The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The mapping component of the BRCA project used a combination of methods to interpret and delineate vegetation and land use polygons. The USGS applied an electronic segmentation method (e-Cognition software) to create preliminary linework on features with high-contrast photo-signatures. Using the preliminary linework as a baseline starting point, the primary photointerpreter drew polygons directly on screen through heads-up digitizing using ArcGIS editing tools. Additionally, trained photointerpreters assisting the primary photointerpreter drew polygons on Mylar overlays covering 1m resolution, 1:12,000-scale, 9 x 9-inch true-color aerial photographs. This process enabled the photointerpreters to view the landscape in stereo in order to identify finer details. The linework drawn on Mylar overlays was then transferred into digital media by heads-up digitizing using ArcGIS software. The park and environs were interpreted and mapped to the same level of detail.

Light Rail and Subway Lines dataset current as of 2000. This Layer was created in ArcView through "heads up" digitizing, using MARTA's digital road network as a basemap..

Planimetric Miscellaneous Structure features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

Every five years, since 1990, the Delaware Valley Regional Planning Commission has produced a GIS Land Use layer for its 9-county region. In 2000, digital orthophotography was flown by DVRPC. Utilizing this orthophotography, all Land Use annotation and digitizing was performed on-screen, or "heads-up," a first at DVRPC. Digitizing was done using ESRI ArcGIS 8 software at a 1:2400 (1 inch = 200 feet) scale.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. The mapping component was initiated by photo interpretation and digitization of 3-band 2001 color infrared (CIR) IKONOS imagery for the vegetation and land use classes determined through the field visit and expert knowledge of project team members. The heads-up digitization was performed at a display scale of 1:1000 to 1:1500. The digitization, evaluation, and modifications were iterative and collaborative processes involving the GIS analysts and the rest of the team. Preliminary maps were checked, corrected, and rechecked for boundary delineations. Final edits were made using the 2009 NAIP imagery, which captured the changes made along the eastern end of the property with the construction of the visitor’s center.

The seamless, county-wide parcel layer was digitized from official Assessor Parcel (AP) Maps which were originally maintained on mylar sheets and/or maintained as individual Computer Aided Design (CAD) drawing files (e.g., DWG). The CRA office continues to maintain the official AP Maps in CAD drawings and Information Systems Department/Geographic Information Systems (ISD/GIS) staff apply updates from these maps to the seamless parcel base in the County’s Enterprise GIS. This layer is a partial view of the Information Sales System (ISS) extract, a report of property characteristics taken from the County’s Megabyte Property Tax System (MPTS). This layer may be missing some attributes (e.g., Owner Name) which may not be published to the Internet due to privacy conditions under the California Public Records Act (CPRA). Please contact the Clerk-Recorder-Assessor (CRA) office at (707) 565-1888 for information on availability, associated fees, and access to other versions of Sonoma County parcels containing additional property characteristics.The seamless parcel layer is updated and published to the Internet on a monthly basis.The seamless parcel layer was developed from the source data using the general methodology outlined below. The mylar sheets were scanned and saved to standard image file format (e.g., TIFF). The individual scanned maps or CAD drawing files were imported into GIS software and geo-referenced to their corresponding real-world locations using high resolution orthophotography as control. The standard approach was to rescale and rotate the scanned drawing (or CAD file) to match the general location on the orthophotograph. Then, appropriate control points were selected to register and rectify features on the scanned map (or CAD drawing file) to the orthophotography. In the process, features in the scanned map (or CAD drawing file) were transformed to real-world coordinates, and line features were created using “heads-up digitizing” and stored in new GIS feature classes. Recommended industry best practices were followed to minimize root mean square (RMS) error in the transformation of the data, and to ensure the integrity of the overall pattern of each AP map relative to neighboring pages. Where available Coordinate Geometry (COGO) & survey data, tied to global positioning systems (GPS) coordinates, were also referenced and input to improve the fit and absolute location of each page. The vector lines were then assembled into a polygon features, with each polygon being assigned a unique identifier, the Assessor Parcel Number (APN). The APN field in the parcel table was joined to the corresponding APN field in the assessor property characteristics table extracted from the MPTS database to create the final parcel layer. The result is a seamless parcel land base, each parcel polygon coded with a unique APN, assembled from approximately 6,000 individual map page of varying scale and accuracy, but ensuring the correct topology of each feature within the whole (i.e., no gaps or overlaps). The accuracy and quality of the parcels varies depending on the source. See the fields RANK and DESCRIPTION fields below for information on the fit assessment for each source page. These data should be used only for general reference and planning purposes. It is important to note that while these data were generated from authoritative public records, and checked for quality assurance, they do not provide survey-quality spatial accuracy and should NOT be used to interpret the true location of individual property boundary lines. Please contact the Sonoma County CRA and/or a licensed land surveyor before making a business decision that involves official boundary descriptions.

Planimetric Bridge features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintainenance of the data includes heads-up digitizing using the orthophoto images.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We used ERDAS Imagine ® Professional 9.2, ENVI ® 4.5, and ArcGIS ® 9.3 with Arc Workstation to develop the vegetation spatial database. Existing GIS datasets that we used to provide mapping information include a NPS park boundary shapefile for VICK (including a 100 meter buffer boundary around the Louisiana Circle, South Fort, and Navy Circle satellite units), a land cover shapefile created by the NWRC (Rangoonwala et al. 2007), and the National Elevation Dataset (NED) (used as the source of the 10-meter elevation model and derived streams, slope, and hillshade). To make the entire spatial data set consistent with NPSVI policies to map only to park boundaries, we clipped the vegetation in and around the previously buffered areas around the Louisiana Circle, South Fort, and Navy Circle satellite unit NPS boundaries. We also added to the spatial database vegetation polygons for the previously omitted Grant’s Canal satellite unit by heads-up digitizing this area from a National Agricultural Information Program (NAIP) image.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. The mapping component was initiated by photo interpretation and digitization of 4-band 2005 IKONOS imagery for the vegetation and land use classes determined through the field visit and expert knowledge of project team members. The heads-up digitization was performed at a display scale of 1:1500 to 1:2000. The digitization, evaluation, and modifications comprised an iterative and collaborative process involving the GIS analysts and the rest of the team. Preliminary maps were checked, corrected, and rechecked for boundary delineations. These image sources included 2003, 2004, 2005, 2006 (3-band, Red, Green, Blue), and 2008 (4-band, Red, Green, Blue, Near Infrared) USDA FSA NAIP, 2002 and 1991 USGS DOQQs, and 1938 panchromatic imagery. Two additional 4-band (Red, Green, Blue, Near Infrared) IKONOS scenes were acquired in June and September of 2008 specifically for this project. These IKONOS image acquisitions targeted specific phenological windows that were generally not covered by other imagery.

Planimetric Parking features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintainenance of the data includes heads-up digitizing using the orthophoto images.

Planimetric Bridge features. In 2006, the Des Moines Regional GIS group contracted with Sanborn to digitize the planimetric features utilizing 3D stereo digitizing methods and GIS processing required under the RFP. The Program Management task included coordination and oversight of the NewCom Technology tasks; incorporating the imagery and photogrammetric data from the spring of 2006 flight, stereo digitizing the planimetric features and GIS processing of the impervious surface features to ensure clean topological data structure for subsequent area / polygon calculations. Maintenance of the data includes heads-up digitizing using the orthophoto images.

Napa County has used a 2004 edition vegetation map produced using the Manual of California Vegetation classification system (Thorne et al. 2004) as one of the input layers for land use decision and policy. The county decided to update the map because of its utility. A University of California, Davis (UCD) group was engaged to produce the map. The earlier map used black and white digital orthophoto quadrangles from 1993, with a pixel resolution of 3 meters. This image was delineated using a heads up digitization technique produced by ASI (Aerial Services Incorporated). The resulting polygons were the provided vegetation and landcover attributes following the classification system used by California State Department of Fish and Wildlife mappers in the Manual of California Vegetation. That effort included a brief field campaign in which surveyors drove accessible roads and verified or corrected the dominant vegetation of polygons adjacent to roadways or visible using binoculars. There were no field relevé or rapid assessment plots conducted. This update version uses a 2016 edition of 1 meter color aerial imagery taken by the National Agriculture Imagery Program (NAIP) as the base imagery. In consultation with the county we decided to use similar methods to the previous mapping effort, in order to preserve the capacity to assess change in the county over time. This meant forgoing recent data and innovations in remote sensing such as the use LiDAR and Ecognition’s segmentation of imagery to delineate stands, which have been recently used in a concurrent project mapping of Sonoma County. The use of such technologies would have made it more difficult to track changes in landcover, because differences between publication dates would not be definitively attributable to either actual land cover change or to change in methodology. The overall cost of updating the map in the way was approximately 20% of the cost of the Sonoma vegetation mapping program.Therefore, we started with the original map, and on-screen inspections of the 2004 polygons to determine if change had occurred. If so, the boundaries and attributes were modified in this new edition of the map. We also used the time series of imagery available on Google Earth, to further inspect many edited polygons. While funding was not available to do field assessments, we incorporated field expertise and other map data from four projects that overlap with parts of Napa Count: the Angwin Experimental Forest; a 2014 vegetation map of the Knoxville area; agricultural rock piles were identified by Amber Manfree; and parts of a Sonoma Vegetation Map that used 2013 imagery.The Angwin Experimental Forest was mapped by Peter Lecourt from Pacific Union College. He identified several polygons of redwoods in what are potentially the eastern-most extent of that species. We reviewed those polygons with him and incorporated some of the data from his area into this map.The 2014 Knoxville Vegetation map was developed by California Department of Fish and Wildlife. It was made public in February of 2019, close to the end of this project. We reviewed the map, which covers part of the northeast portion of Napa County. We incorporated polygons and vegetation types for 18 vegetation types including the rare ones, we reviewed and incorporated some data for another 6 types, and we noted in comments the presence of another 5 types. There is a separate report specifically addressing the incorporation of this map to our map.Dr Amber Manfree has been conducting research on fire return intervals for parts of Napa County. In her research she identified that large piles of rocks are created when vineyards are put in. These are mapable features. She shared the locations of rock piles she identified, which we incorporated into the map. The Sonoma Vegetation Map mapped some distance into the western side of Napa County. We reviewed that map’s polygons for coast redwood. We then examined our imagery and the Google imagery to see if we could discern the whorled pattern of tree branches. Where we could, we amended or expanded redwood polygons in our map.The Vegetation classification systems used here follows California’s Manual of California Vegetation and the National Vegetation Classification System (MCV and NVCS). We started with the vegetation types listed in the 2004 map. We predominantly use the same set of species names, with modifications/additions particularly from the Knoxville map. The NVCS uses Alliance and Association as the two most taxonomically detailed levels. This map uses those levels. It also refers to vegetation types that have not been sampled in the field and that has 3-6 species and a site descriptor as Groups, which is the next more general level in the NVCS classification. We conducted 3 rounds of quality assessment/quality control exercises.

This North Slope infrastructure GIS dataset includes roads (line), pipelines (line) and developed areas (polygon) as separate feature classes. Downloads are in shapefile and geodatabase format. Major, maintained road features on the North Slope are provided. Minor connections or roads within developed areas may not be represented or are generalized. Above surface pipeline features are provided. Multiple adjacent pipelines may be represented as one pipeline, features along routes may be simplified and pipelines within developed areas omitted. Developed area features include gravel pads, material pits, constructed water features and village areas. Road locations within villages have been updated using Alaska Department of Transportation GIS data. Road, pipeline and developed area feature attributes have been assigned oil and gas unit designations using Alaska Division of Oil and Gas GIS data. The Trans-Alaska Pipeline (TAPS) was not digitized and is available via the link below. These infrastructure data were originally compiled by Audubon in 2014 and provided to the Bureau of Land Management (BLM) Rapid Ecological Assessment (REA) project for the North Slope region. Those data were edited by the Alaska Center for Conservation Science (ACCS) for the REA and released for public distribution on the BLM/REA website. The North Slope Science Initiative (NSSI) subsequently updated the REA product using high resolution imagery as a verification base and heads up digitizing to produce an initial version of this infrastructure dataset. Annual updates to these data have been performed by ACCS and funded by BLM. These updates are based on interpretation of 2022 Sentinel imagery for the Prudhoe Bay development area and other image products as available for the greater North Slope region. All locations are approximate. Neither ACCS, BLM, NSSI or other contributors to this dataset shall be held liable for improper or incorrect use of the data described and/or contained herein. In an effort to provide the most comprehensive overview possible, these updates have incorporated many data sources, using a variety compilation methods. As a result, there are a variety of limitations to the thematic and spatial accuracy of these data. The appropriate use of these data is the responsibility of the user. A link to a web map containing this infrastructure data as well as land ownership and administrative information is provided below.

This dataset provides the location of separated paved paths in the Matanuska-Susitna Borough. These paths are typically paved, along side an existing roadway, constructed as part of a road construction or upgrade project, and provide an alternative to motorized transportation methods. This dataset does not include sidewalks. Most trails in this dataset were heads up digitized (scale

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The mapping component was produced by identifying land cover on air photos and hand digitizing on-screen. Heads-up digitizing was accomplished at a display scale of not more than 1:1,000 against a back-drop of air photos. Imagery was the most recent available from the National Agriculture Imagery Program. This included 2010 leaf-on true color and 2006 leaf-off color infrared images.

Under contract to the California Department of Fish and Wildlife (CDFW), Aerial Information Systems (AIS) created a fine-scale vegetation map of portions of the Southern Sierra Nevada Foothills in central California. AIS subcontracted the California Native Plant Society (CNPS) to conduct field reconnaissance assistance for this project, as well as accuracy assessment (AA) field data collection; and Soar Environmental Consulting to assist in the AA field data collection. CDFW''s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. The mapping study area, consists of approximately 1,824,939 acres, of Mariposa, Madera, Tulare, Kern, and Los Angeles counties. Work was performed on the project between 2019 and 2022. The primary purpose of the project was to further CDFW''s goal of developing fine-scale digital vegetation maps as part of the California Biodiversity Initiative Roadmap of 2018.CNPS under separate contract and in collaboration with CDFW VegCAMP developed the floristic vegetation classification used for the project. The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS).The vegetation map was produced applying heads-up digitizing techniques using a 2018 base of one-meter National Agricultural Imagery Program (NAIP) imagery (true-color and color infrared), in conjunction with ancillary data and imagery sources. Map polygons are assessed for Vegetation Type, Percent Cover, Exotics, Development Disturbance, and other attributes. The minimum mapping unit (MMU) is 2 acres; exceptions are made for wetlands and riparian types, which were mapped to a 1-acre MMU.Field reconnaissance and accuracy assessment enhanced map quality. There was a total of 111 mapping classes. The overall Fuzzy Accuracy Assessment rating for the final vegetation map,at the Alliance and Group levels, is 89.5 percent.

The Department of Fish and Game - Division of Wildlife Conservation's game management units and subunits are the most requested of the Division's GIS data. Hunting and trapping regulations and other wildlife management issues often refer geographically to the effected Game Management Unit (GMU). This file gives the user access to the currently available digital representation of the GMU/UCUs. The purpose of the GMU and associated Subunits and Uniform coding units is to give a uniform, geographic based coding system for all State of Alaska wildlife population and habitat management and regulations. This data can be used for mapping or analysis purposes assuming it is used with comparable data.Uniform Coding UnitsPrior to 1982, Alaska Department of Fish and Game - Division of Wildlife Conservation (ADFG-DWC) had a variety of coding schemes (18) relating harvest and management information to geographical areas. This made it difficult when comparing statewide wildlife information gathered across the state. In 1982, a new standardized statewide, geographically-based, hierarchy system of coding was created called the Uniform Coding Unit or UCU system. Game management units (GMUs), Subunits, and uniform coding units (UCUs) are the underlying geographic foundation of the wildlife and habitat management and regulations for ADFG-DWC. The GMU/UCU system consists of five Regions which are divided into twenty-six (26) Game Management Units (GMUs). Many of the GMUs are divided into Subunits (e.g. GMU 15 has three (3) Subunits, 15A, 15B, and 15C). GMUs that are not divided into subunits have a "Z" designation for the subunit. GMUs and Subunits are further divided into Major Drainages, Minor Drainages and Specific Areas. The smallest of these areas (down to the "specific area") is referred to as a Uniform Coding Unit (UCU) and has a unique 10 character code associated with it. (NOTE: UCU layer is for internal and official use only, not for public use or distribution). The UCU code is used for geographically classifying harvest and management information. Data that cannot be tied to a specific code can be generalized to the next higher level of the hierarchy. For example:a location description that is within multiple "specific areas" within a "minor drainage" can be coded to the minor code with a "00" for the specific area. Unknown "minor drainages" can be coded to the "major drainage" level, etc. If the subunit is unknown or the area covers multiple subunits within a unit, the subunit can be specified as a "Z" code (e.g. an area within subunits 15A and 15B could be recorded as 15Z). If a geographic location covers multiple units or the unit is unknown, the most general code (statewide code) is recorded as 27Z-Z00. The original hardcopy master maps were drawn to portray the UCUs fairly accurately geographically, but were not necessarily precisely drawn (i.e. left vs. right bank of a river, or exact ridge line). Each UCU was represented by drawing boundaries on USGS 1:250,000 scale quadrangle maps with a thick magic marker. A list (database) of place-names and their corresponding UCU codes was created and is still used today to assign permit, harvest, and sealing information to one of these geographic areas. In 1988, the UCU boundaries were digitized (traced) from the original maps into a computerized Geographic Information System (ArcInfo). Minor changes were made in 1989. Effective July 1, 2006 - GMU 24 is now divided up into four subunit 24A, 24B, 24C, 24D. - GMU 21A and 21B - - boundary has been modified. Phase I2006-2008 - initial clean-up of boundaries for GMU 6, 9, 10, 12, 16, 19, 20, 25. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Jan 2009 - Priority has shifted to getting the bulk of the updates into the master. Verification and modifications based on the UCU list and the AB corrections will come at a later date. This shift is to attempt to get the master into a permanent SDE GDB, set it up with the GDB topology, make additional clean-up/edits using the GDB tools, set up versioning, make it easier to replicate to area offices, and to take advantage of the tools/features available thru ArcGIS Server with versioned GDBs. June 2009 - initial clean-up of boundaries for Southeast (GMU 1-5), GMU 17, and GMU 18. These have NOT been verified against the UCU master list or by area biologists. -ras July 1 2009 - initial clean-up of boundaries for GMU 7 and 8. Also some adjustments for 25D based on the NHD 2008 version and ArcHydro Tools "raindrop" feature. These have NOT been verified against the UCU master list or by area biologists. -ras Sept 17, 2009 - initial clean-up of boundaries for GMU 13. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Oct 21, 2009 - initial clean-up of boundaries for GMU 14 These modification have NOT been verified against the UCU master list or by area biologists. -rasNov 19, 2009 - initial clean-up of boundaries for GMU 15. These modifications have NOT been verified against the UCU master list or by area biologists. -ras Dec 7, 2009 - initial clean-up of boundaries for GMU 22. These modification have NOT been verified against the UCU master list or by area biologists. -ras March 3, 2010 - initial clean-up of boundaries for GMU 23. These modification have NOT been verified against the UCU master list or by area biologists. -rasApril 10, 2010 - initial clean-up of boundaries for GMU 26. These modification have NOT been verified against the UCU master list or by area biologists. -ras May 2010 - This completes Phase I of refining the UCUs - bulk heads-up re-digitizing of all arcs. Phase II - Converting and establishing procedures for maintaining the master in an Enterprise GDB is underway. Effective July 1, 2010, Region II was split into Region 2 (GMU's 6, 7, 8, 14C, 15) and Region 4 (GMU's 9, 10, 11, 13, 14AB, 16, 17. This version was updated to reflect the change. An archive of the previous version (with Regions I, II, III, and V) is available on request as GMUMaster_063010. -ras2012-present - minor updates continue as needed and time allows, and as newer base maps are used.2014 minor updates continue as needed, including updates to domain listings (not affecting GIS geometry)Effective July 1, 2014- revision to GMU 18/19/21 boundary to clarify/correct previous insufficient boundary description. Passed during Spring 2014 Board of Game.2015 minor changes as needed

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Vegetation and land use were interpreted to as detailed a level as possible from high-resolution, 9” x 9” stereo pairs of 1:12,000-scale true color aerial photography. Polygons representing vegetation or land use map classes were delineated on Mylar overlays on aerial photographs (where signatures were confusing) and with the heads-up digitizing technique (where signatures had high contrast), then transferred to a spatial database. The project used the national program standard minimum mapping unit of 0.5 ha with few exceptions.

Data from a number of sources is used for the development and ongoing maintenance of the MajorRoads feature class. Source data includes SanGIS Roads_All, Caltrans State Highway Centerlines, and street centerline data from the County of Imperial. Regional aerial imagery (1'/pixel resolution or better) is generally used as a guide for delineating roadway alignments, primarily using heads up digitizing methods, using ArcGIS desktop software.

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Base Imagery used for mapping (acquired by MoRAP): 2009, Benton County, AR, leaf-on, true color, 0.61 m (2 feet) 2009, Benton County, AR, leaf-off, 4-band CIR, 1 m The mapping component was produced by identifying land cover in a three-step process: (1) image objects were generated at 1 m resolution using e-Cognition applied to stacked leaf-on and leaf-off air photos, (2) image objects were coded with land cover classes on-screen, and (3) image objects were cut and corrected via heads-up digitizing at a display scale of 1:1,500 against a back-drop of air photos. The best available imagery was from the NAIP. This included 2009 leaf-on true color and 4-band color infrared (CIR) 1 m resolution photos, and 2007-2009 leaf-off true color 2 foot resolution photos.