analyses using ArcGIS Desktop, you can filter a dataset, specify the projection, extent and cell size using the Make Image Server Layer geoprocessing tool.Server Functions: This layer has server functions defined for the following elevation derivatives. In ArcGIS desktop, server function can be invoked from Layer Properties - Processing Templates.

    Slope Degrees Slope Percent Aspect Ellipsoidal height Hillshade Multi-Directional Hillshade Dark Multi-Directional Hillshade Elevation Tinted Hillshade Slope Map Aspect Map Data Sources and Coverage: This layer is compiled from a variety of best available sources from several data providers. To see the coverage and extents of various datasets comprising this service in an interactive map, see Elevation Coverage Map.Mosaic Method: This image service uses a default mosaic method of "By Attribute”, using Field 'Best' and target of 0. Each of the rasters has been attributed with ‘Best’ field value that is generally a function of the pixel size such that higher resolution datasets are displayed at higher priority. Other mosaic methods can be set, but care should be taken as the order of the rasters may change. Where required, queries can also be set to display only specific datasets such as only NED or the lock raster mosaic rule used to lock to a specific dataset.Accuracy: The accuracy of these services will vary as a function of location and data source. Please refer to the metadata available in the services, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes, where available.This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single request.This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

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Chan, Wai Chung Wilson (2023). Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project [Dataset]. http://doi.org/10.5683/SP3/7RVB70

Development of Interactive Data Visualization Tool for the Predictive Ecosystem Mapping Project

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Dataset updated
Dec 28, 2023
Dataset provided by
Borealis
Authors
Chan, Wai Chung Wilson
Description

Biogeoclimatic Ecosystem Classification (BEC) system is the ecosystem classification adopted in the forest management within British Columbia based on vegetation, soil, and climate characteristics whereas Site Series is the smallest unit of the system. The Ministry of Forests, Lands, Natural Resource Operations and Rural Development held under the Government of British Columbia (“the Ministry”) developed a web-based tool known as BEC Map for maintaining and sharing the information of the BEC system, but the Site Series information was not included in the tool due to its quantity and complexity. In order to allow users to explore and interact with the information, this project aimed to develop a web-based tool with high data quality and flexibility to users for the Site Series classes using the “Shiny” and “Leaflet” packages in R. The project started with data classification and pre-processing of the raster images and attribute tables through identification of client requirements, spatial database design and data cleaning. After data transformation was conducted, spatial relationships among these data were developed for code development. The code development included the setting-up of web map and interactive tools for facilitating user friendliness and flexibility. The codes were further tested and enhanced to meet the requirements of the Ministry. The web-based tool provided an efficient and effective platform to present the complicated Site Series features with the use of Web Mapping System (WMS) in map rendering. Four interactive tools were developed to allow users to examine and interact with the information. The study also found that the mode filter performed well in data preservation and noise minimization but suffered from long processing time and creation of tiny sliver polygons.

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