Description

This dataset consist of two vector files which show the change in the building stock of the City of DaNang retrieved from satellite image analysis. Buildings were first identified from a Pléiades satellite image from 24.10.2015 and classified into 9 categories in a semi-automatic workflow desribed by Warth et al. (2019) and Vetter-Gindele et al. (2019).

In a second step, these buildings were inspected for changes based on a second Pléiades satellite image acquired on 13.08.2017 based on visual interpretation. Changes were also classified into 5 categories and aggregated by administrative wards (first dataset: adm) and a hexagon grid of 250 meter length (second dataset: hex).

The full workflow of the generation of this dataset, including a detailled description of its contents and a discussion on its potential use is published by Braun et al. 2020: Changes in the building stock of DaNang between 2015 and 2017

Contents

Both datasets (adm and hex) are stored as ESRI shapefiles which can be used in common Geographic Information Systems (GIS) and consist of the following parts:

shp: polygon geometries (geometries of the administrative boundaries and hexagons)

dbf: attribute table (containing the number of buildings per class for 2015 and 2017 and the underlying changes (e.g. number of new buildings, number of demolished buildings, ect.)

shx: index file combining the geometries with the attributes

cpg: encoding of the attributes (UTF-8)

prj: spatial reference of the datasets (UTM zone 49 North, EPSG:32649) for ArcGIS

qpj: spatial reference of the datasets (UTM zone 49 North, EPSG:32649) for QGIS

lyr: symbology suggestion for the polygons(predefined is the number of local type shophouses in 2017) for ArcGIS

qml: symbology suggestion for the polygons (predefined is the number of new buildings between 2015 and 2017) for QGIS

Citation and documentation

To cite this dataset, please refer to the publication

Braun, A.; Warth, G.; Bachofer, F.; Quynh Bui, T.T.; Tran, H.; Hochschild, V. (2020): Changes in the Building Stock of Da Nang between 2015 and 2017. Data, 5, 42. doi:10.3390/data5020042

This article contains a detailed description of the dataset, the defined building type classes and the types of changes which were analyzed. Furthermore, the article makes recommendations on the use of the datasets and discusses potential error sources.

The purpose of the American Indian and Alaska Native Land Area Representation (AIAN-LAR) Geographic Information System (GIS) dataset is to depict the external extent of federal Indian reservations and the external extent of associated land held in “trust” by the United States, “restricted fee” or “mixed ownership” status for federally recognized tribes and individual Indians. This dataset includes other land area types such as Public Domain Allotments, Dependent Indian Communities and Homesteads. This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes.No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary.The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices.Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust.These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation.The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.

This dataset has been created to support the research activities of Arizona State University researchers. The slope grid identifies the rate of maximum change in elevation value from each grid cell and is calculated in degrees. The data are derived from the 30 meter Digital Elevation Model created for the Central Arizona-Phoenix Long Term Ecological Research program (dem30_utm).

This is the GIS data and imagery used for analyses in the article
Sixty-seven years of land-use change in southern Costa Rica by Zahawi
et al. currently in revision at PLOS One.

This study required the orthorectification of historic aerial photographs, as well as forest cover mapping and landscape analysis of 320 km² around the Las Cruces Biological Station in San Vito de Coto Brus, Costa Rica. The imagery and GIS data generated were used to account for forest cover change over five different time periods from 1947 to 2014.

The datasets supplied include GIS files for:

• Extent of the study area (shapefile).
• Forest cover mapped for each time period (geotiff).
• Imagery of the mosaics generated with the orthorectified historic aerial photographs (geotiff).
• Age in studied time periods of the current forest patches (shapefile).
• Connectivity lines inside the studied area (shapefiles).

All files are in Costa Rica Transverse Mercator 2005 (CRTM05) projected coordinate reference system. For transformation between coordinate systems please refer to http://epsg.io/5367

Aerial photographs for the years 1947, 1960, 1980 and 1997 were acquired from the Organization for Tropical Studies GIS Lab and the Instituto Geográfico Nacional of Costa Rica. The orthorectification process was done first on the 1997 set of images and used the current 1:50,000 and 1:25,000 Costa Rican cartography to identify geographical reference points. The set of 1997 orthophotos was used as a reference set to orthorectify remaining years with the exception of 1947 images. The orthorectification process and all other geospatial analyses were done on the CRTM05 spatial reference system and the resulting orthophotos had a 2m cell size. The largest Root Mean Square error (RMSE) of the orthorectification of these three time slices of aerial photographs was 15 m.

Given the lack of information on flight parameters, and the expansive forest coverage in 1947 photographs, images were georeferenced and built into a mosaic using river basins and the few forest clearings that had a similar shape in the 1960 flyover. The 1947 set of images did not cover the whole study area, having empty areas without photographs that represented ˜12.1% of the analysis extent. Nonetheless, these areas were classified as forested given that forest was present in these same areas in the 1960 imagery.

Forest mapping was done by visual interpretation of orthophotos and Google imagery. The areas were considered forested if tree crowns were easily identified when viewing the images at a scale of 1:10,000. In areas where it was difficult to discern the type of land cover, a scale of 1:5,000 was used. This was done to eliminate agroforestry systems such as shaded coffee areas (with trees planted in rows) or very early stages of forest regeneration from the forest land-cover class. The analysis was done only in areas that were cloud free in the five time slices. This resulted in the elimination of 134 ha (~0.4%) from of the original area outlined above. Polygons were drawn over the different areas using QGIS and were transformed into raster files of 10 m cell size.

This data set is used for spatial reference, lookup for digital orthophotos, and other data that may be identified by PLSS sections.

The i12_InflowData dataset is a point feature class containing 33 point locations representing approximate reservoir inflow locations. Spatial references were developed during the Water Storage Investment Program (WSIP) climate change study conducted in 2016. A related table of timeseries data is provided that corresponds to each of these point locations. Timeseries data reflect a simulation period from 10/31/1921 through 9/30/2011.

Analysis of ‘IRWM Regions’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/cbc38f6e-2dbb-4e4b-9b67-bc9815fb0030 on 27 January 2022.

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

NOTE: The IRWM polygons overlap each other. This polygon Feature Class includes IRWM planning regions participating in the State of California Department of Water Resources IRWM grant program. The data will be included as a component of the DWR Atlas of GIS data and be utilized as the feature data set for GIS projects requiring location of IRWM planning regions. This dataset is not to be utilized for survey purpose and is not designed to that accuracy level. Size of initial data set is 622 KB. Including additional attributes, the dataset is not expected to exceed 700 KB in size. Updates to this data will be once a year or as needed in conjunction with the IRWM Regional Boundaries dataset updates. Some IRWM Regions may decide not to participate in the grant program and will be in the attribute table with no spatial reference. An attribute called “Status” may be added to the feature class table. The data steward will be in charge of updating the dataset and responsible for any versioning. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR GIS Spatial Data Standards. DWR makes no warranties or guarantees, either expressed or implied, as to the completeness, accuracy or correctness of the data, nor accepts or assumes any liability arising from or for any incorrect, incomplete or misleading subject data. Comments, problems improvements, updates or suggestions should be forwarded to the official GIS Data Steward as available and appropriate. The Region Acceptance Process (RAP) is a component of the Integrated Regional Water Management (IRWM) Program Guidelines and is used to evaluate and accept an IRWM region into the IRWM grant program. The RAP is not a grant funding application; however, acceptance of the composition of an IRWM region (including the IRWM region’s boundary) is required for DWR IRWM grant funding eligibility. This dataset includes:-the boundaries of the most current IRWM Regions (as submitted to DWR by the respective IRWM planning region)-their RAP status (Accepted or Conditional) as conferred by DWR the year each entity participated in the RAP-a descriptive field noting the date of any subsequent IRWM boundary changes submitted and accepted by DWR.

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

The dataset and the validation are fully described in a Nature Scientific Data Descriptor https://www.nature.com/articles/s41597-019-0265-5

If you want to use this dataset in an interactive environment, then use this link https://mybinder.org/v2/gh/GeographerAtLarge/TravelTime/HEAD

The following text is a summary of the information in the above Data Descriptor.

The dataset is a suite of global travel-time accessibility indicators for the year 2015, at approximately one-kilometre spatial resolution for the entire globe. The indicators show an estimated (and validated), land-based travel time to the nearest city and nearest port for a range of city and port sizes.

The datasets are in GeoTIFF format and are suitable for use in Geographic Information Systems and statistical packages for mapping access to cities and ports and for spatial and statistical analysis of the inequalities in access by different segments of the population.

These maps represent a unique global representation of physical access to essential services offered by cities and ports.

The datasets travel_time_to_cities_x.tif (where x has values from 1 to 12) The value of each pixel is the estimated travel time in minutes to the nearest urban area in 2015. There are 12 data layers based on different sets of urban areas, defined by their population in year 2015 (see PDF report).

travel_time_to_ports_x (x ranges from 1 to 5)

The value of each pixel is the estimated travel time to the nearest port in 2015. There are 5 data layers based on different port sizes.

Format Raster Dataset, GeoTIFF, LZW compressed Unit Minutes

Data type Byte (16 bit Unsigned Integer)

No data value 65535

Flags None

Spatial resolution 30 arc seconds

Spatial extent

Upper left -180, 85

Lower left -180, -60 Upper right 180, 85 Lower right 180, -60 Spatial Reference System (SRS) EPSG:4326 - WGS84 - Geographic Coordinate System (lat/long)

Temporal resolution 2015

Temporal extent Updates may follow for future years, but these are dependent on the availability of updated inputs on travel times and city locations and populations.

Methodology Travel time to the nearest city or port was estimated using an accumulated cost function (accCost) in the gdistance R package (van Etten, 2018). This function requires two input datasets: (i) a set of locations to estimate travel time to and (ii) a transition matrix that represents the cost or time to travel across a surface.

The set of locations were based on populated urban areas in the 2016 version of the Joint Research Centre’s Global Human Settlement Layers (GHSL) datasets (Pesaresi and Freire, 2016) that represent low density (LDC) urban clusters and high density (HDC) urban areas (https://ghsl.jrc.ec.europa.eu/datasets.php). These urban areas were represented by points, spaced at 1km distance around the perimeter of each urban area.

Marine ports were extracted from the 26th edition of the World Port Index (NGA, 2017) which contains the location and physical characteristics of approximately 3,700 major ports and terminals. Ports are represented as single points

The transition matrix was based on the friction surface (https://map.ox.ac.uk/research-project/accessibility_to_cities) from the 2015 global accessibility map (Weiss et al, 2018).

Code The R code used to generate the 12 travel time maps is included in the zip file that can be downloaded with these data layers. The processing zones are also available.

Validation The underlying friction surface was validated by comparing travel times between 47,893 pairs of locations against journey times from a Google API. Our estimated journey times were generally shorter than those from the Google API. Across the tiles, the median journey time from our estimates was 88 minutes within an interquartile range of 48 to 143 minutes while the median journey time estimated by the Google API was 106 minutes within an interquartile range of 61 to 167 minutes. Across all tiles, the differences were skewed to the left and our travel time estimates were shorter than those reported by the Google API in 72% of the tiles. The median difference was −13.7 minutes within an interquartile range of −35.5 to 2.0 minutes while the absolute difference was 30 minutes or less for 60% of the tiles and 60 minutes or less for 80% of the tiles. The median percentage difference was −16.9% within an interquartile range of −30.6% to 2.7% while the absolute percentage difference was 20% or less in 43% of the tiles and 40% or less in 80% of the tiles.

This process and results are included in the validation zip file.

Usage Notes The accessibility layers can be visualised and analysed in many Geographic Information Systems or remote sensing software such as QGIS, GRASS, ENVI, ERDAS or ArcMap, and also by statistical and modelling packages such as R or MATLAB. They can also be used in cloud-based tools for geospatial analysis such as Google Earth Engine.

The nine layers represent travel times to human settlements of different population ranges. Two or more layers can be combined into one layer by recording the minimum pixel value across the layers. For example, a map of travel time to the nearest settlement of 5,000 to 50,000 people could be generated by taking the minimum of the three layers that represent the travel time to settlements with populations between 5,000 and 10,000, 10,000 and 20,000 and, 20,000 and 50,000 people.

The accessibility layers also permit user-defined hierarchies that go beyond computing the minimum pixel value across layers. A user-defined complete hierarchy can be generated when the union of all categories adds up to the global population, and the intersection of any two categories is empty. Everything else is up to the user in terms of logical consistency with the problem at hand.

The accessibility layers are relative measures of the ease of access from a given location to the nearest target. While the validation demonstrates that they do correspond to typical journey times, they cannot be taken to represent actual travel times. Errors in the friction surface will be accumulated as part of the accumulative cost function and it is likely that locations that are further away from targets will have greater a divergence from a plausible travel time than those that are closer to the targets. Care should be taken when referring to travel time to the larger cities when the locations of interest are extremely remote, although they will still be plausible representations of relative accessibility. Furthermore, a key assumption of the model is that all journeys will use the fastest mode of transport and take the shortest path.

🇺🇸 United States English NOTE: The IRWM polygons overlap each other. This polygon Feature Class includes IRWM planning regions participating in the State of California Department of Water Resources IRWM grant program. The data will be included as a component of the DWR Atlas of GIS data and be utilized as the feature data set for GIS projects requiring location of IRWM planning regions. This dataset is not to be utilized for survey purpose and is not designed to that accuracy level. Size of initial data set is 622 KB. Including additional attributes, the dataset is not expected to exceed 700 KB in size. Updates to this data will be once a year or as needed in conjunction with the IRWM Regional Boundaries dataset updates. Some IRWM Regions may decide not to participate in the grant program and will be in the attribute table with no spatial reference. An attribute called “Status” may be added to the feature class table. The data steward will be in charge of updating the dataset and responsible for any versioning. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR GIS Spatial Data Standards. DWR makes no warranties or guarantees, either expressed or implied, as to the completeness, accuracy or correctness of the data, nor accepts or assumes any liability arising from or for any incorrect, incomplete or misleading subject data. Comments, problems improvements, updates or suggestions should be forwarded to the official GIS Data Steward as available and appropriate. The Region Acceptance Process (RAP) is a component of the Integrated Regional Water Management (IRWM) Program Guidelines and is used to evaluate and accept an IRWM region into the IRWM grant program. The RAP is not a grant funding application; however, acceptance of the composition of an IRWM region (including the IRWM region’s boundary) is required for DWR IRWM grant funding eligibility. This dataset includes:-the boundaries of the most current IRWM Regions (as submitted to DWR by the respective IRWM planning region)-their RAP status (Accepted or Conditional) as conferred by DWR the year each entity participated in the RAP-a descriptive field noting the date of any subsequent IRWM boundary changes submitted and accepted by DWR.

The i12_CalSim_Output dataset is a point feature class containing 44 point locations representing a subset of CalSim II output locations. A related table of timeseries data is provided that corresponds to each of these point locations. Timeseries data reflect a simulation period from 10/31/1921 through 9/30/2003 as simulated by the CalSim II model. Multiple CalSim II model simulations are included to reflect projected changes in climate for early-century (2030) and late-century (2070) model simulations (including 2070 drier extreme warming [DEW] scenario and wetter moderate warming [WMW] scenario). Spatial references were developed during the Water Storage Investment Program (WSIP) climate change study conducted in 2016. The user should use caution and fully understand the limitations of these datasets before applying them in a water budget calculation as these datasets correspond to model simulation outputs that contain their own assumptions and limitations.

Service Lanes as identified in the Taupō District Plan. Service Lanes have specific rules relating to them in the Operative District Plan.

The Taupō District Plan has been operative since 2007. Selected datasets from the Taupō District Plan have been made available for download to allow for better public access to the data underlying the plan. Note that some features mapped for district plan purposes may have changed over time. Taupō District Council does not make any representation or give any warranty as to the accuracy or exhaustiveness of the District Plan data released for public download. The data provided is indicative only and does not purport to be a complete database of all information in Taupō District Council's possession or control. Taupō District Council shall not be liable for any loss, damage, cost or expense (whether direct or indirect) arising from reliance upon or use of any data provided, or Council's failure to provide this data. While you are free to crop, export and repurpose the data, we ask that you attribute the Taupō District Council and clearly state that your work is a derivative and not the authoritative data source. Please include this statement when distributing any work derived from this data:

This work is a derivative of the Taupō District Plan. You can view the full Taupō District E-Plan here: https://eplan.taupodc.govt.nz/eplan

Date Created

14 March 2025

Date Modified

Modified as per National Planning Standards 2025.

Review Date

Department Responsible

Policy Team

Creation Method

Developed as part of Plan Change 40

Data Source

Taupo District Council

Spatial Reference

NZGD2000 / New Zealand Transverse Mercator 2000

Digital orthophotography of New Jersey, distributed as a Web Map Service (WMS). There are numerous layers in the service, one displaying the 2007 3 natural color bands, another displaying 2007 3 band false color infrared (near IR). The native data set spatial reference system is State Plane Coordinate System NAD83 Coordinates, U.S. Survey Feet. In most client software, the default spatial reference system of the service will be Geographic Coordinates, WGS84. Several other coordinate systems are supported (see Distribution Information section).Multi-spectral digital orthophotography was produced at a scale of 1:2400 (1" = 200') with a 1 foot pixel resolution for the State of New Jersey totaling approximately 8,162 square miles. The GeoTIFF tiles delivered to the State of New Jersey were then converted to lossless JPEG2000 files, which are used in this service.Aerial photography of the entire State of New Jersey was captured during March-May, 2007. Two flight dates (4-30-07 and 5-3-07 were rejected from the original 2007 flight due to excessive leaf conditions. Spring 2008 re-flights were planned and acquired in three missions dating: April 3rd, 10th, and 15th of 2008. The final orthophotos for parts of Warren, Hunterdon, Sussex, Passaic, Essex, Union, and all of Bergen and Hudson Counties were created utilizing both years of imagery.

Analysis of ‘IRWM Regions’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/4a01a42f-bc64-493b-ac59-b6ed65aaddea on 27 January 2022.

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

NOTE: The IRWM polygons overlap each other. This polygon Feature Class includes IRWM planning regions participating in the State of California Department of Water Resources IRWM grant program. The data will be included as a component of the DWR Atlas of GIS data and be utilized as the feature data set for GIS projects requiring location of IRWM planning regions. This dataset is not to be utilized for survey purpose and is not designed to that accuracy level. Size of initial data set is 622 KB. Including additional attributes, the dataset is not expected to exceed 700 KB in size. Updates to this data will be once a year or as needed in conjunction with the IRWM Regional Boundaries dataset updates. Some IRWM Regions may decide not to participate in the grant program and will be in the attribute table with no spatial reference. An attribute called “Status” may be added to the feature class table. The data steward will be in charge of updating the dataset and responsible for any versioning. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR GIS Spatial Data Standards. DWR makes no warranties or guarantees, either expressed or implied, as to the completeness, accuracy or correctness of the data, nor accepts or assumes any liability arising from or for any incorrect, incomplete or misleading subject data. Comments, problems improvements, updates or suggestions should be forwarded to the official GIS Data Steward as available and appropriate. The Region Acceptance Process (RAP) is a component of the Integrated Regional Water Management (IRWM) Program Guidelines and is used to evaluate and accept an IRWM region into the IRWM grant program. The RAP is not a grant funding application; however, acceptance of the composition of an IRWM region (including the IRWM region’s boundary) is required for DWR IRWM grant funding eligibility. This dataset includes:-the boundaries of the most current IRWM Regions (as submitted to DWR by the respective IRWM planning region)-their RAP status (Accepted or Conditional) as conferred by DWR the year each entity participated in the RAP-a descriptive field noting the date of any subsequent IRWM boundary changes submitted and accepted by DWR.

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

In Oklahoma, historic depictions of the land areas representations, as described in 1867-1870, were developed and called Tribal Statistical Areas (TSA) in the AIAN-LAR. These areas are similar to the Bureau of Census Oklahoma Tribal Statistical Areas (OTSA) which are areas used for the collection, tabulation and presentation of decennial census data for the 36 Federally- recognized American Indian tribes located in the state. No legal inference can or should be made from the TSA information in the GIS dataset. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate tribe and then the BIA to obtain interpretations of the reservation boundary. This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary. The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices. Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust. These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation. The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.

Shaded relief map service of San Mateo County. Derived from aerial imagery acquired in 2006. For use as a basemap in online maps and to show elevation change using shading.

Spatial Reference: 102643 (2227) Pixel Size X: 5.0 Pixel Size Y: 5.0 Band Count: 3

More information about the service itself can be found here: http://gis.co.sanmateo.ca.us/arcgis/rest/services/COMMON/SanMateoCounty_ShadedRelief2006/ImageServer

The purpose of the American Indian and Alaska Native Land Area Representation (AIAN-LAR) Geographic Information System (GIS) dataset is to depict the external extent of federal Indian reservations and the external extent of associated land held in “trust” by the United States, “restricted fee” or “mixed ownership” status for federally recognized tribes and individual Indians. This dataset includes other land area types such as Public Domain Allotments, Dependent Indian Communities and Homesteads. This GIS Dataset is prepared strictly for illustrative and reference purposes only and should not be used, and is not intended for legal, survey, engineering or navigation purposes. No warranty is made by the Bureau of Indian Affairs (BIA) for the use of the data for purposes not intended by the BIA. This GIS Dataset may contain errors. There is no impact on the legal status of the land areas depicted herein and no impact on land ownership. No legal inference can or should be made from the information in this GIS Dataset. The GIS Dataset is to be used solely for illustrative, reference and statistical purposes and may be used for government to government Tribal consultation. Reservation boundary data is limited in authority to those areas where there has been settled Congressional definition or final judicial interpretation of the boundary. Absent settled Congressional definition or final judicial interpretation of a reservation boundary, the BIA recommends consultation with the appropriate Tribe and then the BIA to obtain interpretations of the reservation boundary. The land areas and their representations are compilations defined by the official land title records of the Bureau of Indian Affairs (BIA) which include treaties, statutes, Acts of Congress, agreements, executive orders, proclamations, deeds and other land title documents. The trust, restricted, and mixed ownership land area shown here, are suitable only for general spatial reference and do not represent the federal government’s position on the jurisdictional status of Indian country. Ownership and jurisdictional status is subject to change and must be verified with plat books, patents, and deeds in the appropriate federal and state offices. Included in this dataset are the exterior extent of off reservation trust, restricted fee tracts and mixed tracts of land including Public Domain allotments, Dependent Indian Communities, Homesteads and government administered lands and those set aside for schools and dormitories. There are also land areas where there is more than one tribe having an interest in or authority over a tract of land but this information is not specified in the AIAN-LAR dataset. The dataset includes both surface and subsurface tracts of land (tribal and individually held) “off reservation” tracts and not simply off reservation “allotments” as land has in many cases been subsequently acquired in trust. These data are public information and may be used by various organizations, agencies, units of government (i.e., Federal, state, county, and city), and other entities according to the restrictions on appropriate use. It is strongly recommended that these data be acquired directly from the BIA and not indirectly through some other source, which may have altered or integrated the data for another purpose for which they may not have been intended. Integrating land areas into another dataset and attempting to resolve boundary differences between other entities may produce inaccurate results. It is also strongly recommended that careful attention be paid to the content of the metadata file associated with these data. Users are cautioned that digital enlargement of these data to scales greater than those at which they were originally mapped can cause misinterpretation. The BIA AIAN-LAR dataset’s spatial accuracy and attribute information are continuously being updated, improved and is used as the single authoritative land area boundary data for the BIA mission. These data are available through the Bureau of Indian Affairs, Office of Trust Services, Division of Land Titles and Records, Branch of Geospatial Support.