USGS is assessing the feasibility of map projections and grid systems for lunar surface operations. We propose developing a new Lunar Transverse Mercator (LTM), the Lunar Polar Stereographic (LPS), and the Lunar Grid Reference Systems (LGRS). We have also designed additional grids designed to NASA requirements for astronaut navigation, referred to as LGRS in Artemis Condensed Coordinates (ACC), but this is not released here. LTM, LPS, and LGRS are similar in design and use to the Universal Transverse Mercator (UTM), Universal Polar Stereographic (LPS), and Military Grid Reference System (MGRS), but adhere to NASA requirements. LGRS ACC format is similar in design and structure to historic Army Mapping Service Apollo orthotopophoto charts for navigation. The Lunar Transverse Mercator (LTM) projection system is a globalized set of lunar map projections that divides the Moon into zones to provide a uniform coordinate system for accurate spatial representation. It uses a transverse Mercator projection, which maps the Moon into 45 transverse Mercator strips, each 8°, longitude, wide. These transverse Mercator strips are subdivided at the lunar equator for a total of 90 zones. Forty-five in the northern hemisphere and forty-five in the south. LTM specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large areas with high positional accuracy while maintaining consistent scale. The Lunar Polar Stereographic (LPS) projection system contains projection specifications for the Moon’s polar regions. It uses a polar stereographic projection, which maps the polar regions onto an azimuthal plane. The LPS system contains 2 zones, each zone is located at the northern and southern poles and is referred to as the LPS northern or LPS southern zone. LPS, like is equatorial counterpart LTM, specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large polar areas with high positional accuracy, while maintaining consistent scale across the map region. LGRS is a globalized grid system for lunar navigation supported by the LTM and LPS projections. LGRS provides an alphanumeric grid coordinate structure for both the LTM and LPS systems. This labeling structure is utilized in a similar manner to MGRS. LGRS defines a global area grid based on latitude and longitude and a 25×25 km grid based on LTM and LPS coordinate values. Two implementations of LGRS are used as polar areas require a LPS projection and equatorial areas a transverse Mercator. We describe the difference in the techniques and methods report associated with this data release. Request McClernan et. al. (in-press) for more information. ACC is a method of simplifying LGRS coordinates and is similar in use to the Army Mapping Service Apollo orthotopophoto charts for navigation. These data will be released at a later date. Two versions of the shape files are provided in this data release, PCRS and Display only. See LTM_LPS_LGRS_Shapefiles.zip file. PCRS are limited to a single zone and are projected in either LTM or LPS with topocentric coordinates formatted in Eastings and Northings. Display only shapefiles are formatted in lunar planetocentric latitude and longitude, a Mercator or Equirectangular projection is best for these grids. A description of each grid is provided below: Equatorial (Display Only) Grids: Lunar Transverse Mercator (LTM) Grids: LTM zone borders for each LTM zone Merged LTM zone borders Lunar Polar Stereographic (LPS) Grids: North LPS zone border South LPS zone border Lunar Grid Reference System (LGRS) Grids: Global Areas for North and South LPS zones Merged Global Areas (8°×8° and 8°×10° extended area) for all LTM zones Merged 25km grid for all LTM zones PCRS Shapefiles:` Lunar Transverse Mercator (LTM) Grids: LTM zone borders for each LTM zone Lunar Polar Stereographic (LPS) Grids: North LPS zone border South LPS zone border Lunar Grid Reference System (LGRS) Grids: Global Areas for North and South LPS zones 25km Gird for North and South LPS zones Global Areas (8°×8° and 8°×10° extended area) for each LTM zone 25km grid for each LTM zone The rasters in this data release detail the linear distortions associated with the LTM and LPS system projections. For these products, we utilize the same definitions of distortion as the U.S. State Plane Coordinate System. Scale Factor, k - The scale factor is a ratio that communicates the difference in distances when measured on a map and the distance reported on the reference surface. Symbolically this is the ratio between the maps grid distance and distance on the lunar reference sphere. This value can be precisely calculated and is provided in their defining publication. See Snyder (1987) for derivation of the LPS scale factor. This scale factor is unitless and typically increases from the central scale factor k_0, a projection-defining parameter. For each LPS projection. Request McClernan et. al., (in-press) for more information. Scale Error, (k-1) - Scale-Error, is simply the scale factor differenced from 1. Is a unitless positive or negative value from 0 that is used to express the scale factor’s impact on position values on a map. Distance on the reference surface are expended when (k-1) is positive and contracted when (k-1) is negative. Height Factor, h_F - The Height Factor is used to correct for the difference in distance caused between the lunar surface curvature expressed at different elevations. It is expressed as a ratio between the radius of the lunar reference sphere and elevations measured from the center of the reference sphere. For this work, we utilized a radial distance of 1,737,400 m as recommended by the IAU working group of Rotational Elements (Archinal et. al., 2008). For this calculation, height factor values were derived from a LOLA DEM 118 m v1, Digital Elevation Model (LOLA Science Team, 2021). Combined Factor, C_F – The combined factor is utilized to “Scale-To-Ground” and is used to adjust the distance expressed on the map surface and convert to the position on the actual ground surface. This value is the product of the map scale factor and the height factor, ensuring the positioning measurements can be correctly placed on a map and on the ground. The combined factor is similar to linear distortion in that it is evaluated at the ground, but, as discussed in the next section, differs numerically. Often C_F is scrutinized for map projection optimization. Linear distortion, δ - In keeping with the design definitions of SPCS2022 (Dennis 2023), we refer to scale error when discussing the lunar reference sphere and linear distortion, δ, when discussing the topographic surface. Linear distortion is calculated using C_F simply by subtracting 1. Distances are expended on the topographic surface when δ is positive and compressed when δ is negative. The relevant files associated with the expressed LTM distortion are as follows. The scale factor for the 90 LTM projections: LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_K_grid_scale_factor.tif Height Factor for the LTM portion of the Moon: LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_EF_elevation_factor.tif Combined Factor in LTM portion of the Moon LUNAR_LTM_GLOBAL_PLOT_HEMISPHERES_distortion_CF_combined_factor.tif The relevant files associated with the expressed LPS distortion are as follows. Lunar North Pole The scale factor for the northern LPS zone: LUNAR_LGRS_NP_PLOT_LPS_K_grid_scale_factor.tif Height Factor for the north pole of the Moon: LUNAR_LGRS_NP_PLOT_LPS_EF_elevation_factor.tif Combined Factor for northern LPS zone: LUNAR_LGRS_NP_PLOT_LPS_CF_combined_factor.tif Lunar South Pole Scale factor for the northern LPS zone: LUNAR_LGRS_SP_PLOT_LPS_K_grid_scale_factor.tif Height Factor for the south pole of the Moon: LUNAR_LGRS_SP_PLOT_LPS_EF_elevation_factor.tif Combined Factor for northern LPS zone: LUNAR_LGRS_SP_PLOT_LPS_CF_combined_factor.tif For GIS utilization of grid shapefiles projected in Lunar Latitude and Longitude, referred to as “Display Only”, please utilize a registered lunar geographic coordinate system (GCS) such as IAU_2015:30100 or ESRI:104903. LTM, LPS, and LGRS PCRS shapefiles utilize either a custom transverse Mercator or polar Stereographic projection. For PCRS grids the LTM and LPS projections are recommended for all LTM, LPS, and LGRS grid sizes. See McClernan et. al. (in-press) for such projections. Raster data was calculated using planetocentric latitude and longitude. A LTM and LPS projection or a registered lunar GCS may be utilized to display this data. Note: All data, shapefiles and rasters, require a specific projection and datum. The projection is recommended as LTM and LPS or, when needed, IAU_2015:30100 or ESRI:104903. The datum utilized must be the Jet Propulsion Laboratory (JPL) Development Ephemeris (DE) 421 in the Mean Earth (ME) Principal Axis Orientation as recommended by the International Astronomy Union (IAU) (Archinal et. al., 2008).

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state but may extend across county and county subdivision boundaries. An incorporated place is usually a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs are often defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2024, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2024 BAS as well.

USGS is assessing the feasibility of map projections and grid systems for lunar surface operations. We propose developing a new Lunar Transverse Mercator (LTM), the Lunar Polar Stereographic (LPS), and the Lunar Grid Reference Systems (LGRS). We have also designed additional grids designed to NASA requirements for astronaut navigation, referred to as LGRS in Artemis Condensed Coordinates (ACC). This data release includes LGRS grids finer than 25km (1km, 100m, and 10m) in ACC format. LTM, LPS, and LGRS grids are not released here but may be acceded from https://doi.org/10.5066/P13YPWQD. LTM, LPS, and LGRS are similar in design and use to the Universal Transverse Mercator (UTM), Universal Polar Stereographic (LPS), and Military Grid Reference System (MGRS), but adhere to NASA requirements. LGRS ACC format is similar in design and structure to historic Army Mapping Service Apollo orthotopophoto charts for navigation. The Lunar Transverse Mercator (LTM) projection system is a globalized set of lunar map projections that divides the Moon into zones to provide a uniform coordinate system for accurate spatial representation. It uses a Transverse Mercator projection, which maps the Moon into 45 transverse Mercator strips, each 8°, longitude, wide. These Transverse Mercator strips are subdivided at the lunar equator for a total of 90 zones. Forty-five in the northern hemisphere and forty-five in the south. LTM specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large areas with high positional accuracy while maintaining consistent scale. The Lunar Polar Stereographic (LPS) projection system contains projection specifications for the Moon’s polar regions. It uses a polar stereographic projection, which maps the polar regions onto an azimuthal plane. The LPS system contains 2 zones, each zone is located at the northern and southern poles and is referred to as the LPS northern or LPS southern zone. LPS, like its equatorial counterpart LTM, specifies a topocentric, rectangular, coordinate system (easting and northing coordinates) for spatial referencing. This projection is commonly used in GIS and surveying for its ability to represent large polar areas with high positional accuracy while maintaining consistent scale across the map region. LGRS is a globalized grid system for lunar navigation supported by the LTM and LPS projections. LGRS provides an alphanumeric grid coordinate structure for both the LTM and LPS systems. This labeling structure is utilized similarly to MGRS. LGRS defines a global area grid based on latitude and longitude and a 25×25 km grid based on LTM and LPS coordinate values. Two implementations of LGRS are used as polar areas require an LPS projection and equatorial areas a Transverse Mercator. We describe the differences in the techniques and methods reported in this data release. Request McClernan et. al. (in-press) for more information. ACC is a method of simplifying LGRS coordinates and is similar in use to the Army Mapping Service Apollo orthotopophoto charts for navigation. These grids are designed to condense a full LGRS coordinate to a relative coordinate of 6 characters in length. LGRS in ACC format is completed by imposing a 1km grid within the LGRS 25km grid, then truncating the grid precision to 10m. To me the character limit, a coordinate is reported as a relative value to the lower-left corner of the 25km LGRS zone without the zone information; However, zone information can be reported. As implemented, and 25km^2 area on the lunar surface will have a set of a unique set of ACC coordinates to report locations The shape files provided in this data release are projected in the LTM or LPS PCRSs and must utilize these projections to be dimensioned correctly. LGRS ACC Grids Files and Resolution: LGRS ACC Grids in LPS portion: Amundsen_Rim 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Nobile_Rim_2 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Haworth 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Faustini_Rim_A 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile de_Gerlache_Rim_2 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Connecting_Ridge_Extension 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Connecting_Ridge 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Nobile_Rim_1 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Peak_Near_Shackleton 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile de_Gerlache_Rim' 'Leibnitz_Beta_Plateau 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Malapert_Massif 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile de_Gerlache-Kocher_Massif 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile LGRS ACC Grids in LTM portion: Apollo_11 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Apollo_12 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Apollo_14 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Apollo_15 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Apollo_16 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile Apollo_17 1km Grid Shapefile 100m Grid Shapefile 10m Grid Shapefile LTM, LPS, and LGRS PCRS shapefiles utilize either a custom transverse Mercator or polar Stereographic projection. For PCRS grids the LTM and LPS projections are recommended for all LTM, LPS, and LGRS grid sizes. See McClernan et. al. (in-press) for such projections. For GIS utilization of grid shapefiles projected in Lunar Latitude and Longitude should utilize a registered lunar geographic coordinate system (GCS) such as IAU_2015:30100 or ESRI:104903. This only applies to grids that cross multiple LTM zones. Note: All data, shapefiles require a specific projection and datum. The projection is recommended as LTM and LPS or, when needed, IAU_2015:30100 or ESRI:104903. The datum utilized must be the Jet Propulsion Laboratory (JPL) Development Ephemeris (DE) 421 in the Mean Earth (ME) Principal Axis Orientation as recommended by the International Astronomy Union (IAU) (Archinal et. al., 2008).

The TIGER/Line shapefilez and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation.

The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state, but may extend across county and county subdivision boundaries. An incorporated place usually is a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name, but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs often are defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population.

The boundaries of most incorporated places in this shapefile are as of January 1, 2015, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2010 Census.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Block groups are clusters of blocks within the same census tract. Each census tract contains at least one block group, and are uniquely numbered within census tracts. Block groups have a valid code range of 0 through 9. They also have the same first digit of their 4-digit census block number from the same decennial census. For example, tabulation blocks numbered 3001, 3002, 3003,.., 3999 within census tract 1210.02 are also within block group 3 within that census tract. Block groups coded 0 are intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. Block groups generally contain between 600 and 3,000 people. A block group usually covers a contiguous area but never crosses county or census tract boundaries. They may, however, cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. The block group boundaries in this release are those that were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census.

These line shapefiles trace apparent topographic and air-photo lineaments in various counties in Colorado. It was made in order to identify possible fault and fracture systems that might be conduits for geothermal fluids, as part of a DOE reconnaissance geothermal exploration program.

Geothermal fluids commonly utilize fault and fractures in competent rocks as conduits for fluid flow. Geothermal exploration involves finding areas of high near-surface temperature gradients, along with a suitable "plumbing system" that can provide the necessary permeability. Geothermal power plants can sometimes be built where temperature and flow rates are high.

This line shapefile is an attempt to use desktop GIS to delineate possible faults and fracture orientations and locations in highly prospective areas prior to an initial site visit. Geochemical sampling and geologic mapping could then be centered around these possible faults and fractures.

To do this, georeferenced topographic maps and aerial photographs were utilized in an existing GIS, using ESRI ArcMap 10.0 software. The USA_Topo_Maps and World_Imagery map layers were chosen from the GIS Server at server.arcgisonline.com, using a UTM Zone 13 NAD27 projection. This line shapefile was then constructed over that which appeared to be through-going structural lineaments in both the aerial photographs and topographic layers, taking care to avoid manmade features such as roads, fence lines, and utility right-of-ways. Still, it is unknown what actual features these lineaments, if they exist, represent.

Although the shapefiles are arranged by county, not all areas within any county have been examined for lineaments. Work was focused on either satellite thermal infrared anomalies, known hot springs or wells, or other evidence of geothermal systems. Finally, lineaments may be displaced somewhat from their actual location, due to such factors as shadow effects with low sun angles in the aerial photographs.

Credits: These lineament shapefile was created by Geothermal Development Associates, as part of a geothermal geologic reconnaissance performed by Flint Geothermal, LLC, of Denver Colorado.

Use Limitation: These shapefiles were constructed as an aid to geothermal exploration in preparation for a site visit for field checking. We make no claims as to the existence of the lineaments, their location, orientation, and/or nature.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) System (MTS). The MTS represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The TIGER/Line shapefiles include both incorporated places (legal entities) and census designated places or CDPs (statistical entities). An incorporated place is established to provide governmental functions for a concentration of people as opposed to a minor civil division (MCD), which generally is created to provide services or administer an area without regard, necessarily, to population. Places always nest within a state but may extend across county and county subdivision boundaries. An incorporated place is usually a city, town, village, or borough, but can have other legal descriptions. CDPs are delineated for the decennial census as the statistical counterparts of incorporated places. CDPs are delineated to provide data for settled concentrations of population that are identifiable by name but are not legally incorporated under the laws of the state in which they are located. The boundaries for CDPs are often defined in partnership with state, local, and/or tribal officials and usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity. CDP boundaries often change from one decennial census to the next with changes in the settlement pattern and development; a CDP with the same name as in an earlier census does not necessarily have the same boundary. The only population/housing size requirement for CDPs is that they must contain some housing and population. The boundaries of most incorporated places in this shapefile are as of January 1, 2024, as reported through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries of all CDPs were delineated as part of the Census Bureau's Participant Statistical Areas Program (PSAP) for the 2020 Census, but some CDPs were added or updated through the 2024 BAS as well.

Description: This zipfile contains three shapefiles of linear geometries showing channel networks across the SAFE landscape.

RIVERS_UTM.shp: From Igor Lysenko's SAFE pack, this is a river network with two areas, covering Maliau and the area around the SAFE experimental region. The network density is much higher in Maliau than SAFE and the channel network around SAFE is not complete. This is projected in UTM50N WGS84. LFEriver_SL.shp: This is provided (by Sarah Luke?) through Clare Wilkinson's GIS files and adds a critical missing stream for the Logged Forest Edge (LFE) catchment. This is projected in UTM50N WGS84. all_rivers.shp: This is provided through Clare Wilkinson's GIS files and provides streams for a single region covering Danum and the SAFE experimental region but not sampled watersheds in Oil Palm plantations to the south of SAFE. The original file is missing projection information (no .prj file) but other files in the same dataset are projected in RSO Timbalai 1948 and using this projection fits with the context of other data. The version uploaded onto Zenodo has been reprojected into UTM50N WGS84.Although the files are not consistent, they do contain channels and channel data that are referenced in some studies. The provenance of these files are unknown, although the following suggests that they may be traced using GPS or from imagery:

Incomplete coverage within the regions they cover. Treatment of larger rivers, changing from a single line feature showing the stream centreline (?) to double lines showing the river banks. Variation in network density: the western edge of all_rivers.shp shows a vertical band about 4 km wide of higher stream density than the rest of the region; RIVERS_UTM.shp shows marked differences in stream density between SAFE and Maliau.

Project: This dataset was collected as part of the following SAFE research project: SAFE CORE DATA XML metadata: GEMINI compliant metadata for this dataset is available here Files: This dataset consists of 2 files: SAFE_Alternative_Stream_network_metadata.xlsx, Preexisting_SAFE_river_files.zip SAFE_Alternative_Stream_network_metadata.xlsx This file only contains metadata for the files below Preexisting_SAFE_river_files.zip Description: Contains three shapefiles of channel networks. This file contains 3 data tables:

Feature properties (described in worksheet LFEriver_SL) Description: Field descriptions for shapefile properties Number of fields: 1 Number of data rows: Unavailable (table metadata description only). Fields:

Id: Identity of river (Field type: id)

Feature properties (described in worksheet RIVERS_UTM) Description: Field descriptions for shapefile properties Number of fields: 1 Number of data rows: Unavailable (table metadata description only). Fields:

NAME: Local name of segment (Field type: comments)

Feature properties (described in worksheet all_river_UTM50N_WGS84) Description: Field descriptions for shapefile properties Number of fields: 10 Number of data rows: Unavailable (table metadata description only). Fields:

FNODE_: Unknown (Field type: numeric) TNODE_: Unknown (Field type: numeric) LPOLY_: Unknown (Field type: numeric) RPOLY_: Unknown (Field type: numeric) LENGTH_MET: Length of channel segment in metres (Field type: numeric) RIV_YSC_: Unknown (Field type: numeric) RIV_YSC_ID: Unknown (Field type: numeric) CODE: Unknown (Field type: numeric) NAME: Local name of segment (Field type: comments) AREA: Local area of segment (Field type: comments)

Date range: 2010-10-01 to 2019-10-01 Latitudinal extent: 4.0223 to 5.9761 Longitudinal extent: 116.0242 to 117.9758

This dataset is presented in Figure 25 of Matsuoka et al. (in review, DOI XXXX).

This dataset presents the grounding line retreat by 2100 projected by a selected set of ISMIP6 model ensembles (Seroussi et al., https://doi.org/10.5194/tc-14-3033-2020) downloaded from Ghub https://theghub.org/resources/4748.

In total, 51 ISMIP6 experiments were used to calculate retreat probability here, including 12 experiments based on RCP8.5 scenarios from 6 CMIP5 models; 4 experiments based on RCP 2.6 scenarios from 2 CMIP5 models; 2 experiments testing ice-shelf collapse; 2 experiments testing the uncertainty in the basal-melt parameterization, and 2 experiments testing the uncertainty in the melt calibration. The retreat probability is represented by the count of the number of experiments projecting grounding line retreat (ranging 0 to 51) in each cell of 8 km by 8 km. The results are based on model output computed from the ISMIP6 native grids that vary between models (ranging from 8 to 32 km).

_ISMIP6_GL_retreat.shp:_ Grounding line retreat probability, representing the number of modelled retreat cells in IMSIP6 experiments.

For full details of the participating models and experiments, see Seroussi et al. (2020; https://doi.org/10.5194/tc-14-3033-2020).

Shapefile fields:

count: accumulated count of modelled grounding line retreat cells from 51 ISMIP6 model experiments. These values represent the total number of grid cells in which the ISMIP6 model experiments have simulated retreat, and were calculated using the 'Count Overlap' tool in QGIS.

sector: Antarctic sectors used in ISMIP6 analysis (Seroussi et al., 2020) on an 8 km grid, numbered from 1 to 18.

area: total area (in square kilometres) of all modelled grounding line retreat cells across 51 ISMIP6 experiments. Note: this is not a strict measure of total retreat area per sector. Instead, it reflects the combined spatial footprint of all grounding line retreat instances in each of these ISMIP6 experiments, derived from stacking all grounding line retreat polygons from these experiments. This approach highlights the maximum potential extent of grounding line retreat by 2100, as projected by the ensemble.

Workflow to create ISMIP6_GL_Retreat.shp:

For each Model/Experiment, original netCDF files of grounded ice area fraction were converted to polygon shapefiles. The grounding line was extracted where grounded ice area fraction =1.

For calculating the number of modelled retreat cells between 2016 and 2100 for each experiment, a polygon shapefile was created by differencing the 2016 and 2100 fully grounded model grid cells (i.e. where grounded ice area fraction = 1).

'_groundinglines_' contains individual grounding line positions as GIS polygon shapefiles for ISMIP6 experiments, file naming format: 'Group_ModelName_experiment_grounded_Year'. These were created from the original netCDF files of grounded ice area fraction, by selecting all cells where grounded ice area fraction =1.

UngroundedIceFrac.xlsx contains a summary of the area of ungrounded cells for each of the 18 sectors used in ISMIP6 (Seroussi et al., 2016). This includes the percentage of the grounding line that is projected to retreat at least 50 km from the present-day grounding line in different regions of Antarctica, based on the ISMIP6 experiments analysed here.

The IPUMS National Historical Geographic Information System (NHGIS) provides free online access to summary statistics and GIS files for U.S. censuses and other nationwide surveys from 1790 through the present. NHGIS boundary files are derived primarily from the U.S. Census Bureau's TIGER/Line files with numerous additions to represent historical (1790-1980) boundaries that do not appear in TIGER/Line files. For more recent boundary files (1990 or later), NHGIS typically makes only a few key changes to the TIGER/Line source: (1) we merge files that are available only for individual states or counties to produce new nationwide or statewide files, (2) we project the data into Esri's USA Contiguous Albers Equal Area Conic Projected Coordinate System, (3) we add a GISJOIN attribute field, which supplies standard identifiers that correspond to the GISJOIN identifiers in NHGIS data tables, (4) we rename files to use the NHGIS naming style and geographic-level codes, (5) we add NHGIS-specific metadata, and (6) most substantially, we erase coastal water areas to produce polygons that terminate at the U.S. coasts and Great Lakes shores.NHGIS derived this shapefile from the U.S. Census Bureau's 2023 TIGER/Line Shapefiles.

The IPUMS National Historical Geographic Information System (NHGIS) provides free online access to summary statistics and GIS files for U.S. censuses and other nationwide surveys from 1790 through the present. NHGIS boundary files are derived primarily from the U.S. Census Bureau's TIGER/Line files with numerous additions to represent historical (1790-1980) boundaries that do not appear in TIGER/Line files. For more recent boundary files (1990 or later), NHGIS typically makes only a few key changes to the TIGER/Line source: (1) we merge files that are available only for individual states or counties to produce new nationwide or statewide files, (2) we project the data into Esri's USA Contiguous Albers Equal Area Conic Projected Coordinate System, (3) we add a GISJOIN attribute field, which supplies standard identifiers that correspond to the GISJOIN identifiers in NHGIS data tables, (4) we rename files to use the NHGIS naming style and geographic-level codes, (5) we add NHGIS-specific metadata, and (6) most substantially, we erase coastal water areas to produce polygons that terminate at the U.S. coasts and Great Lakes shores.NHGIS derived this shapefile from the U.S. Census Bureau's 2023 TIGER/Line Shapefiles.

This file is based on the Geospatial Services Division's Official Protraction Diagram (OPD)and Leasing Maps (LM). Each offshore area is defined by an API Number corresponding to those in the API Bulletin Number D12A. OPDs are numbered using the United Nations International Map of the World Numbering System, and are generally named for land or hydrographic features contained within the limits of the diagram. This data set contains Official Protraction Diagram (OPD) and Leasing Map (LM) outlines in ESRI shape file formats for the BOEM Gulf of Mexico Region. The use of OPDs and LMs makes it easier to refer to individual blocks within a region or planning area. These diagrams were clipped along the Submerged Lands Act (SLA) boundary and along lines contained in the Continental Shelf Boundaries (CSB) GIS data files to show only those blocks or portions thereof within federal jurisdiction. Because GIS projection and topology functions can change or generalize coordinates, these GIS files are NOT an OFFICIAL record for the exact OPD boundaries. Only the paper OPD or a digital image of them serves as OFFICIAL records.Official Protraction Diagrams and other cadastre information the BOEM produces are generated in accordance with 30 Code of Federal Regulations (CFR) Part 556.8 Subpart A, (formerly Part 256.8 Subpart A (2010)) to support Federal land ownership and mineral resource management. Further information on the SLA and development of this line from baseline points can be found in OCS Report BOEM 99-0006: Boundary Development on the Outer Continental Shelf. https://www.boem.gov/BOEM-Newsroom/Library/Publications/1999/99-0006-pdf.aspx Because GIS projection and topology functions can change or generalize coordinates, and because shapefiles cannot represent true arcs, these GIS files are considered to be approximate and are NOT an OFFICIAL record for the exact block coordinates or areas. The Official Protraction Diagrams (OPDs)and Leasing Maps (LMs) and Supplemental Official Block Diagrams (SOBDs) serve as the legal definition for BOEM offshore boundary coordinates and area descriptions and can be found at the following location: https://www.boem.gov/Official-Protraction-Diagrams/. Contains the protraction polygons clipped on the fedstate (SLA-Boundary) as of March 15, 2013. Used ArcCatalog to create shape files.

This dataset contains information on household incomes within U.S. Census designated Block Groups, clipped to the Mohawk River Watershed. In order for others to use the information in the Census MAF/TIGER database in a geographic information system (GIS) or for other geographic applications, the Census Bureau releases to the public extracts of the database in the form of TIGER/Line Shapefiles. This data was collected by Stone Environmental, Inc. for the New York State Department of State with funds provided under Title 11 of the Environmental Protection Fund. The original dataset was re-projected and clipped for use in the Mohawk River Watershed Management Plan. The TIGER/Line Files are shapefiles and related database files (.dbf) that are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Block Groups (BGs) are defined before tabulation block delineation and numbering, but are clusters of blocks within the same census tract that have the same first digit of their 4-digit census block number from the same decennial census. For example, Census 2000 tabulation blocks 3001, 3002, 3003,.., 3999 within Census 2000 tract 1210.02 are also within BG 3 within that census tract. Census 2000 BGs generally contained between 600 and 3,000 people, with an optimum size of 1,500 people. Most BGs were delineated by local participants in the Census Bureau's Participant Statistical Areas Program (PSAP). The Census Bureau delineated BGs only where the PSAP participant declined to delineate BGs or where the Census Bureau could not identify any local PSAP participant. A BG usually covers a contiguous area. Each census tract contains at least one BG, and BGs are uniquely numbered within census tract. Within the standard census geographic hierarchy, BGs never cross county or census tract boundaries, but may cross the boundaries of other geographic entities like county subdivisions, places, urban areas, voting districts, congressional districts, and American Indian / Alaska Native / Native Hawaiian areas. BGs have a valid code range of 0 through 9. BGs coded 0 were intended to only include water area, no land area, and they are generally in territorial seas, coastal water, and Great Lakes water areas. For Census 2000, rather than extending a census tract boundary into the Great Lakes or out to the U.S. nautical three-mile limit, the Census Bureau delineated some census tract boundaries along the shoreline or just offshore. The Census Bureau assigned a default census tract number of 0 and BG of 0 to these offshore, water-only areas not included in regularly numbered census tract areas. Median household income data were sourced from the 2005 - 2009 American Community Survey, which replaced the long form questionnaire on the Decennial Census. Data and more information are available at http://factfinder.census.gov.Mohawk River Watershed Processing: The original files were clipped to the Mohawk watershed counties. The data was re-projected from GCS_North_American_1983 to UTM 18N, NAD 83.View Dataset on the GatewayView Dataset on the Gateway

This data set contains the Submerged Lands Act (SLA)boundary line (also known as the State Seaward Boundary (SSB) and Fed State Boundary) for the BOEM Pacific Region in ESRI ArcGIS shape file format. The SLA defines the seaward limit of a state owned submerged lands and the landward boundary of federally managed Outer Continental Shelf (OCS) lands. In the BOEM Pacific Region the SLA is projected 3 nautical miles offshore from the coastal baseline. Further information on the SLA and development of this line from baseline points can be found in OCS Report BOEM 99-0006: Boundary Development on the Outer Continental Shelf. The SLA boundary was developed using nautical charts, topographic maps, and hydrographic surveys to identify coastal baseline points. For California, there was a wide range of map scales used (1:200 – 1:100,000). The Minerals Management Service (MMS - the predecessor bureau to BOEM) used mapping software that was developed in-house to mathematically project the SLA boundary 3 nautical miles seaward from the baseline. For purposes of the SLA, all coordinates are assumed as absolute values with a precision of three decimals of a meter. For purposes other than the SLA, the actual positional precision for a scale of 1:40,000 is approximately 23 meters. In 1992, MMS adopted NADCON v.2.00 or better as the bureau standard horizontal datum transformation software, and reiterated that, for its purposes, “the World Geodetic System of 1984 (WGS 84) is considered equivalent to NAD 83 offshore of Alaska and the conterminous United States.” 57 Fed. Reg. 5168 (February 12, 1992). On December 24, 2014, the SLA boundary offshore of California was fixed (permanently immobilized) by a decree issued by the U.S. Supreme Court. United States v. California, 135 S. Ct. 563 (2014). For a detailed discussion on the fixing of the SLA boundary for California, please see http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Multi-Purpose-Marine-Cadastre-Map-Viewer/Court-Decisions.aspx Because GIS projection and topology functions can change or generalize coordinates, these GIS shape files are NOT an OFFICIAL record for the exact Submerged Lands Act Boundary.The official record is reflected through the coordinates listed in the decree, and the boundary shown on the BOEM Supplemental Official Block Diagrams, which are available at http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Pacific.aspx

This database consists of a series of maps showing estimates for the change in position of Hawaii shorelines caused by sea-level rise (SLR) of + 0.5, 1.1, 2.0, and 3.2 feet. Individual maps show perpendicular measurement axes and lines of predicted shoreline positions at mileposts along Hawaii state routes on the islands of Hawaii, Maui, Molokai, Oahu and Kauai previously identified for their vulnerability to the effects of climate change as part of the Statewide Coastal Highways Project Report.

Mileposts are identified by Brandes et al. (2019). State of Hawaii Department of Transportation (HDOT) state routes and county street centerline datasets are acquired from HDOT (2017) and HOLIS, C&CH (2017). Projected vegetation lines (long-lasting markers of the shoreline) are determined and reported by the Hawaii Coastal Geology Group (HCGG) in Anderson et al. (2018). Rate of projected erosion is determined as a mean value of rates along the measurement axis (magenta line) from the 2008 vegetation line (blue) to subsequent SLR vegetation lines (red, orange, yellow, and green). Dates for SLR elevations are reported by Anderson et al. (2018) using the IPCC AR5 high-end representative concentration pathway (RCP) 8.5 scenario as 2030 for 0.5 ft of SLR, 2050 for 1.1 ft of SLR, 2075 for 2.0 ft of SLR, and 2100 for 3.2 ft of SLR.

Please read ‘Description-Map of Projected Shoreline Change with Sea Level Rise.docx’ for detailed information.

References Anderson, T.R., Fletcher, C.H., Barbee, M.M., Romine, B.M., Lemmo, S., and Delevaux, J.M.S. (2018). Modeling multiple sea level rise stresses reveals up to twice the land at risk compared to strictly passive flooding methods. Scientific Reports, 8(1), 1–14. https://doi.org/10.1038/s41598-018-32658-x Brandes, H., Doygun, O., Rossi, C., Francis, O., Yang, L., and Togia, H., (2019) Coastal Road Exposure Susceptibility Index (CRESI) for the State of Hawaii Statewide Coastal Highway Program Report. Department of Civil and Environmental Engineering, University of Hawai'i at Manoa, doi: 10.17632/frr3fsx3j6.2. HDOT (State of Hawaii Department of Transportation). “StateRoutes_SDOT” [shapefile]. Scale Not Given. State Routes. Hawaii Statewide GIS Program. Retrieved from http://files.hawaii.gov/dbedt/op/gis/data/StateAndCountyRoutes.shp.zip (December 2017). HOLIS, C&CH (Honolulu Land Information System, City and County of Honolulu). “Oah_streets” [shapefile]. Scale Not Given. Oahu Street Centerlines. Hawaii Statewide GIS Program. Retrieved from http://geoportal.hawaii.gov/datasets/roads-honolulu-county (December 2017).

The Northern Circumpolar Soil Carbon Database version 2 (NCSCDv2) is a geospatial database created for the purpose of quantifying storage of organic carbon in soils of the northern circumpolar permafrost region down to a depth of 300 cm. The NCSCDv2 is based on polygons from different regional soils maps homogenized to the U.S. Soil Taxonomy. The NCSCDv2 contains information on fractions of coverage of different soil types (following U.S. Soil Taxonomy nomenclature) as well as estimated storage of soil organic carbon (kg/m2) between 0-30 cm, 0-100 cm, 100-200 cm and 200-300 cm depth. The database was compiled by combining and homogenizing several regional/national soil maps. To calculate storage of soil organic carbon, these soil maps have been linked to field-data on soil organic carbon storage from sites with circumpolar coverage. More information on database processing and properties can be found in the product guide. The data is stored as ESRI shapefiles with associated attribute table databases. There are separate zipped data-folders with: (1) a merged circumpolar dataset in the Lambert Azimuthal Equal Area (LAEA) projection, (2) a merged circumpolar dataset geographic latitude/longitude coordinates (WGS84), (3) all regions in separate shape-files, in LAEA projection and (4) all regions in separate shape-files with geographic latitude/longitude coordinates (WGS84). Citation

Dataset description: This repository contains data pertaining to the manuscript "Mawrth Vallis, Mars, classified using the NOAH-H deep-learning terrain classification system." submitted to Journal of Maps. NOAH-H Mosaics: Mawrth_Vallis_NOAHH_Mosaic_DC_IG_25cm4bit_20230121_reclass.zip This folder contain mosaics of terrain classifications for Mawrth Vallis, Mars, made by the Novelty or Anomaly Hunter - HiRISE (NOAH-H) deep learning convolutional neural network developed for the European Space Agency (ESA) by SCISYS Ltd. In coordination with the Open University Planetary Environments Group. These folders contain the NOAH-H mosaics, as well as ancillary files needed to display the NOAH-H products in geographic information software (GIS). Included are two large raster datasets, containing the NOAH-H classification for the entire study area. One uses the 14 descriptive classes of the terrain, and the other with the five interpretative groups (Barrett et al., 2022). · Mawrth_Vallis_NOAHH_Mosaic_DC_25cm4bit_20230121_reclass.tif Contains the full 14 class “Descriptive Classes” (DC) dataset, reclassified so that pixel values reflect the original NOAH-H ontology, and not the priority rankings described in Wright et al., (2022) and Barrett et al., (2022b). It is accompanied by all auxiliary files required to view the data in GIS. · Mawrth_Vallis_NOAHH_Mosaic_IG_25cm4bit_20230121_reclass.tif Contains the 5 class “Interpretive Groups” (IG) dataset, reclassified so that pixel values reflect the original NOAH-H ontology, and not the priority rankings described in Wright et al., (2022) and Barrett et al., (2022b). It is accompanied by all auxiliary files required to view the data in GIS. Symbology layer files: NOAH-H_Symbology.zip This folder contains GIS layer file and colour map files for both the Descriptive Classes (DC) and interpretive Groups (IG) versions of the classification. These can be applied to the data using the symbology options in GIS. Georeferencing Control points: Mawrth_Vallis_Final_Control_Points.zip This file contains the control points used to georeferenced the 26 individual HiRISE images which make up the mosaic. These allow publicly available HiRISE images to be aligned to the terrain in Mawrth Vallis, and thus the NOAH-H Mosaic. Twenty-six 25 cm/pixel HiRISE images of Mawrth Vallis were used as input for NOAH-H. These are:

PSP_002140_2025_RED

PSP_002074_2025_RED

ESP_057351_2020_RED

ESP_053909_2025_RED

ESP_053698_2025_RED

ESP_052274_2025_RED

ESP_051931_2025_RED

ESP_051351_2025_RED

ESP_051219_2030_RED

ESP_050217_2025_RED

ESP_046960_2025_RED

ESP_046670_2025_RED

ESP_046525_2025_RED

ESP_046459_2025_RED

ESP_046314_2025_RED

ESP_045536_2025_RED

ESP_045114_2025_RED

ESP_044903_2025_RED

ESP_043782_2025_RED

ESP_043637_2025_RED

ESP_038758_2025_RED

ESP_037795_2025_RED

ESP_037294_2025_RED

ESP_036872_2025_RED

ESP_036582_2025_RED

ESP_035804_2025_RED NOAH-H produced corresponding 25 cm/pixel rasters where each pixel is assigned a terrain class based on the corresponding pixels in the input HiRISE image. To mosaic the NOAH-H rasters together, first the input HiRISE images were georeferenced to the HRSC basemap (HMC_11E10_co5) tile, using CTX images as an intermediate step. High order (spline, in ArcGIS Pro 3.0) transformations were used to make the HiRISE images georeference closely onto the target layers. Once the HiRISE images were georeferenced, the same control points and transformations were applied to the corresponding NOAH-H rasters. To mosaic the georeferenced NOAH-H rasters the pixel values for the classes needed to be changed so that more confidently identified, and more dangerous, classes made it into the mosaic (see dataset manuscript for details. To produce a HiRISE layer which fits the NOAH-H classification, download one of the listed HiRISE images from https://www.uahirise.org/, Select the corresponding control point file from this archive and apply a spline transformation through the GIS georeferencing toolbar. Manually Mapped Aeolian Bedforms: Mawrth_Manual_TARs.zip The manually mapped data was produced by Fawdon, independently of the NOAH-H project, as an assessment of “Aeolian Hazard” at Mawrth Vallis. This was done to inform the ExoMars landing site selection process. This file contains two GIS shape files, containing the manually mapped bedforms for both the entire mapping area, and the HiRISE image ESP_046459_2025_RED where the two datasets were compared on a pixel scale. The full manual map is offset slightly from the NOAH-H, since it was digitised from bespoke HiRISE orthomosaics, rather than from the publicly available HiRISE Red band images. It is suitable for comparison to the NOAH-H data with 100m-1km aggregation as in figure 8 of the associated paper. It is not suitable for pixel scale comparison. The map of ESP_046459_2025_RED was manually georeferenced to the NOAH-H mosaic, allowing for direct pixel to pixel comparisons, as presented in figure 6 of the associated paper. Two GIS shape files are included: · Mawrth_Manual_TARs_ESP_046459_2025.shp · Mawrth_Manual_TARs_all.shp Containing the high fidelity data for ESP_046459_2025, and the medium fidelity data for the entire area respectively. The are accompanied by ancillary files needed to view them in GIS. Gridded Density Statistics This dataset contains gridded density maps of Transverse Aeolian Ridges and Boulders, as classified by the Novelty or Anomaly Hunter – HiRISE (NOAH-H). The area covered is the runner up candidate ExoMars landing site in Mawrth Vallis, Mars. These are the data shown in figures; 7, 8, and S1. Files are presented for every classified ripple and boulder class, as well as for thematic groups. These are presented as .shp GIS shapefiles, along with all auxiliary files required to view them in GIS. Gridded Density stats are available in two zip folders, one for NOAH-H predicted density, and one for manually mapped density. NOAH-H Predicted Density: Mawrth_NOAHH_1km_Grid_TAR_Boulder_Density.zip Individual classes are found in the files: · Mawrth_NOAHH_1km_Grid_8TARs.shp · Mawrth_NOAHH_1km_Grid_9TARs.shp · Mawrth_NOAHH_1km_Grid_11TARs.shp · Mawrth_NOAHH_1km_Grid_12TARs.shp · Mawrth_NOAHH_1km_Grid_13TARs.shp · Mawrth_NOAHH_1km_Grid_Boulders.shp Where the text following Grid denotes the NOAH-H classes represented, and the landform classified. E.g. 8TARs = NOAH-H TAR class 8. The following thematic groups are also included: · Mawrth_NOAHH_1km_Grid_8_11continuousTARs.shp · Mawrth_NOAHH_1km_Grid_12_13discontinuousTARs · Mawrth_NOAHH_1km_Grid_8_10largeTARs.shp · Mawrth_NOAHH_1km_Grid_11_13smallTARs.shp · Mawrth_NOAHH_1km_Grid_8_13AllTARs.shp When the numbers denote the range of NOAH-H classes which were aggregated to produce the map, followed by a description of the thematic group: “continuous”, “discontinuous”, “large”, “small”, “all”. Manually Mapped Density Plots: Mawrth_Manual_1km_Grid.zip These GIS shapefiles have the same format as the NOAH-H classified ones. Three datasets are presented for all TARs (“_allTARs”), Continuous TARs (“_con”) and Discontinuous TARs (“_dis”) · Mawrth_Manual_1km_Grid_AllTARs.shp · Mawrth_Manual_1km_Grid_Con.shp · Mawrth_Manual_1km_Grid_Dis.shp Related public datasets: The HiRISE images discussed in this work are publicly available from https://www.uahirise.org/. and are credited to NASA/JPL/University of Arizona. HRSC images are credited to the European Space Agency; Mars Express mission team, German Aerospace Center (DLR), and the Freie Universität Berlin (FUB). They are available at the ESA Planetary Science Archive (PSA) https://www.cosmos.esa.int/web/psa/mars-express and are used under the Creative Commons CC BY-SA 3.0 IGO licence. SPATIAL DATA COORDINATE SYSTEM INFORMATION All NOAH-H files and derivative density plots have the same projected coordinate system: “Equirectangular Mars” - Projection: Plate Carree - Sphere radius: 3393833.2607584 m SOFTWARE INFORMATION All GIS workflows (georeferencing, mosaicking) were conducted in ArcGIS Pro 3.0. NOAH-H is a deep learning semantic segmentation software developed by SciSys Ltd for the European Space Agency to aid preparation for the ExoMars rover mission.

This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

© MarineCadastre.gov This layer is a component of BOEMRE Layers.

This Map Service contains many of the primary data types created by both the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) within the Department of Interior (DOI) for the purpose of managing offshore federal real estate leases for oil, gas, minerals, renewable energy, sand and gravel. These data layers are being made available as REST mapping services for the purpose of web viewing and map overlay viewing in GIS systems. Due to re-projection issues which occur when converting multiple UTM zone data to a single national or regional projected space, and line type changes that occur when converting from UTM to geographic projections, these data layers should not be used for official or legal purposes. Only the original data found within BOEM/BSEE’s official internal database, federal register notices or official paper or pdf map products may be considered as the official information or mapping products used by BOEM or BSEE. A variety of data layers are represented within this REST service are described further below. These and other cadastre information the BOEM and BSEE produces are generated in accordance with 30 Code of Federal Regulations (CFR) 256.8 to support Federal land ownership and mineral resource management.

For more information – Contact: Branch Chief, Mapping and Boundary Branch, BOEM, 381 Elden Street, Herndon, VA 20170. Telephone (703) 787-1312; Email: mapping.boundary.branch@boem.gov

The REST services for National Level Data can be found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer

REST services for regional level data can be found by clicking on the region of interest from the following URL: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE

Individual Regional Data or in depth metadata for download can be obtained in ESRI Shape file format by clicking on the region of interest from the following URL: http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx

Currently the following layers are available from this REST location:

OCS Drilling Platforms -Locations of structures at and beneath the water surface used for the purpose of exploration and resource extraction. Only platforms in federal Outer Continental Shelf (OCS) waters are included. A database of platforms and rigs is maintained by BSEE.

OCS Oil and Natural Gas Wells -Existing wells drilled for exploration or extraction of oil and/or gas products. Additional information includes the lease number, well name, spud date, the well class, surface area/block number, and statistics on well status summary. Only wells found in federal Outer Continental Shelf (OCS) waters are included. Wells information is updated daily. Additional files are available on well completions and well tests. A database of wells is maintained by BSEE.

OCS Oil & Gas Pipelines -This dataset is a compilation of available oil and gas pipeline data and is maintained by BSEE. Pipelines are used to transport and monitor oil and/or gas from wells within the outer continental shelf (OCS) to resource collection locations. Currently, pipelines managed by BSEE are found in Gulf of Mexico and southern California waters.

Unofficial State Lateral Boundaries - The approximate location of the boundary between two states seaward of the coastline and terminating at the Submerged Lands Act Boundary. Because most State boundary locations have not been officially described beyond the coast, are disputed between states or in some cases the coastal land boundary description is not available, these lines serve as an approximation that was used to determine a starting point for creation of BOEM’s OCS Administrative Boundaries. GIS files are not available for this layer due to its unofficial status.

BOEM OCS Administrative Boundaries - Outer Continental Shelf (OCS) Administrative Boundaries Extending from the Submerged Lands Act Boundary seaward to the Limit of the United States OCS (The U.S. 200 nautical mile Limit, or other marine boundary)For additional details please see the January 3, 2006 Federal Register Notice.

BOEM Limit of OCSLA ‘8(g)’ zone - The Outer Continental Shelf Lands Act '8(g) Zone' lies between the Submerged Lands Act (SLA) boundary line and a line projected 3 nautical miles seaward of the SLA boundary line. Within this zone, oil and gas revenues are shared with the coastal state(s). The official version of the ‘8(g)’ Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction described below.

Submerged Lands Act Boundary - The SLA boundary defines the seaward limit of a state's submerged lands and the landward boundary of federally managed OCS lands. The official version of the SLA Boundaries can only be found on the BOEM Official Protraction Diagrams (OPDs) or Supplemental Official Protraction Diagrams described below.

Atlantic Wildlife Survey Tracklines(2005-2012) - These data depict tracklines of wildlife surveys conducted in the Mid-Atlantic region since 2005. The tracklines are comprised of aerial and shipboard surveys. These data are intended to be used as a working compendium to inform the diverse number of groups that conduct surveys in the Mid-Atlantic region.The tracklines as depicted in this dataset have been derived from source tracklines and transects. The tracklines have been simplified (modified from their original form) due to the large size of the Mid-Atlantic region and the limited ability to map all areas simultaneously.The tracklines are to be used as a general reference and should not be considered definitive or authoritative. This data can be downloaded from http://www.boem.gov/uploadedFiles/BOEM/Renewable_Energy_Program/Mapping_and_Data/ATL_WILDLIFE_SURVEYS.zip

BOEM OCS Protraction Diagrams & Leasing Maps - This data set contains a national scale spatial footprint of the outer boundaries of the Bureau of Ocean Energy Management’s (BOEM’s) Official Protraction Diagrams (OPDs) and Leasing Maps (LMs). It is updated as needed. OPDs and LMs are mapping products produced and used by the BOEM to delimit areas available for potential offshore mineral leases, determine the State/Federal offshore boundaries, and determine the limits of revenue sharing and other boundaries to be considered for leasing offshore waters. This dataset shows only the outline of the maps that are available from BOEM.Only the most recently published paper or pdf versions of the OPDs or LMs should be used for official or legal purposes. The pdf maps can be found by going to the following link and selecting the appropriate region of interest. http://www.boem.gov/Oil-and-Gas-Energy-Program/Mapping-and-Data/Index.aspx Both OPDs and LMs are further subdivided into individual Outer Continental Shelf(OCS) blocks which are available as a separate layer. Some OCS blocks that also contain other boundary information are known as Supplemental Official Block Diagrams (SOBDs.) Further information on the historic development of OPD's can be found in OCS Report MMS 99-0006: Boundary Development on the Outer Continental Shelf: http://www.boemre.gov/itd/pubs/1999/99-0006.PDF Also see the metadata for each of the individual GIS data layers available for download. The Official Protraction Diagrams (OPDs) and Supplemental Official Block Diagrams (SOBDs), serve as the legal definition for BOEM offshore boundary coordinates and area descriptions.

BOEM OCS Lease Blocks - Outer Continental Shelf (OCS) lease blocks serve as the legal definition for BOEM offshore boundary coordinates used to define small geographic areas within an Official Protraction Diagram (OPD) for leasing and administrative purposes. OCS blocks relate back to individual Official Protraction Diagrams and are not uniquely numbered. Only the most recently published paper or pdf

This layer traces apparent topographic and air-photo lineaments in the area around Pagosa springs in Archuleta County, Colorado. It was made in order to identify possible fault and fracture systems that might be conduits for geothermal fluids. Geothermal fluids commonly utilize fault and fractures in competent rocks as conduits for fluid flow. Geothermal exploration involves finding areas of high near-surface temperature gradients, along with a suitable plumbing system that can provide the necessary permeability. Geothermal power plants can sometimes be built where temperature and flow rates are high.

To do this, georeferenced topographic maps and aerial photographs were utilized in an existing GIS, using ESRI ArcMap 10.0 software. The USA_Topo_Maps and World_Imagery map layers were chosen from the GIS Server at server.arcgisonline.com, using a UTM Zone 13 NAD27 projection. This line shapefile was then constructed over that which appeared to be through-going structural lineaments in both the aerial photographs and topographic layers, taking care to avoid manmade features such as roads, fence lines, and right-of-ways. These lineaments may be displaced somewhat from their actual location, due to such factors as shadow effects with low sun angles in the aerial photographs.

Note: This shape file was constructed as an aid to geothermal exploration in preparation for a site visit for field checking. We make no claims as to the existence of the lineaments, their location, orientation, and nature.

Abstract

This is a source dataset created by the Bioregional Assessment Programme without the use of source data.

This dataset contains all of the surface water footprint polygons that were created from mining reports that were used in the surface water modelling. There is also a document with the source references for all of the footprints included in the dataset.

Dataset History

Environmental impact statements and similar documents were downloaded from New South Wales Department of Planning and Environment Major Projects website, and from mining companies' websites. To obtain mine footprints for surface water modelling, the mining reports were searched for past and future projected mine layouts and surface water contributing areas. Each figure was digitised and georeferenced using one of four methods:

1. The preferred method was to use maps or plans with coordinates already on them.

2. If there were no coordinates, then three point locations were matched with points on Google Earth and the latitude and longitude from Google Earth were used to georeference the image.

3. If there were not three clearly identifiable point locations in the image, then supplementary points were found by matching contour information to the Shuttle Radar Topography Mission Smoothed Digital Elevation Model (SRTM DEM-S) grid

Dataset GUID - 12e0731d-96dd-49cc-aa21-ebfd65a3f67a

1. Other site-specific approaches: a. Mangoola Coal Mine did not have adequate georeferencing points in the Year 10 and Final Landform images so these images were georeferenced to the matching project boundary in the other Mangoola Coal Mine images.

b. The West Wallsend Colliery existing pit top surface facilities image, containing a satellite photo background, was georeferenced using Google Earth. The West Wallsend Colliery pit top facility outline was used to georeference the water management system image as they both contained the same outline.

These areas were exported as polygon files (\*.poly) using Geosoft Oasis Montaj software.

A list of documents used for creating these polygon files are also included in the dataset

Dataset Citation

Bioregional Assessment Programme (2016) HUN SW footprint shapefiles v01. Bioregional Assessment Source Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/2a9520c8-1569-4e0e-8bd8-26e2c7b9e9e0.