This map presents a tour of the City of Redlands, California using the detailed map of Redlands included in the community basemap. The City of Redlands is located in Southern California, about 65 miles east of Los Angeles. The map tour highlights some of the unique features in the history of Redlands as well as several of the places and events that make it a very livable community today.The map features a detailed basemap for the City of Redlands, California, including buildings, parcels, vegetation, land use, landmarks, streets, and more. The map features special detail for areas of high interest within the City, including local parks, landmarks, and the ESRI campus.The map references detailed GIS data provided by the City of Redlands, Department of Innovation and Technology, GIS Division. The map was authored using map templates available from ESRI, including:Topographic Map Template - Large ScalesCampus Basemap TemplateThe map was published as part of ESRI's Community Maps Program and is one of several detailed maps of cities and counties in the World Topographic Map.

This map presents a tour of the City of Redlands, California using the detailed map of Redlands included in the community basemap. The City of Redlands is located in Southern California, about 65 miles east of Los Angeles. The map tour highlights some of the unique features in the history of Redlands as well as several of the places and events that make it a very livable community today.The map features a detailed basemap for the City of Redlands, California, including buildings, parcels, vegetation, land use, landmarks, streets, and more. The map features special detail for areas of high interest within the City, including local parks, landmarks, and the ESRI campus.The map references detailed GIS data provided by the City of Redlands, Department of Innovation and Technology, GIS Division. The map was authored using map templates available from ESRI, including:Topographic Map Template - Large ScalesCampus Basemap TemplateThe map was published as part of ESRI's Community Maps Program and is one of several detailed maps of cities and counties in the World Topographic Map.

This map is the foundation for the Redlands Emergency Dashboard operation view in the Learn ArcGIS project Monitor Real-Time Emergencies. The map data is fictitious and should be used only for education and demonstration purposes.

URL: https://geoscience.data.qld.gov.au/dataset/mr003952

The REDLAND BAY Mine map was published in 1978, charted in 1980 at 1:10 000 as part of the 1:10 000 series to administer permit and permit related spatial information. The map was maintained internally as a provisional office chart and is located within the Beenleigh (9542) 1:100 000 map area.
The map product is available to all government agencies, industry and the public for reference.
Title and Image reference number is REDLAND BAY_6655.

Permits current as at 01/07/1988 transferred into Mines spatial database and viewer. Author:Department of Mapping and Surveying, Queensland.

To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.

Aerial Information Systems, Inc. (AIS) was contracted by the Coachella Valley Conservation Commission (CVCC) through a Local Assistance Grant originating from the California Department of Fish and Wildlife (CDFW) to map and describe the essential habitats for bighorn sheep monitoring within the San Jacinto-Santa Rosa Mountains Conservation Area. This effort was completed in support of the Coachella Valley Multiple Species Habitat Conservation Plan (CVMSHCP). The completed vegetation map is consistent with the California Department of Fish and Wildlife classification methodology and mapping standards. The mapping area covers 187,465 acres of existing and potential habitat on the northern slopes of the San Jacinto and Santa Rosa Mountains ranging from near sea level to over 6000 feet in elevation. The map was prepared over a baseline digital image created in 2014 by the US Department of Agriculture '' Farm Service Agency''s National Agricultural Imagery Program (NAIP). Vegetation units were mapped using the National Vegetation Classification System (NVCS) to the Alliance (and in several incidences to the Association) level (See Appendix A for more detail) as described in the second edition of the Manual of California Vegetation Second Edition (Sawyer et al, 2009). The mapping effort was supported by extensive ground-based field gathering methods using CNPS rapid assessment protocol in the adjacent areas as part of the Desert Renewable Energy Conservation Plan (DRECP) to the north and east; and by the 2012 Riverside County Multiple Species Habitat Conservation Plan vegetation map in the western portion of Riverside County adjacent to the west. These ground-based data have been classified and described for the abovementioned adjacent regions and resultant keys and descriptions for those efforts have been used in part for this project.For detailed information please refer to the following report: Menke, J. and D. Johnson. 2015. Vegetation Mapping '' Peninsular Bighorn Sheep Habitat. Final Vegetation Mapping Report. Prepared for the Coachella Valley Conservation Commission. Aerial Information Systems, Inc., Redlands, CA.

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 interpreted polygons were manually transferred to overlays that were registered to the base maps. Map unit attributes and appropriate physiognomic modifier codes were added to a second overlay. The overlays were subsequently rechecked for accuracy. Each overlay of transferred data was scanned using a large format sheet fed scanner at a resolution of 400 dots per inch. The resulting Tagged Image File Format (TIFF) images were then converted to a grid using ArcInfo (Version 7.2.1 Patch 2, Environmental Systems Research Institute, Redlands, California). For data produced with the DOQ base maps, the converted grid was projected to UTM Zone 15 using North American Datum of 1983 (NAD83).

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) database enhancement. All digital map automation was projected in Universal Transverse Mercator (UTM) projection, Zone 12, using North American Datum of 1983 (NAD83). To produce a polygon vector coverage for use in GIS, we converted each raster-based image mosaic of orthorectified overlays containing the photointerpreted data into a grid format using ArcInfo (Version 8.0.2, Environmental Systems Research Institute, Redlands, California). In ArcTools, we used the ArcScan utility to trace the polygon data and produce ArcInfo vector-based coverages. 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 78 individual coverages into a seamless map coverage of GNP and immediate environs. We synchronized polygons and attributes along the boundary between the GNP and WLNP map coverages. Although GNP and WLNP are two separate map coverages, they are seamless in the sense they edge tie perfectly in both polygon location and map attribute.

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. Twenty-two map classes were developed to map the vegetation and general land cover of Cape Lookout and surrounding areas. These maps included the following: 13 map classes representing natural/semi-natural vegetation at the association level in the National Vegetation Classification System (NVCS), one map class representing cultural vegetation (e.g., developed) in the NVCS, and eight map classes representing non-vegetated units (e.g., open water bodies, buildings, roads, etc.). Features were interpreted using 1:12,000 scale digital color-infrared aerial photography (flown 31 May 2009) through heads-up-digitizing in ArcGIS (Version 10.0, © 2010 Environmental Systems Research Institute, Redlands, California). Polygons were mapped to a 0.5- hectare minimum mapping unit (MMU). A geodatabase containing various feature class layers and tables show the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, AA sites, project boundary extent, and aerial photographic centers.

A 300 x 600 m integrated terrain unit map (ITUM) was produced at 1:500 scale inside the 350 x 650 m Martinelli grid, and the 1:500 digital elevation model (DEM). Vegetation was mapped using Komarkova's (1979) classification system (Braun-Blanquet) units. All map units were mapped to 1/8-inch minimum map-polygon-size resolution. The map is part of the Martinelli grid geographic information system (GIS). Many GIS projects use an approach in which existing mapped information is digitized into the GIS database directly from the original sources. The maps may have different map scale, map-unit resolutions, dates of data collection, and classification systems. When these different sources are combined in a GIS, artifacts may arise due to boundary mismatches and scale incompatibility (Dangermond and Harnden 1990). Integrated geobotanical mapping can minimize many of these problems. This method simultaneously maps vegetation and other terrain features that are interpreted on a common air-photo base (Everett et al. 1978, Walker et al. 1980). We use the term geobotany in its traditional European sense to refer to the study of plant communities and their relationships to geology, landforms, and soils (Braun-Blanquet 1932). Terrain geomorphic boundaries are used to guide the delineation on aerial photographs of most major vegetation boundaries similiar to the landscape-guided vegetation mapping approach developed in Europe (Zonneveld 1988) and the integrated terrain unit mapping approach developed by the Environmental System Research Institute in Redlands, CA (Dangermond and Harnden 1990). Additional information concerning the Niwot Ridge LTER GIS can be found in Walker et al. (1993). [1]Braun-Blanquet, J. 1932. Plant sociology: The study of plant communities. New York: McGraw-Hill, 439 pp. [2]Everett, K.R., P.J. Webber, D.A. Walker, R.J. Parkinson, and J. Brown. 1978. A geoecological mapping scheme for Alaskan coastal tundra. Third International Conference on Permafrost, 10-13 July 1978, Edmonton, Alberta, Canada. [3]Komarkova, V. 1979. Alpine vegetation of the Indian Peaks area, Front Range, Colorado Rocky Mountains. Vaduz (Germany): J. Cramer, 591 pp. [4]Walker, D.A., K.R. Everett, P.J. Webber, and J. Brown. 1980. Geobotanical atlas of the Prudhoe Bay region, Alaska. United States Army Cold Regions Research and Engineering Laboratory, CRREL Report #80, Hanover, NH, 69 pp. [5]Zonneveld, I.S. 1988. The ITC method of mapping natural and semi- natural vegetation. Pp. 401-426 in Kuchler, A.W., and I.S. Zonneveld (eds.). Vegetation mapping. Boston: Kluwer Academic. [6]Dangermond, J., and E. Harnden. 1990. Map data standardization: A methodology for integrating thematic cartographic data before automation. ARC News 12(2): 16-19. [7]Walker, D.A., J.C. Halfpenny, M.D. Walker, and C.A. Wessman. 1993. Long-term studies of snow-vegetation interactions. Bioscience 43(5): 287-301. [8]Walker, D.A., B.E. Lewis, W.B. Krantz, E.T. Price, and R.D. Tabler. 1994. Hierarchic studies of snow-ecosystem interactions: A 100-year snow-alteration experiment. Pp. 407-414 In: Ferrik, M. (ed.). Proceedings of the Fiftieth Annual Eastern and Western Snow Conference, Quebec City, Quebec, Canada, 8-10 June 1993. 441 pp.

A 300 x 600 m integrated terrain unit map (ITUM) was produced at 1:500 scale inside the 350 x 650 m Martinelli grid, and the 1:500 digital elevation model (DEM). Vegetation was mapped using Komarkova's (1979) classification system (Braun-Blanquet) units. All map units were mapped to 1g8-inch minimum map-polygon-size resolution. The map is part of the Martinelli grid geographic information system (GIS). Many GIS projects use an approach in which existing mapped information is digitized into the GIS database directly from the original sources. The maps may have different map scale, map-unit resolutions, dates of data collection, and classification systems. When these different sources are combined in a GIS, artifacts may arise due to boundary mismatches and scale incompatibility (Dangermond and Harnden 1990). Integrated geobotanical mapping can minimize many of these problems. This method simultaneously maps vegetation and other terrain features that are interpreted on a common air-photo base (Everett et al. 1978, Walker et al. 1980). We use the term geobotany in its traditional European sense to refer to the study of plant communities and their relationships to geology, landforms, and soils (Braun-Blanquet 1932). Terrain geomorphic boundaries are used to guide the delineation on aerial photographs of most major vegetation boundaries similiar to the landscape-guided vegetation mapping approach developed in Europe (Zonneveld 1988) and the integrated terrain unit mapping approach developed by the Environmental System Research Institute in Redlands, CA (Dangermond and Harnden 1990). Additional information concerning the Niwot Ridge LTER GIS can be found in Walker et al. (1993).

Regional Housing Needs Allocation (RHNA) & Rezone Parcels for the City of Redlands Housing Element.

A 350 x 500 m integrated terrain unit map (ITUM) was produced at 1:500 scale inside the 350 x 500 m saddle grid, and the 1:500 digital elevation model (DEM). Vegetation was mapped using Komarkova's (1979) classification system (Braun-Blanquet) units. All map units were mapped to 1/8-inch minimum map-polygon-size resolution. The map is part of the Saddle grid geographic information system (GIS). Many GIS projects use an approach in which existing mapped information is digitized into the GIS database directly from the original sources. The maps may have different map scale, map-unit resolutions, dates of data collection, and classification systems. When these different sources are combined in a GIS, artifacts may arise due to boundary mismatches and scale incompatibility (Dangermond and Harnden 1990). Integrated geobotanical mapping can minimize many of these problems. This method simultaneously maps vegetation and other terrain features that are interpreted on a common air-photo base (Everett et al. 1978, Walker et al. 1980). We use the term geobotany in its traditional European sense to refer to the study of plant communities and their relationships to geology, landforms, and soils (Braun-Blanquet 1932). Terrain geomorphic boundaries are used to guide the delineation on aerial photographs of most major vegetation boundaries similiar to the landscape-guided vegetation mapping approach developed in Europe (Zonneveld 1988) and the integrated terrain unit mapping approach developed by the Environmental System Research Institute in Redlands, CA (Dangermond and Harnden 1990). Additional information concerning the Niwot Ridge LTER GIS can be found in Walker et al. (1993). [1]Braun-Blanquet, J. 1932. Plant sociology: The study of plant communities. New York: McGraw-Hill, 439 pp. [2]Everett, K.R., P.J. Webber, D.A. Walker, R.J. Parkinson, and J. Brown. 1978. A geoecological mapping scheme for Alaskan coastal tundra. Third International Conference on Permafrost, 10-13 July 1978, Edmonton, Alberta, Canada. [3]Komarkova, V. 1979. Alpine vegetation of the Indian Peaks area, Front Range, Colorado Rocky Mountains. Vaduz (Germany): J. Cramer, 591 pp. [4]Walker, D.A., K.R. Everett, P.J. Webber, and J. Brown. 1980. Geobotanical atlas of the Prudhoe Bay region, Alaska. United States Army Cold Regions Research and Engineering Laboratory, CRREL Report #80, Hanover, NH, 69 pp. [5]Halfpenny, J.C., K.P. Ingraham, J.A. Adams. 1983. Working Atlas for the Saddle, Niwot Ridge, Front Range, Colorado. Long-Term Ecolological Research Data Report, April 1983, 24 pp. [6]Zonneveld, I.S. 1988. The ITC method of mapping natural and semi- natural vegetation. Pp. 401-426 in Kuchler, A.W., and I.S. Zonneveld (eds.). Vegetation mapping. Boston: Kluwer Academic. [7]Dangermond, J., and E. Harnden. 1990. Map data standardization: A methodology for integrating thematic cartographic data before automation. ARC News 12(2): 16-19. [8]Walker, D.A., J.C. Halfpenny, M.D. Walker, and C.A. Wessman. 1993. Long-term studies of snow-vegetation interactions. Bioscience 43(5): 287-301. [9]Walker, D.A., B.E. Lewis, W.B. Krantz, E.T. Price, and R.D. Tabler. 1994. Hierarchic studies of snow-ecosystem interactions: A 100-year snow-alteration experiment. Pp. 407-414 In: Ferrik, M. (ed.). Proceedings of the Fiftieth Annual Eastern and Western Snow Conference, Quebec City, Quebec, Canada, 8-10 June 1993. 441 pp. NOTE: This EML metadata file does not contain important geospatial data processing information. Before using any NWT LTER geospatial data read the arcgis metadata XML file in either ISO or FGDC compliant format, using ArcGIS software (ArcCatalog > description), or by viewing the .xml file provided with the geospatial dataset.

A 350 x 500 m integrated terrain unit map (ITUM) was produced at 1:500 scale inside the 350 x 500 m saddle grid, and the 1:500 digital elevation model (DEM). Vegetation was mapped using Komarkova's (1979) classification system (Braun-Blanquet) units. All map units were mapped to 1g8-inch minimum map-polygon-size resolution. The map is part of the Saddle grid geographic information system (GIS). Many GIS projects use an approach in which existing mapped information is digitized into the GIS database directly from the original sources. The maps may have different map scale, map-unit resolutions, dates of data collection, and classification systems. When these different sources are combined in a GIS, artifacts may arise due to boundary mismatches and scale incompatibility (Dangermond and Harnden 1990). Integrated geobotanical mapping can minimize many of these problems. This method simultaneously maps vegetation and other terrain features that are interpreted on a common air-photo base (Everett et al. 1978, Walker et al. 1980). We use the term geobotany in its traditional European sense to refer to the study of plant communities and their relationships to geology, landforms, and soils (Braun-Blanquet 1932). Terrain geomorphic boundaries are used to guide the delineation on aerial photographs of most major vegetation boundaries similiar to the landscape-guided vegetation mapping approach developed in Europe (Zonneveld 1988) and the integrated terrain unit mapping approach developed by the Environmental System Research Institute in Redlands, CA (Dangermond and Harnden 1990). Additional information concerning the Niwot Ridge LTER GIS can be found in Walker et al. (1993).

U.S. Census Bureau QuickFacts statistics for Redland CDP, Alabama. QuickFacts data are derived from: Population Estimates, American Community Survey, Census of Population and Housing, Current Population Survey, Small Area Health Insurance Estimates, Small Area Income and Poverty Estimates, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits.

Tracklines and associated observations were mapped and analyzed using ArcMap (ESRI, Redlands, CA). GPS data were recorded in NAD27 map datum and projected to an USGS Albers Equal Area Conic map projection for presentation and subsequent density analyses. Concatenated GPS and observation data were then used to generate point and line coverages in ArcMap (ESRI, Redlands, CA). We designed a custom analytic tool using ArcMap Model Builder that allows for the construction and export of user-specified and effort-adjusted spatial binning of species observations along continuous trackines. For the purposes of this report, we calculated seabird density estimates and marine mammal counts along continuous 3.0-kilometer and 7.7-kilometer trackline segments (i.e., 3.0 kilometer and 7.7 kilometer bins). Therefore, marine bird densities (at 3-kilometer scale, for example) are based on a composite strip area ranging from 0.15 per kilometer squared (one observer on effort) to 0.30 per kilometer squared (two observers on effort). We made no effort to adjust densities such that they would be proportional to variations in the area of buffered transect strip bin (i.e., weighted offset variable). These data are associated with the following publication: Mason, J.W., McChesney, G.J., McIver, W.R., Carter, H.R., Takekawa, J.Y., Golightly, R.T., Ackerman, J.T., Orthmeyer, D.L., Perry, W.M., Yee, J.L. and Pierson, M.O. 2007. At-sea distribution and abundance of seabirds off southern California: a 20-Year comparison. Cooper Ornithological Society, Studies in Avian Biology Vol. 33. References- ESRI. ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research Institute.

Analysis of ‘Peninsular Bighorn Sheep Habitat Vegetation Map [ds2660]’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/98b073c5-53df-418e-b9f8-ad694e008f0e on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Aerial Information Systems, Inc. (AIS) was contracted by the Coachella Valley Conservation Commission (CVCC) through a Local Assistance Grant originating from the California Department of Fish and Wildlife (CDFW) to map and describe the essential habitats for bighorn sheep monitoring within the San Jacinto-Santa Rosa Mountains Conservation Area. This effort was completed in support of the Coachella Valley Multiple Species Habitat Conservation Plan (CVMSHCP). The completed vegetation map is consistent with the California Department of Fish and Wildlife classification methodology and mapping standards. The mapping area covers 187,465 acres of existing and potential habitat on the northern slopes of the San Jacinto and Santa Rosa Mountains ranging from near sea level to over 6000 feet in elevation. The map was prepared over a baseline digital image created in 2014 by the US Department of Agriculture '' Farm Service Agency''s National Agricultural Imagery Program (NAIP). Vegetation units were mapped using the National Vegetation Classification System (NVCS) to the Alliance (and in several incidences to the Association) level (See Appendix A for more detail) as described in the second edition of the Manual of California Vegetation Second Edition (Sawyer et al, 2009). The mapping effort was supported by extensive ground-based field gathering methods using CNPS rapid assessment protocol in the adjacent areas as part of the Desert Renewable Energy Conservation Plan (DRECP) to the north and east; and by the 2012 Riverside County Multiple Species Habitat Conservation Plan vegetation map in the western portion of Riverside County adjacent to the west. These ground-based data have been classified and described for the abovementioned adjacent regions and resultant keys and descriptions for those efforts have been used in part for this project.For detailed information please refer to the following report: Menke, J. and D. Johnson. 2015. Vegetation Mapping '' Peninsular Bighorn Sheep Habitat. Final Vegetation Mapping Report. Prepared for the Coachella Valley Conservation Commission. Aerial Information Systems, Inc., Redlands, CA.

--- Original source retains full ownership of the source dataset ---

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 web map shows the walkability times from Downtown Redlands in increments of 3, 5, 10, and 15 minutes.Feature layers include walkability buffer times, Omnitrans bus stops and route, Arrow Rail Line route and stations, downtown Redlands boundary, and Redlands city boundary.