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. were derived from the NVC. NatureServe developed a preliminary list of potential vegetation types. These data were combined with existing plot data (Cully 2002) to derive an initial list of potential types. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the park’s small size and the large amount of field data, the map units are equivalent to existing vegetation associations or local associations/descriptions (e.g., Prairie Dog Colony). In addition to vegetation type, vegetation structures were described using three attributes: height, coverage density, and coverage pattern. In addition to vegetation structure and context, a number of attributes for each polygon were stored in the associated table within the GIS database. Many of these attributes were derived from the photointerpretation; others were calculated or crosswalked from other classifications. Table 2.7.2 shows all of the attributes and their sources. Anderson Level 1 and 2 codes are also included (Anderson et al. 1976). These codes should allow for a more regional perspective on the vegetation types. Look-up tables for the names associated with the codes is included within the geodatabase and in Appendix D. The look-up tables contain all the NVC formation information as well as alliance names, unique IDs, and the ecological system codes (El_Code) for the associations. These El_Codes often represent a one-to-many relationship; that is, one association may be related to more than one ecological system. The NatureServe conservation status is included as a separate item. Finally, slope (degrees), aspect, and elevation were calculated for each polygon label point using a digital elevation model and an ArcView script. The slope figure will vary if one uses a TIN (triangulated irregular network) versus a GRID (grid-referenced information display) for the calculation (Jenness 2005). A grid was used for the slope figure in this dataset. Acres and hectares were calculated using XTools Pro for ArcGIS Desktop.

Everything is awesome!Of course I don't need to convince you of the charm, educational utility, considered minimalism, and pure joy that Lego brings to the world. So why would I need to convince you that making maps in a Lego aesthetic is worth your while?This ArcGIS Pro style makes any vector point, line, or polygon layer look like a grid of little plastic nobly studs, ready to capture eyeballs and whip up unbridled excitement for skeuomorphic cartography! Plus it always re-sorts itself as you zoom in and out, always looking nice and blocky.Created in collaboration with Warren Davison, this style is ready to assemble your map into little Lego wonders.Here are some snapshots for you to peruse.Based mainly on these two texture overlays (sitting atop a dynamically colorable background element: Happy assembling! John Nelson

This website provides a limited number of Substructure Maps in “pdf” format via GIS polygons representing grids containing URL links. Across various areas of Los Angeles County, paper maps were created by Public Works (PW) and its predecessor Departments to show underground utilities such as cable TV, gas, oil, and telephone lines.

Though most of these maps are no longer updated, they can be useful as a research resource. Every reasonable effort has been made to assure the accuracy of this data and the maps referenced. Some cities may provide substructure information for the areas not covered by these grids. Additional and more accurate substructure data and information may also be obtained through the utility companies. Before digging, it is strongly advised to contact the Underground Service Alert (DigAlert Express) at www.digalert.org/digexpress.html or by calling 811.

Please note that California State Law Says, You Must Contact DigAlert!

The County of Los Angeles makes no warranty, representation, or guarantee as to the content, sequence, accuracy, timeliness, or completeness of any of the data provided herein or of any maps referenced. Los Angeles County Public Works recommends that all utility research be conducted under the supervision of a licensed civil engineer.

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 converted the photointerpreted data into a format usable in a geographic information system (GIS) by employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM), Zone 16, using the North American Datum of 1983 (NAD83). Orthorectify: We orthorectified the interpreted overlays by using OrthoMapper, a softcopy photogrammetric software for GIS. One function of OrthoMapper is to create orthorectified imagery from scanned and unrectified imagery (Image Processing Software, Inc., 2002). The software features a method of visual orientation involving a point-and-click operation that uses existing orthorectified horizontal and vertical base maps. Of primary importance to us, OrthoMapper also has the capability to orthorectify the photointerpreted overlays of each photograph based on the reference information provided. Digitize: To produce a polygon vector layer for use in ArcGIS (Environmental Systems Research Institute [ESRI], Redlands, California), we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format by using ArcGIS. In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map-attribute codes (both map-class codes and physiognomic modifier codes) to the polygons and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer. Geodatabase: At this stage, the map layer has only map-attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map-class names, physiognomic definitions, links to NVCS types), we produced a feature-class table, along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature-class layers produced from this project, including vegetation sample plots, accuracy assessment (AA) sites, aerial photo locations, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

This collection of files are part of a larger dataset uploaded in support of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB, DOE Project DE-EE0006726). Phase 1 of the GPFA-AB project identified potential Geothermal Play Fairways within the Appalachian basin of Pennsylvania, West Virginia and New York. This was accomplished through analysis of 4 key criteria: thermal quality, natural reservoir productivity, risk of seismicity, and heat utilization. Each of these analyses represent a distinct project task, with the fifth task encompassing combination of the 4 risks factors. Supporting data for all five tasks has been uploaded into the Geothermal Data Repository node of the National Geothermal Data System (NGDS).

This submission comprises the data for Thermal Quality Analysis (project task 1) and includes all of the necessary shapefiles, rasters, datasets, code, and references to code repositories that were used to create the thermal resource and risk factor maps as part of the GPFA-AB project. The identified Geothermal Play Fairways are also provided with the larger dataset. Figures (.png) are provided as examples of the shapefiles and rasters. The regional standardized 1 square km grid used in the project is also provided as points (cell centers), polygons, and as a raster. Two ArcGIS toolboxes are available: 1) RegionalGridModels.tbx for creating resource and risk factor maps on the standardized grid, and 2) ThermalRiskFactorModels.tbx for use in making the thermal resource maps and cross sections. These toolboxes contain item description documentation for each model within the toolbox, and for the toolbox itself. This submission also contains three R scripts: 1) AddNewSeisFields.R to add seismic risk data to attribute tables of seismic risk, 2) StratifiedKrigingInterpolation.R for the interpolations used in the thermal resource analysis, and 3) LeaveOneOutCrossValidation.R for the cross validations used in the thermal interpolations.

Some file descriptions make reference to various 'memos'. These are contained within the final report submitted October 16, 2015.

Each zipped file in the submission contains an 'about' document describing the full Thermal Quality Analysis content available, along with key sources, authors, citation, use guidelines, and assumptions, with the specific file(s) contained within the .zip file highlighted.

UPDATE: Newer version of the Thermal Quality Analysis has been added here: https://gdr.openei.org/submissions/879 (Also linked below) Newer version of the Combined Risk Factor Analysis has been added here: https://gdr.openei.org/submissions/880 (Also linked below) Regional Grid Shapefiles and Raster used in Thermal Quality Analysis task of Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin. Polygon (Fishnet2.shp and associated files), Point (Fishnet2_label.shp and associated files) and Raster grid (GridNAD.tif) are included, made using ArcGIS Create Fishnet tool.

There is an associated file containing the ArcGIS Toolbox with the Regional Grid Models, (ArcGISToolbox_RegionalGridModels.zip) .

The shapefiles, ArcGIS toolbox, and R script contained within these two .zip files were used to convert vector and raster files to the standardized 1 square km grid used in this project. The code is general enough to be used in other studies that may need to work on a standard grid. ArcGIS 10.1 or later is needed to use the models in the toolbox.

Details regarding methods for seismic risk factor conversion (within the toolbox) may be found in the memo contained within the project final report entitled 14_GPFA-AB_SeismicRiskMapCreationMethods.pdf (Smith and Horowitz, 2015).

The R script AddNewSeisFieldsFunctions.R implements some of the methods described in the memo.

Details about all of the ArcGIS toolbox models may be found in the memo entitled 16_GPFA-AB_RiskAnalysisAndRiskFactorDescriptions.pdf (Whealton, et al., 2015). Some models have been given different names since the memo was written. These models have the former names listed next to the current model name in the list above.

Note, this version 10-minute by 10-minute grid cells is not clipped to the Great Lakes shoreline, however see clipped companion dataset if shoreline representation is needed.After the union of the Lake Huron and 10 min by 10 min grid coverages, some of the resulting polygons were unioned and nearly all were assigned unique ID numbers as to correpond to the generally accepted 10 min grid definition used by the fishery community. This attribute is found under the field titled "Grid10min." For example maps containing said generally accepted grid definitions, see for example: <"Status of the Fishery Resource - 1989"; A Report by the Technical Fisheries Review Committee on the Assessment of Major Fish Stocks in those Waters of the Upper Great Lakes Ceded in the Treaty of 1836; U.S. Fish and Wildlife Service, Michigan Department of Natural Resources, Chippewa/Ottawa Treaty Fishery Management Authority; Appendix Figure B1.2>. Additional attributes include which Whitefish Management Unit "Wfm_units" and Statistical District "Stat_dist" each 10 minute by 10 minute grid belongs to (as defined by the State of Michigan Department of Natural Resources Fisheries Division) and "Area" in square meters (since meters are the map units of Michigan GeoRef), "Perimeter" in meters, and "Hectares" which were all calculated with the ArcView Xtools Meters/Hectares extension (XtoolsMH.avx).After merging the shoreline pieces there were two known gaps on the Michigan shore (most likely near the intersection of counties). These were sealed by graphically adding arcs to fill the gap (so that polygons that would not "leak out" could be created). There is no guarantee regarding the accuracy of this editing. The two edits were done at approximately: -83.32 lon, 44.50 lat; -84.22 lon, 46.00 lat.The Mackinac Bridge between the Michigan lower peninsula and Michigan upper peninsula was not included with the NOAA shoreline data that was merged. It was also added graphically, extending from approximately -84.73 lon, 45.79 lat to -84.72, 45.85.There has been a reduction of detail from the original shoreline data and grid during editing within ArcInfo/ArcView due to tolerances/snapping/etc. which would be evident upon comparison of this coverage with the two original coverages. The original grid coverage was created in ArcInfo using the Generate command - Fishnet option and was "straight" prior to union. After union of the two coverages, close inspection of some of the grid polygon border-arcs will reveal slight shifts in their "straightness". There has been no attempt to remedy said flaw. It is believed that the overall accuracy is within reason for many fishery applications.

This is a MGRS 100km Square Identifier polygon shapefile. The polygons are defined by UTM zone and MGRS band letters into mostly 6ºx8º polygons, with subdivisions into MGRS 100km Square Identifiers. There are no classification restrictions on this information. This information was created by the National Geospatial-Intelligence Agency (NGA) Coordinate Systems Analysis Team (SNAC).This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Location/MD_USNGZone17S/FeatureServer/1

A polygon feature class of Miami-Dade County Police Department (MDPD) Grid Boundaries.Updated: Bi-Annually The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

This is a MGRS 1km Square Identifier polygon shapefile. The polygons are defined by UTM zone and MGRS band letters into mostly 6ºx8º polygons, with subdivisions into MGRS 1km Square Identifiers. There are no classification restrictions on this information. This information was created by the National Geospatial-Intelligence Agency (NGA) Coordinate Systems Analysis Team (SNAC).This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Location/MD_USNGZone17S/FeatureServer/3

The following area shall be a lake trout refuge with boundaries in Lake Huron, grids 307 through 309, the north half (N½) of grid 407, and grids 408 through 410. Regulations: All commercial fishing is prohibited in the above area. Maps for general reference only: refer to text of Consent Decree 2000 for exact locations and provisions.Created a new polygon shapefile in ArcGIS 8.1. Copied selected features (as outlined in the Consent Decree 2000 documentation) of the US Department of Commerce (Bureau of the Census, Geography Division) county census (1995) layer into new shapefile. Created a new polygon shapefile in ArcGIS 8.1. The new pollygon layer was created using the snapping tool in ArcMap. Snapping to the vertices (as outlined in the Consent Decree 2000 documentation) of the MDNR (University of Michigan) Statistical Grid layer, extending the polygon boundaries beyond the preceding polygon we created, and finishing the sketch at the starting point. The new polygon feature was then commbined with the copied polygon generated from the US Department of Commerce (Bureau of the Census, Geography Division) county census (1995) layer using the union tool from the geoprocessing wizard in Arc Map. The desired features were then selected, exported as a new shapefile, and reprojected from Michigan georef to Decimal Degrees to create the final Drummond Island Lake Trout Refuge layer.The boundaries represented on consent decree maps are approximations based on the text contained in the 2000 Consent Decree. For legal descriptions of geographic extent or details pertaining to regulations for these representations refer to the original 2000 Consent Decree Document.

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 converted the photointerpreted data into a GIS-usable format employing three fundamental processes: (1) orthorectify, (2) digitize, and (3) develop the geodatabase. All digital map automation was projected in Universal Transverse Mercator (UTM) projection, Zone 16, using North American Datum of 1983 (NAD83). To produce a polygon vector layer for use in ArcGIS, we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format using ArcGIS (Version 9.2, © 2006 Environmental Systems Research Institute, Redlands, California). In ArcGIS, we used the ArcScan extension to trace the raster data and produce ESRI shapefiles. We digitally assigned map attribute codes (both map class codes and physiognomic modifier codes) to the polygons, and checked the digital data against the photointerpreted overlays for line and attribute consistency. Ultimately, we merged the individual layers into a seamless layer of INDU and immediate environs. At this stage, the map layer has only map attribute codes assigned to each polygon. To assign meaningful information to each polygon (e.g., map class names, physiognomic definitions, link to NVC association and alliance codes), we produced a feature class table along with other supportive tables and subsequently related them together via an ArcGIS Geodatabase. This geodatabase also links the map to other feature class layers produced from this project, including vegetation sample plots, accuracy assessment sites, and project boundary extent. A geodatabase provides access to a variety of interlocking data sets, is expandable, and equips resource managers and researchers with a powerful GIS tool.

This data publication is a compilation of six different multibeam surveys covering the previously unmapped Queen Charlotte Fault offshore southeast Alaska and Haida Gwaii, Canada. These data were collected between 2005 and 2018 under a cooperative agreement between the U.S. Geological Survey, Natural Resources Canada, and the National Oceanic and Atmospheric Administration. The six source surveys from different multibeam sonars are combined into one terrain model with a 30-meter resolution. A complementary polygon shapefile records the extent of each source survey in the output grid.

Abstract

The dataset was created by the Bioregional Assessment Programme. The History Field in this metadata statement describes how this dataset was created.

A 1000 m \* 1000m vector grid over the entire Bioregional Assessment Bioregions/Preminary Areas of Extent (using the boundary that is largest) starting at the whole km to ensure grid lines fall exactly on the whole km. The grid is in Australia Albers (GDA94) (EPSG 3577). This grid is intended as the template for standardized assessment units for the following bioregional assessment regions:

Hunter

Namoi

Clarence-Moreton

Galilee

Please note for the Gloucester subregion model a 500m grid ( GUID ) is proposed to be used as the standard assessment unit due to the finer resolution of the output models.

To facilitate processing speed and efficiency each of the above Bioregional Assessments have their own grid and extent created from this master vector grid template, (please see Lineage).

The unique ID field for each grid cell is AUID and starts from 1. The grid also has a column id and row for easy reference and processing.

Purpose

The GRID is an attempt to standardise (where possible) outputs of models from BA assessments and is a whole of BA template for the groundwater and potentially surface water teams of the above mentioned assessment areas.

Dataset History

The Vector grid was generated using the Fishnet tool in ArcGIS. The following fields were added:

AUID - Assessment Unit Unique Id

R001_C001 - A row and column id was calculated using the following python code in the field calculator in ArcGIS where 2685 is the number of rows in the grid and 2324 is the number of columns.

'R' + str(( !OID!-1)/2685).rjust(3, '0') + '_C' + str(( !OID!-1)%2324).rjust(3, '0')

A spatial index was added in ArcGIS 10.1 to increase processing and rendering speed using the Spatial index tool from the ArcToolbox.

The following parameters were used to generate the grid in the Create Fishnet tool in ArcGIS 10.1

Left: -148000

Bottom: -4485000

Fishnet Origin Coordinate

x Coordinate = -148000 Y Coordinate -4485000

Y-Axis Coordinate

X Coordinate -148000 Y Coordinate -4484990

Cell Height - 1000m

Cell Width - 1000m

Number of rows 0

Number of columns 0

Opposite corner: default

Geometry type: Polygon

Y

Dataset Citation

XXXX XXX (2016) BA ALL Assessment Units 1000m 'super set' 20160516_v01. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/6c1aa99e-c973-4472-b434-756e60667bfa.

This file contains the digital vector boundaries for the GEOSTAT grid in the UK as at 31 December 2011, as produced and supplied by Eurostat. The file was created as part of a ‘Pan-European' grid system. The grid contains 2011 Census data on total population and number of households for the United Kingdom and a break down by sex for England, Wales and Northern Ireland. This data is provided on the basis of the previously released postcode information from the Census where each postcode (and its associated data) is allocated to the GEOSTAT grid on the basis of its grid reference (point-in-polygon). Using the previously published data has allowed the publication of small counts for grid cells that may previously have been suppressed if there was a risk of disclosure. The file is in GRE format (grid, extent), meaning that is grid formed of equally sized cells which extends beyond the coastline. It can be used to aggregate statistics to equally sized 'areas’. Please note that this product contains Eurostat, National Records of Scotland, Northern Ireland Statistics and Research Agency and ONS Intellectual Property Rights. The services for the GEOSTAT Grids are published in the ETRS 1989 LAEA projection. As the file is not in the British National Grid (BNG) projection, it may not line up with other spatial datasets. Download File Size - 18 MB.REST URL of ArcGIS for INSPIRE View Service – https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/GEOSTAT_Grid_December_2011_Boundaries/MapServer/exts/InspireView REST URL of ArcGIS for INSPIRE Feature Download Service - https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/GEOSTAT_Grid_December_2011_Boundaries/MapServer/exts/InspireFeatureDownloadREST URL of ArcGIS Feature Service - https://ons-inspire.esriuk.com/arcgis/rest/services/Eurostat_Boundaries/GEOSTAT_Grid_December_2011_Boundaries/FeatureServer

Abstract

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

The layer in question describes faults interpreted to occur within the base of Permian geology within the Arckaringa Basin.

Purpose

Fault deformation was considered an important architectural feature of the Arckaringa basin to map, particularly with respect to the potential for inter-aquifer connectivity with other basins such as the Great Artesian Basin such faulting may engender.

Dataset History

The shapefile was developed by Frogtech in 2013. The generation of this and other interpretations developed by Frogtech followed this work flow pattern: 1.Complete all seismic and well interpretations after mistie analysis and fixes. 2.Define extent polygons for each unit using well data, surface geology polygons, seismic data and faults as constraints. This includes making detailed polygons of inclusions and exclusion areas for each grid to allow for erosional highs etc. 3.Define fault polygons in Kingdom for each surface where there is a mappable, significant offset on a horizon. 4.Create a test grid in twt using the gridding modules in Kingdom. The default gridding parameters used are 200m cell size, fault convergence (where faults are relevant) and moderate grid smoothng. 5.Review and interrogate the test map looking for grid artefacts. Review, check, adjust seismic interpretations as relevant. 6.Regrid. Iterate. 7.Once satisfied with the twt map, depth convert the relevant seismic horizon using the inbuilt Kingdom function to depth-convert by selected time-depth curve. After QA/QC we used the Cootanoorina-2 checkshot data to depth convert horizons in the north and east and the Arkeeta-1 checkshot data to depth convert horizons in the south. 8.Grid the horizon in the depth domain using the depth converted horizon and relevant depth-domain formation tops. 9.Review and assess the resultant draft depth structure map. 10.Remove grid artefacts and adjust interpretation as necessary. Regrid. Iterate. 11.Local smoothing of grids to create continuation of inferred troughs between control points and where first iteration isopachs show grid overlaps. Regrid. Iterate. 12.Create final maps in Kingdom. Export to ArcGIS. Create contours and apply consistent colour stretches to each map.

Dataset Citation

SA Department of Environment, Water and Natural Resources (2015) FrogTech, Permian Geology Base Faults - ARC. Bioregional Assessment Source Dataset. Viewed 26 May 2016, http://data.bioregionalassessments.gov.au/dataset/ab5e2e15-3666-4ad3-a11d-b12e453990f3.

For purposes of this Decree only, the parties reserving the issue of the eastern boundary of the 1836 Treaty waters in Lake Huron, Grids 507 through 512, 606 through 611, 709, and those portions of grids 612, 613, 710, 711, and 810 which are north of a line from the mouth of the Thunder Bay River in a straight line northeast through the northeast corner of grid 711 to the international border. Regulations: Tribal commercial fishing by any method other than trap nets shall be prohibited except fishing for chubs with small mesh gill nets or small mesh trap nets. Trap net fishing in this zone shall be open only to Bay Mills and Sault Tribe trap net fishers. A total of four (4) trap net operations shall initially be authorized for this zone. Each trap net operation will be limited to twelve (12) trap nets within the zone. Additional operations may be authorized in the future by CORA based on data collected in previous years. Maps for general reference only: refer to text of Consent Decree 2000 for exact locations and provisions.Created a new point shapefile in ArcGIS 8.1. A point was located on the USGS Alpena county 1:24,000 DRG as outlined in the Consent Decree 2000 documentation. The point was generated at the mouth of the Thunder Bay River. We then created a new polygon shapefile in ArcGIS 8.1. The new pollygon layer was created using the snapping tool in ArcMap. Starting form the above point location and heading in a clockwise direction snapping to the vertices (as outlined in the Consent Decree 2000 documentation) of the MDNR (University of Michigan) Statistical Grid layer, extending the polygon boundaries beyond the US Department of Commerce (Bureau of the Census, Geography Division) county census (1995) layer, and finishing the sketch at the starting point. The new polygon feature was then commbined with the US Department of Commerce (Bureau of the Census, Geography Division) county census (1995) layer using the union tool from the geoprocessing wizard in Arc Map. The desired features were then selected, exported as a new shapefile, and reprojected from Michigan georef to Decimal Degrees to create the final Southern Lake Huron Trap Net Zone layer.The boundaries represented on consent decree maps are approximations based on the text contained in the 2000 Consent Decree. For legal descriptions of geographic extent or details pertaining to regulations for these representations refer to the original 2000 Consent Decree Document.

The Key Map Grid dataset contains square features representing 0.75-mile by 0.75-mile grids within Montgomery County, Texas. These grids are organized and referenced according to the Key Map Grid Index, with each grid corresponding to a specific location within the county. The grids are assigned unique identifiers combining the index page number and letter, with 24 grids fitting within a single index page. The letters "I" and "O" are excluded to avoid confusion with numbers. The Key Map Grid was created by the Houston Map Company, which covers multiple counties in the Houston metropolitan area including Harris, Fort Bend, Galveston, Brazoria, Liberty, Waller, and Montgomery Counties. More information can be found on the Houston Map Company's website at www.keymaps.com.Data Fields Included:Grid ID: Unique identifier assigned to each grid (combination of index page number and letter)Boundary Polygon: Square representing the 0.75-mile by 0.75-mile grid

This map shows composite diversity averaged between 4 data sets: RecFIN recreational hook and line, SCCWRP trawls, NMFS benthic trawls, and kelp diver surveys. Diversity (H') was calculated independently for each of the four large datasets on a total of 364 species using the Shannon index of diversity (Shannon and Weaver, 1949). Using ArcGIS, 5 x 5 minute grids were created and mean diversity was calculated for each grid cell containing data. To provide an overall map of diversity, results from the four datasets were combined. To standardize, gridded results from each dataset were divided into quintiles with 5 denoting the greatest diversity and 1 the least diversity. The standardized diversity was averaged where more than one diversity estimate was available for a cell. Standardization re-scales the results from all datasets to the same scale. This process can remove some differences that result from variable collection methods; however, it can also minimize actual differences between habitats.

A polygon feature class that represents the grid of the United States Geological Survey (USGS) 7.5 minute quadrangles (quad) that are commonly associated with topographic map sheets, Digital Line Graphics (DLG), and Digital Raster Graphics (DRG) files.Updated: Not Planned The data was created using: Projected Coordinate System: WGS_1984_Web_Mercator_Auxiliary_SphereProjection: Mercator_Auxiliary_Sphere

This data set is an intersection of all 63 vector polygon ranges depicted in the following publication with a statewide grid of 25 square mile hexagon cells. Shuford, W.D., and Gardali, T., editors. 2008. California Bird Species of Special Concern: A ranked assessment of species, subspecies, and distinct populations of birds of immediate conservation concern in California. Studies of Western Birds 1. Western Field Ornithologists, Camarillo, California, and California Department of Fish and Game. Sacramento. http://www.dfg.ca.gov/wildlife/species/ssc/birds.html The vector polygon ranges were hand drawn at a scale of 1:6,600,000 by authors and editors of the Bird Species of Special Concern report and digitized into shapefiles by staff of the Biogeographic Data Branch, California Department of Fish and Game. The hexagon grid for the state was created by Steve Goldman by modifying an AML (Arc Macro Language) script originally written by Eric Kauffman.