Attachment Viewer allows app viewers to explore images stored as feature attachments. Present your photos, videos, and PDF files collected using ArcGIS Field Maps or Survey 123 workflows. Choose an attachment focused layout to display individual images beside your map or a map focused layout to highlight your map beside a gallery of images.Examples:Review photos collected during emergency response damage inspectionsDisplay the results of field data collection and support the downloading of images for inclusion in a reportPresent a map of land parcel along with associated documents stored as attachmentsData RequirementsThis web app includes the capability to view attachments of a hosted feature service or an ArcGIS Server feature service (10.8 or greater). Currently the attachment viewer will display jpeg, jpg, png, gif, mp4, mov, quicktime, pdf in the viewer window. All other attachment types are displayed as a link.Key App CapabilitiesMap focused layout - Display the map in the main panel of the app with a gallery of attachmentsAttachment focused layout - Display one attachment at a time in the main panel of the app with the map on the sideFeature selection - Allow app viewers to select features in the map and view associated attachmentsReview data - Enable tools to review and update existing recordsNavigation boundary - Keep the area in the map in focus by using a navigation boundary or disabling the ability to scrollZoom, pan, download attachments - Allow app viewers to interact with and download attachmentsHome, Zoom Controls, Legend, Layer List, SearchSupportabilityThis web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

This dataset contains the West Siberian Lowland (WSL) peatland GIS data collection. The collection covers the entire West Siberian lowland and was compiled from a wide array of data under the auspices of the NSF-funded Sensitivity of the West Siberian Lowland to Past and Present Climate project (Smith et al., 2000; Smith et al., 2004). Detailed physical characteristics of 9,691 individual peatlands (patches) were obtained from previously unpublished Russian field and ancillary map data, previously published depth measurements, and field depth and core measurements taken throughout the region during field campaigns in 1999, 2000, and 2001. The data collection features eight layers containing the detailed peatland inventory, political, and hydrographic information. Point data consist of field and laboratory measurements of peat depth, ash content, and bulk density. This research was funded by the National Science Foundation (NSF) Office of Polar Programs (OPP), grant number OPP-9818496.

The Fundamental GIS: Digital Chart of China, 1:1M, Version 1 consists of vector maps of China and surrounding areas. The maps include roads, railroads, drainage systems, contours, populated places, and urbanized areas for China proper, as well as for China and neighboring countries. The maps are at a scale of one to one million (1:1M). This data set is produced in collaboration with the University of Washington as part of the China in Time and Space (CITAS) project and the Columbia University Center for International Earth Science Information Network (CIESIN).

The RBDC Metadata contains information related to the fields in each of the datasets. It includes a unique identifier for each field, field name and plain English descriptions. Additional metadata is also provided in the portal’s ArcGIS Online description (where the RBDC data is hosted) including Open Data License and terms of use. Fields in each dataset may vary, therefore the metadata is provided per table in a downloadable Excel Spreadsheet. Each tab on this document corresponds to the RBDC open dataset table unique identifier.

Summary: How to configure Esri Collector for ArcGIS with a Bad Elf GPS Receiver for High-Accuracy Field Data Collection Storymap metadata page: URL forthcoming Possible K-12 Next Generation Science standards addressed:Grade level(s) 1: Standard 1-LS3-1 - Heredity: Inheritance and Variation of Traits - Make observations to construct an evidence-based account that young plants and animals are like, but not exactly like, their parentsGrade level(s) 4: Standard 4-ESS2-2 - Earth’s Systems - Analyze and interpret data from maps to describe patterns of Earth’s featuresGrade level(s) 5: Standard 5-ESS1-2 - Earth’s Place in the Universe - Represent data in graphical displays to reveal patterns of daily changes in length and direction of shadows, day and night, and the seasonal appearance of some stars in the night skyGrade level(s) 6-8: Standard MS-LS4-5 - Biological Evolution: Unity and Diversity - Gather and synthesize information about technologies that have changed the way humans influence the inheritance of desired traits in organisms.Grade level(s) 6-8: Standard MS-LS4-6 - Biological Evolution: Unity and Diversity - Use mathematical representations to support explanations of how natural selection may lead to increases and decreases of specific traits in populations over timeGrade level(s) 6-8: Standard MS-ESS1-3 - Earth’s Place in the Universe - Analyze and interpret data to determine scale properties of objects in the solar systemGrade level(s) 6-8: Standard MS-ESS2-2 - Earth’s Systems - Construct an explanation based on evidence for how geoscience processes have changed Earth’s surface at varying time and spatial scalesGrade level(s) 9-12: Standard HS-LS4-4 - Biological Evolution: Unity and Diversity - Construct an explanation based on evidence for how natural selection leads to adaptation of populationsGrade level(s) 9-12: Standard HS-ESS2-1 - Earth’s Systems - Develop a model to illustrate how Earth’s internal and surface processes operate at different spatial and temporal scales to form continental and ocean-floor features.Most frequently used words:featurebadelfselectgpsApproximate Flesch-Kincaid reading grade level: 9.9. The FK reading grade level should be considered carefully against the grade level(s) in the NGSS content standards above.

This dataset is a LAS (industry-standard binary format for storing large point clouds) dataset containing light detection and ranging (LiDAR) data and sonar data representing the beach and near-shore topography of Lake Superior at Minnesota Point, Duluth, Minnesota. Average point spacing of the LAS files in the dataset are as follows: LiDAR, 0.137 meters (m); multi-beam sonar, 1.029 m; single-beam sonar, 0.999 m. The LAS dataset was used to create a 10-m (32.8084 feet) digital elevation model (DEM) of the approximately 5.9 square kilometer (2.3 square mile) surveyed area using the "LAS dataset to raster" tool in Esri ArcGIS, version 10.7. LiDAR data were collected August 10, 2019 using a boat-mounted Optech ILRIS scanner and methodology similar to that described by Huizinga and Wagner (2019). Multi-beam sonar data were collected August 7-11, 2019 using an R2Sonic 2024 sonar unit and methodology similar to that described by Richards and Huizinga (2018). Single-beam sonar data were collected August 27-28, 2019 using a CEESCOPE single-beam echosounder and methodology similar to that described by Wilson and Richards (2006).

This is a national data collection of data resources managed by the Bureau of Ocean Energy Management (BOEM) for the Outer Continental Shelf (OCS). The data collection is designated as a National Geospatial Data Asset (NGDA) and includes: OCS BOEM Offshore Boundary Lines (Submerged Lands Act Boundary, OCSLA Limit of “8(g) Zone,” and Continental Shelf Boundary), OCS Protraction Polygons - 1st Division, OCS Gulf of Mexico NAD27 Protraction Polygons - 1st Division, OCS Block Polygons - 2nd Division, OCS Gulf of Mexico NAD27 Block Polygons - 2nd Division, and Aliquot 16ths Polygons - 3rd Division.All polygons are clipped to the Submerged Land Act Boundary and Continental Shelf Boundaries reflecting federal jurisdiction. The NAD27 Gulf of Mexico Protractions and Blocks have a different protraction and block configuration when compared to the OCS Protraction Polygons - 1st Division and OCS Block Polygons - 2nd Division. The NAD27 Gulf of Mexico data is used for Oil and Gas leasing.These data were created in the applicable NAD83 UTM or NAD27 UTM/SPCS Projection and re-projected to GCS WGS84 (EPSG 4326) for management in BOEM"s enterprise GIS. However, the services in this collection have been published in WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857). Because GIS projection and topology functions can change or generalize coordinates,these data are NOT an OFFICIAL record for the exact boundaries. These data are to be used for Cartographic purposes only and should not be used to calculate area.Layers MetadataOCS BOEM Offshore Boundary LinesOCS Protraction Polygons - 1st DivisionOCS Gulf of Mexico NAD27 Protraction Polygons - 1st DivisionOCS Block Polygons - 2nd DivisionOCS Gulf of Mexico NAD27 Block Polygons - 2nd DivisionAliquot 16ths Polygons - 3rd Division

World Imagery provides one meter or better satellite and aerial imagery for most of the world’s landmass and lower resolution satellite imagery worldwide. The map is currently comprised of the following sources:Worldwide 15-m resolution TerraColor imagery at small and medium map scales.Maxar imagery basemap products around the world: Vivid Premium at 15-cm HD resolution for select metropolitan areas, Vivid Advanced 30-cm HD for more than 1,000 metropolitan areas, and Vivid Standard from 1.2-m to 0.6-cm resolution for the most of the world, with 30-cm HD across the United States and parts of Western Europe. More information on the Maxar products is included below. High-resolution aerial photography contributed by the GIS User Community. This imagery ranges from 30-cm to 3-cm resolution. You can contribute your imagery to this map and have it served by Esri via the Community Maps Program.Maxar Basemap ProductsVivid PremiumProvides committed image currency in a high-resolution, high-quality image layer over defined metropolitan and high-interest areas across the globe. The product provides 15-cm HD resolution imagery.Vivid AdvancedProvides committed image currency in a high-resolution, high-quality image layer over defined metropolitan and high-interest areas across the globe. The product includes a mix of native 30-cm and 30-cm HD resolution imagery.Vivid StandardProvides a visually consistent and continuous image layer over large areas through advanced image mosaicking techniques, including tonal balancing and seamline blending across thousands of image strips. Available from 1.2-m down to 30-cm HD. More on Maxar HD.Updates and CoverageYou can use the World Imagery Updates app to learn more about recent updates and map coverage.CitationsThis layer includes imagery provider, collection date, resolution, accuracy, and source of the imagery. With the Identify tool in ArcGIS Desktop or the ArcGIS Online Map Viewer you can see imagery citations. Citations returned apply only to the available imagery at that location and scale. You may need to zoom in to view the best available imagery. Citations can also be accessed in the World Imagery with Metadata web map.UseYou can add this layer to the ArcGIS Online Map Viewer, ArcGIS Desktop, or ArcGIS Pro. To view this layer with a useful reference overlay, open the Imagery Hybrid web map.FeedbackHave you ever seen a problem in the Esri World Imagery Map that you wanted to report? You can use the Imagery Map Feedback web map to provide comments on issues. The feedback will be reviewed by the ArcGIS Online team and considered for one of our updates.

The China Administrative Regions GIS Data: 1:1M, County Level, 1 July 1990 consists of geographic boundary data for the administrative regions of China as of 1 July 1990. The data includes the geographical location, area, administrative division code, and county and island name. The data are at a scale of one to one million (1:1M) at the national, provincial, and county level. This data set is produced in collaboration with the Center for International Earth Science Information Network (CIESIN), Chinese Academy of Surveying and Mapping (CASM), and the University of Washington as part of the China in Time and Space (CITAS) project.

Survey123 for ArcGIS is a simple and intuitive form-centric field data gathering solution. This seminar teaches you about Survey123. The presenters demonstrate how to create both simple and more sophisticated surveys, collect data over the web and in the field, analyze and view the survey results with Survey123's reporting capabilities, and how survey data is integrated with the ArcGIS platform.This seminar was developed to support the following:Survey123 for ArcGIS

The northeastern North Carolina coastal system, from False Cape, Virginia, to Cape Lookout, North Carolina, has been studied by a cooperative research program that mapped the Quaternary geologic framework of the estuaries, barrier islands, and inner continental shelf. This information provides a basis to understand the linkage between geologic framework, physical processes, and coastal evolution at time scales from storm events to millennia. The study area attracts significant tourism to its parks and beaches, contains a number of coastal communities, and supports a local fishing industry, all of which are impacted by coastal change. Knowledge derived from this research program can be used to mitigate hazards and facilitate effective management of this dynamic coastal system. This regional mapping project produced spatial datasets of high-resolution geophysical (bathymetry, backscatter intensity, and seismic reflection) and sedimentary (core and grab-sample) data. The high-resolution geophysical data were collected during numerous surveys within the back-barrier estuarine system, along the barrier island complex, in the nearshore, and along the inner continental shelf. Sediment cores were taken on the mainland and along the barrier islands, and both cores and grab samples were taken on the inner shelf. Data collection was a collaborative effort between the U.S. Geological Survey (USGS) and several other institutions including East Carolina University (ECU), the North Carolina Geological Survey, and the Virginia Institute of Marine Science (VIMS). The high-resolution geophysical data of the inner continental shelf were collected during six separate surveys conducted between 1999 and 2004 (four USGS surveys north of Cape Hatteras: 1999-045-FA, 2001-005-FA, 2002-012-FA, 2002-013-FA, and two USGS surveys south of Cape Hatteras: 2003-003-FA and 2004-003-FA) and cover more than 2600 square kilometers of the inner shelf. Single-beam bathymetry data were collected north of Cape Hatteras in 1999 using a Furuno fathometer. Swath bathymetry data were collected on all other inner shelf surveys using a SEA, Ltd. SwathPLUS 234-kHz bathymetric sonar. Chirp seismic data as well as sidescan-sonar data were collected with a Teledyne Benthos (Datasonics) SIS-1000 north of Cape Hatteras along with boomer seismic reflection data (cruises 1999-045-FA, 2001-005-FA, 2002-012-FA and 2002-013-FA). An Edgetech 512i was used to collect chirp seismic data south of Cape Hatteras (cruises 2003-003-FA and 2004-003-FA) along with a Klein 3000 sidescan-sonar system. Sediment samples were collected with a Van Veen grab sampler during four of the USGS surveys (1999-045-FA, 2001-005-FA, 2002-013-FA, and 2004-003-FA). Additional sediment core data along the inner shelf are provided from previously published studies. A cooperative study, between the North Carolina Geological Survey and the Minerals Management Service (MMS cores), collected vibracores along the inner continental shelf offshore of Nags Head, Kill Devils Hills and Kitty Hawk, North Carolina in 1996. The U.S. Army Corps of Engineers collected vibracores along the inner shelf offshore of Dare County in August 1995 (NDC cores) and July-August 1995 (SNL cores). These cores are curated by the North Carolina Geological Survey and were used as part of the ground validation process in this study. Nearshore geophysical and core data were collected by the Virginia Institute of Marine Science. The nearshore is defined here as the region between the 10-m isobath and the shoreline. High-resolution bathymetry, backscatter intensity, and chirp seismic data were collected between June 2002 and May 2004. Vibracore samples were collected in May and July 2005. Shallow subsurface geophysical data were acquired along the Outer Banks barrier islands using a ground-penetrating radar (GPR) system. Data were collected by East Carolina University from 2002 to 2005. Rotasonic cores (OBX cores) from five drilling operations were collected from 2002 to 2006 by the North Carolina Geological Survey as part of the cooperative study with the USGS. These cores are distributed throughout the Outer Banks as well as the mainland. The USGS collected seismic data for the Quaternary section within the Albemarle-Pamlico estuarine system between 2001 and 2004 during six surveys (2001-013-FA, 2002-015-FA, 2003-005-FA , 2003-042-FA, 2004-005-FA, and 2004-006-FA). These surveys used Geopulse Boomer and Knudsen Engineering Limited (KEL) 320BR Chirp systems, except cruise 2003-042-FA, which used an Edgetech 424 Chirp and a boomer system. The study area includes Albemarle Sound and selected tributary estuaries such as the South, Pungo, Alligator, and Pasquotank Rivers; Pamlico Sound and trunk estuaries including the Neuse and Pamlico Rivers; and back-barrier sounds including Currituck, Croatan, Roanoke, Core, and Bogue.

The USDA Long-Term Agroecosystem Research was established to develop national strategies for sustainable intensification of agricultural production. As part of the Agricultural Research Service, the LTAR Network incorporates numerous geographies consisting of experimental areas and locations where data are being gathered. Starting in early 2019, two working groups of the LTAR Network (Remote Sensing and GIS, and Data Management) set a major goal to jointly develop a geodatabase of LTAR Standard GIS Data Layers. The purpose of the geodatabase was to enhance the Network's ability to utilize coordinated, harmonized datasets and reduce redundancy and potential errors associated with multiple copies of similar datasets. Project organizers met at least twice with each of the 18 LTAR sites from September 2019 through December 2020, compiling and editing a set of detailed geospatial data layers comprising a geodatabase, describing essential data collection areas within the LTAR Network. The LTAR Standard GIS Data Layers geodatabase consists of geospatial data that represent locations and areas associated with the LTAR Network as of late 2020, including LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This geodatabase was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. The creation of the geodatabase began with initial requests to LTAR site leads and data managers for geospatial data, followed by meetings with each LTAR site to review the initial draft. Edits were documented, and the final draft was again reviewed and certified by LTAR site leads or their delegates. Revisions to this geodatabase will occur biennially, with the next revision scheduled to be published in 2023. Resources in this dataset:Resource Title: LTAR Standard GIS Data Layers, 2020 version, File Geodatabase. File Name: LTAR_Standard_GIS_Layers_v2020.zipResource Description: This file geodatabase consists of authoritative GIS data layers of the Long-Term Agroecosystem Research Network. Data layers include: LTAR site locations, LTAR site points of contact and street addresses, LTAR experimental boundaries, LTAR site "legacy region" boundaries, LTAR eddy flux tower locations, and LTAR phenocam locations.Resource Software Recommended: ArcGIS,url: esri.com Resource Title: LTAR Standard GIS Data Layers, 2020 version, GeoJSON files. File Name: LTAR_Standard_GIS_Layers_v2020_GeoJSON_ADC.zipResource Description: The contents of the LTAR Standard GIS Data Layers includes geospatial data that represent locations and areas associated with the LTAR Network as of late 2020. This collection of geojson files includes spatial data describing LTAR site locations, addresses, experimental plots, fields and watersheds, eddy flux towers, and phenocams. There are six data layers in the geodatabase available to the public. This dataset was created in 2019-2020 by the LTAR network as a national collaborative effort among working groups and LTAR sites. Resource Software Recommended: QGIS,url: https://qgis.org/en/site/

The following data is provided as a public service, for informational purposes only. This data should not be construed as legal advice. Users of this data should independently verify its determinations prior to taking any action under the California Environmental Quality Act (CEQA) or any other law. The State of California makes no warranties as to accuracy of this data. General plan land use element data was collected from 532 of California's 539 jurisdictions. An effort was made to contact each jurisdiction in the state and request general plan data in whatever form available. In the event that general plan maps were not available in a GIS format, those maps were converted from PDF or image maps using geo-referencing techniques and then transposing map information to parcel geometries sourced from county assessor data. Collection efforts began in late 2021 and were mostly finished in late 2022. Some data has been updated in 2023. Sources and dates are documented in the "Source" and "Date" columns with more detail available in the accompanying sources table. Data from a CNRA funded project, performed at UC Davis was used for 7 jurisdictions that had no current general plan land use maps available. Information about that CNRA funded project is available here: https://databasin.org/datasets/8d5da7200f4c4c2e927dafb8931fe75dIndividual general plan maps were combined for this statewide dataset. As part of the aggregation process, contiguous areas with identical use designations, within jurisdictions, were merged or dissolved. Some features representing roads with right-of-way or Null zone designations were removed from this data. Features less than 4 square meters in area were also removed.

The USGS 3D Hydrography Program (3DHP) ArcGIS REST service (3DHP_all) from The National Map is the first of several data services that will be delivered by the 3D Hydrography Program. The 3DHP_all comprises a national network of flowlines, hydrolocations, and water bodies, and will include catchments, drainage areas, and flow network derivatives as they are populated in the future. The 3DHP_all service will provide access to a 3D-enabled geospatial hydrography vector dataset built from 3DHP data and intended to provide the most comprehensive but general rendering of 3DHP data. 3DHP data is derived from elevation-derived hydrography (EDH) Elevation-Derived Hydrography Specifications | U.S. Geological Survey (usgs.gov) where available. Where EDH has not been collected, 3DHP data will be supplemented by data from the National Hydrography Dataset (NHD) National Hydrography Dataset | U.S. Geological Survey (usgs.gov). As further EDH data is collected, the EDH data will replace the NHD data in that data collection area. 3DHP data ingested from EDH sources will include catchments, drainage areas derived from catchments, and flowline network attribute derivatives.Use Constraints: _ None. All data are open and non-proprietary. However, users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of this data may no longer represent actual conditions. Users should not use this data for critical applications without a full awareness of its limitations. This dataset is not intended to be used for site-specific regulatory determinations. Acknowledgment of the U.S. Geological Survey would be appreciated for products derived from these data.For additional information on the 3DHP, go to https://www.usgs.gov/3dhp.See https://apps.nationalmap.gov/help/ for assistance with The National Map viewer, download client, services, or metadata.

The USGS National Hydrography Dataset (NHD) Downloadable Data Collection from The National Map (TNM) is a comprehensive set of digital spatial data that encodes information about naturally occurring and constructed bodies of surface water (lakes, ponds, and reservoirs), paths through which water flows (canals, ditches, streams, and rivers), and related entities such as point features (springs, wells, stream gages, and dams). The information encoded about these features includes classification and other characteristics, delineation, geographic name, position and related measures, a "reach code" through which other information can be related to the NHD, and the direction of water flow. The network of reach codes delineating water and transported material flow allows users to trace movement in upstream and downstream directions. In addition to this geographic information, the dataset contains metadata that supports the exchange of future updates and improvements to the data. The NHD supports many applications, such as making maps, geocoding observations, flow modeling, data maintenance, and stewardship. For additional information on NHD, go to https://www.usgs.gov/core-science-systems/ngp/national-hydrography.

DWR was the steward for NHD and Watershed Boundary Dataset (WBD) in California. We worked with other organizations to edit and improve NHD and WBD, using the business rules for California. California's NHD improvements were sent to USGS for incorporation into the national database. The most up-to-date products are accessible from the USGS website. Please note that the California portion of the National Hydrography Dataset is appropriate for use at the 1:24,000 scale.

For additional derivative products and resources, including the major features in geopackage format, please go to this page: https://data.cnra.ca.gov/dataset/nhd-major-features Archives of previous statewide extracts of the NHD going back to 2018 may be found at https://data.cnra.ca.gov/dataset/nhd-archive.

In September 2022, USGS officially notified DWR that the NHD would become static as USGS resources will be devoted to the transition to the new 3D Hydrography Program (3DHP). 3DHP will consist of LiDAR-derived hydrography at a higher resolution than NHD. Upon completion, 3DHP data will be easier to maintain, based on a modern data model and architecture, and better meet the requirements of users that were documented in the Hydrography Requirements and Benefits Study (2016). The initial releases of 3DHP will be the NHD data cross-walked into the 3DHP data model. It will take several years for the 3DHP to be built out for California. Please refer to the resources on this page for more information.

The FINAL,STATIC version of the National Hydrography Dataset for California was published for download by USGS on December 27, 2023. This dataset can no longer be edited by the state stewards.

The first public release of the 3D Hydrography Program map service may be accessed at https://hydro.nationalmap.gov/arcgis/rest/services/3DHP_all/MapServer.

Questions about the California stewardship of these datasets may be directed to nhd_stewardship@water.ca.gov.

Tags

   survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES




   Summary


   BES Research, Applications, and Education


   Description


   Geocoded for Baltimore County. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 



   The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 


   Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey.


   This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because

MD/PA Sandy Supplemental Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00397 Woolpert Order No. 74333 CONTRACTOR: Woolpert, Inc. This task is for a high resolution data set of lidar covering approximately 1,845 square miles. The lidar data was acquired and processed under the requirements identified in this task order. Lidar data is a remotely sensed high resolution elevation data collected by an airborne platform. The lidar sensor uses a combination of laser range finding, GPS positioning, and inertial measurement technologies. The lidar systems collect data point clouds that are used to produce highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures, and vegetation. The task required the LiDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. The final products include classified LAS, one (1) meter pixel raster DEMs of the bare-earth surface in ERDAS IMG Format, and 8-bit intensity images. Each LAS file contains lidar point information, which has been calibrated, controlled, and classified. Additional deliverables include hydrologic breakline data, control data, tile index, lidar processing and survey reports in PDF format, FGDC metadata files for each data deliverable in .xml format, and LAS swath data. Ground conditions: Water at normal levels; no unusual inundation; no snow; leaf off. Coastal tiles 18SVH065720 and 8SVH095690 contain no lidar points as they exist completely in water. A DEM IMG was generated for these two tiles as the digitized hydro breakline assumed the data extent in the area. As such only 2568 LAS and Intensity files will be delivered along with 2570 DEM IMG's.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://lidar.geodata.md.gov/imap/rest/services/Kent/MD_kent_shadedRelief_RGB/ImageServer

This database was designed in response to the Director Memorandum - "Effective January 1, 2019 all structure greater than 120 square feet in the State Responsibility Area (SRA) damaged by wildfire will be inspected and documented in the DINS Collector App."To document and structure damaged or destroyed by the Mosquito wildland fire open the associated Field Map app.NOTE - this feature service is configured to not allow record deletion. If a record needs to be deleted contact the program manager below.This is the schema developed and used by the CAL FIRE Office of State Fire Marshal to assess and record structure damage on wildland fire incidents. The schema is designed to be configured in the Esri Collector/Field Maps app for data collection during or after an incident.

The US Forest Service manages 193 million acres including the nation's 154 National Forests and 20 National Grasslands. These lands provide a wide variety of recreational opportunities, protect sources of clean water, and supply timber and forage.Dataset SummaryPhenomenon Mapped: United States lands managed by the US Forest Service Coordinate System: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, and Puerto RicoVisible Scale: The data is visible at all scales.Source: USFS Surface Ownership Parcels layerPublication Date: February 2024This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Forest Service lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "forest service" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "forest service" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in ProThe data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage..This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.