This product set contains reduced-resolution Interferometric Synthetic Aperture Radar (IFSAR) imagery and geospatial data for the Barrow Peninsula (155.39 - 157.48 deg W, 70.86 - 71.47 deg N), for use in Geographic Information Systems (GIS) and remote sensing software. The primary IFSAR data sets were acquired by Intermap Technologies from 27 to 29 July 2002, and consist of an Orthorectified Radar Imagery (ORRI), a Digital Surface Model (DSM), and a Digital Terrain Model (DTM). Derived data layers include aspect, shaded relief, and slope-angle grids (floating-point binary format), as well as a vector layer of contour lines (ESRI Shapefile format). Also available are accessory layers compiled from other sources: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow Peninsula (ESRI Shapefile format). The DSM and DTM data sets (20 m resolution) are provided in floating-point binary format with header and projection files. The ORRI mosaic (5 m resolution) is available in GeoTIFF format. FGDC-compliant metadata for all data sets are provided in text, HTML, and XML formats, along with the Intermap License Agreement and product handbook. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are available via FTP and CD-ROM.

Zoom in on the map above and click your area of interest or use the Tile Index linked below to determine which package(s) you require for download. Note that the products from the SWOOP 2010 project are not currently packaged for download. To order data from this project see LIO Support – Large Data Ordering Instructions. Data sizes are listed below.

The Digital Surface Models (DSM) are raster elevation products that were generated from the elevation point clouds created via pixel-correlation from aerial photography. A DSM is the highest reflective surface of ground features captured by the sensor. This surface may also be referred to as the first reflective surface. The DSM may include treetops, rooftops, and tops of towers, telephone poles, and other natural or artificial features; or it may include the ground surface if there is no vegetative ground cover.

For more detailed information about this dataset, refer to the associated User Guide.

Now also available through a web service which exposes the data for visualization, geoprocessing and limited download. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection.

For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca.

Service Endpoints

https://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DSM_ImageryDerived/ImageServer https://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DSM_ImageryDerived/ImageServer (Government of Ontario Internal Users)

Additional Documentation

Ontario DSM (Imagery-Derived) - User Guide (Word)

Ontario DSM (Imagery-Derived) - Tile Index (SHP)

SCOOP 2013 DSM - Vertical Accuracy Assessment (Word) SCOOP 2013 DSM - Vertical Accuracy Assessment - Data (SHP)

Product Packages

SWOOP 2010 - Chatham-Kent - 3.63 GB SWOOP 2010 - Elgin - 4.96 GB SWOOP 2010 - Essex - 5.0 GB SWOOP 2010 - Huron - 7.55 GB SWOOP 2010 - Lambton - 8.92 GB SWOOP 2010 - Middlesex

Data Package Download Links for the Ontario DSM (Imagery-Derived) (Word) SCOOP 2013 DRAPE 2014 SWOOP 2015 SCOOP 2018 DRAPE 2019 SWOOP 2020 COOP 2021 NWOOP 2022

Status On going: Data is continually being updated

Maintenance and Update Frequency As needed: Data is updated as deemed necessary

Contact Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return. Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected in 2011.An ordnance datum (OD) is a vertical datum used as the basis for deriving heights on maps. This data is referenced to the Malin Head Vertical Datum which is the mean sea level of the tide gauge at Malin Head, County Donegal. It was adopted as the national datum in 1970 from readings taken between 1960 and 1969 and all heights on national grid maps are measured above this datum. Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.Digital Surface Models (DSM) are earth models in its current state. For example, a DSM includes elevations from buildings, tree canopy, electrical power lines and other features.Hillshading is a method which gives a 3D appearance to the terrain. It shows the shape of hills and mountains using shading (levels of grey) on a map, by the use of graded shadows that would be cast by high ground if light was shining from a chosen direction.This data shows the hillshade of the DSM.This data was collected by the Office of Public Works. All data formats are provided as GeoTIFF rasters. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. OPW data has a grid cell size of 2 meter by 2 meter. This means that each cell (pixel) represents an area of 2 meter squared.

PLEASE NOTE: This record has been retired. It has been superseded by: https://environment.data.gov.uk/dataset/b5aaa28d-6eb9-460e-8d6f-43caa71fbe0e This dataset is not suitable for identifying whether an individual property will flood. GIS layer showing information about the modelling used at that location. Including whether local outputs were used to replace the national outputs and other parameters, such as the model software used. This dataset is one output of our Risk of Flooding from Surface Water (RoFSW) mapping, previously known as the updated Flood Map for Surface Water (uFMfSW). It is one of a group of datasets previously available as the uFMfSW Complex Package. Further information on using these datasets can be found at the Resource Locator link below. Information Warnings: Risk of Flooding from Surface Water is not to be used at property level. If the Content is displayed in map form to others we recommend it should not be used with basemapping more detailed than 1:10,000 as the data is open to misinterpretation if used as a more detailed scale. Because of the way they have been produced and the fact that they are indicative, the maps are not appropriate to act as the sole evidence for any specific planning or regulatory decision or assessment of risk in relation to flooding at any scale without further supporting studies or evidence. Attribution statement: © Environment Agency copyright and/or database right 2015. All rights reserved.

The High Resolution Digital Elevation Model (HRDEM) product is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The complete coverage of the Canadian territory is gradually being established. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived data. For DTM datasets, derived data available are slope, aspect, shaded relief, color relief and color shaded relief maps and for DSM datasets, derived data available are shaded relief, color relief and color shaded relief maps. The productive forest line is used to separate the northern and the southern parts of the country. This line is approximate and may change based on requirements. In the southern part of the country (south of the productive forest line), DTM and DSM datasets are generated from airborne LiDAR data. They are offered at a 1 m or 2 m resolution and projected to the UTM NAD83 (CSRS) coordinate system and the corresponding zones. The datasets at a 1 m resolution cover an area of 10 km x 10 km while datasets at a 2 m resolution cover an area of 20 km by 20 km. In the northern part of the country (north of the productive forest line), due to the low density of vegetation and infrastructure, only DSM datasets are generally generated. Most of these datasets have optical digital images as their source data. They are generated at a 2 m resolution using the Polar Stereographic North coordinate system referenced to WGS84 horizontal datum or UTM NAD83 (CSRS) coordinate system. Each dataset covers an area of 50 km by 50 km. For some locations in the north, DSM and DTM datasets can also be generated from airborne LiDAR data. In this case, these products will be generated with the same specifications as those generated from airborne LiDAR in the southern part of the country. The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013), which is now the reference standard for heights across Canada. Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The tiles are aligned within each project. The product High Resolution Digital Elevation Model (HRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan. Collaboration is a key factor to the success of the National Elevation Data Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.

a quarter-quadrangle index map for the 26 IFSAR tiles (ESRI Shapefile format)

This layer provides Digital Surface Models developed by the USACE National Coastal Mapping Program (NCMP). The USACE NCMP acquires high-resolution, high-accuracy topographic/bathymetric lidar elevation and imagery on a recurring basis along the sandy shorelines of the US. The program's survey footprint includes an approximately 1-mile wide swath of topography, bathymetry and imagery 500-m onshore and 1000-m offshore. The standard suite of NCMP data products include topographic/bathymetric lidar point clouds, digital surface and elevation models, shoreline vectors and both true-color and hyperspectral imagery mosaics. Value-added derivative information products may include laser reflectance images, landcover classification images and volume change metrics.USACE Headquarters initiated the NCMP in 2004. The program's update cycle follows counter-clockwise along the US West Coast, Gulf Coast, East Coast and Great Lakes approximately every 5 years. Surveys in support of USACE project-specific missions and external partners are included constituent to the current NCMP schedule and reimbursable funding. All work is coordinated with Federal mapping partners through the Interagency Working Group on Ocean and Coastal Mapping (IWGOCM) and the 3D Elevation Program (3DEP).NCMP operations are executed by the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). The JALBTCX mission is to perform operations, research and development in airborne lidar bathymetry and complementary technologies to support the coastal mapping and charting requirements of the US Army Corps of Engineers, the US Naval Meteorology and Oceanography Command and the National Oceanic and Atmospheric Administration. Survey operations are conducted worldwide using the Coastal Zone Mapping and Imaging (CZMIL) system and other industry-based coastal mapping and charting systems. CZMIL is JALBTCX's in-house survey capability that includes and Optech International, CZMIL 03-1 lidar instrument with simultaneous topographic and bathymetric capabilities. CZMIL is integrated with an Itres CASI-1500 hyperspectral imager and an 80MP Leica RCD30 RGBN camera. CZMIL collects 10-kHz lidar data with spatially- and temporally-coincident digital true-color and hyperspectral imagery.

This product set contains reduced-resolution Interferometric Synthetic Aperture Radar (IFSAR) imagery and geospatial data for the Barrow Peninsula (155.39 - 157.48 deg W, 70.86 - 71.47 deg N), for use in Geographic Information Systems (GIS) and remote sensing software. The primary IFSAR data sets were acquired by Intermap Technologies from 27 to 29 July 2002, and consist of an Orthorectified Radar Imagery (ORRI), a Digital Surface Model (DSM), and a Digital Terrain Model (DTM). Derived data layers include aspect, shaded relief, and slope-angle grids (floating-point binary format), as well as a vector layer of contour lines (ESRI Shapefile format). Also available are accessory layers compiled from other sources: 1:250,000- and 1:63,360-scale USGS Digital Raster Graphic (DRG) mosaic images (GeoTIFF format); 1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format); and a simple polygon layer of the extent of the Barrow Peninsula (ESRI Shapefile format). The DSM and DTM data sets (20 m resolution) are provided in floating-point binary format with header and projection files. The ORRI mosaic (5 m resolution) is available in GeoTIFF format. FGDC-compliant metadata for all data sets are provided in text, HTML, and XML formats, along with the Intermap License Agreement and product handbook. The baseline geospatial data support education, outreach, and multi-disciplinary research of environmental change in Barrow, which is an area of focused scientific interest. Data are available via FTP and CD-ROM.

Digital Surface Model (DSM) has three layers. Two layers come from the rasterisation of the building and vegetation classes among all the points of the LiDAR file .las; and the third layer is the hydrography of the Geographical Reference Information. By applying a suitable colour for each layer, the final product is visualised. ECW file format. ETRS89 reference geodetic system (in the Canary Islands REGCAN95, compatible with ETRS89) and EPSG projection: 3857 throughout the national territory

This dataset has been created to meet the needs of the research community of Arizona State University. Apart from purely vizualization purposes (i.e. displaying the data on various maps) it can potentially be used for spatial modeling. The data consist of engineering-quality contours, also known as isolines, created from the NED 10-meter Digital Elevation Model subset to the extent somewhat exceeding Cetral Arizona - Phoenix LTER. Contours ( lines connecting points of equal height above sea level) are drawn at 15 meter intervals with the base set at 145 m of elevation. Contours are an exact interpretation of the grid surface model and may sometimes appear blocky looking, may cross, appear to intersect, or form an unclosed branching line. All these are valid engineering-quality interpretations of the elevation surface that cartographers typically modify (smooth) for aesthetic purposes.

The Digital Elevation Model (DEM) market, encompassing Digital Surface Models (DSM) and Digital Terrain Models (DTM), is experiencing robust growth, driven by increasing demand across diverse sectors. The market, currently valued at $1034.9 million in 2025, is projected to expand significantly over the forecast period (2025-2033). Key application areas like planning and construction, where DEMs are crucial for site analysis, infrastructure development, and 3D modeling, are fueling this expansion. Furthermore, the aviation industry relies heavily on DEMs for air traffic route planning and navigation, ensuring safe and efficient flight operations. Meteorological services utilize DEMs for accurate weather forecasting and modeling, while geological exploration leverages them for subsurface analysis and resource mapping. Technological advancements, including improved sensor technologies (LiDAR, photogrammetry) and the increasing availability of high-resolution satellite imagery, are further contributing to market growth. While data acquisition costs and processing complexities can pose challenges, the overall market outlook remains positive, supported by the continuous demand for precise and detailed elevation data across a broad range of applications. The geographical distribution of the DEM market is widespread, with North America and Europe currently holding significant market share. However, rapid economic development and infrastructure projects in Asia-Pacific regions, particularly China and India, are expected to drive substantial growth in these markets. Government initiatives promoting digital mapping and spatial data infrastructure are also contributing to market expansion globally. Competition in the DEM market is intense, with a mix of established players and emerging technology providers. The market is characterized by ongoing innovation in data acquisition techniques, processing algorithms, and data delivery platforms. Companies are focusing on developing integrated solutions that combine DEM data with other geospatial information, providing comprehensive analysis and visualization tools for end-users. The future of the DEM market is expected to be shaped by advancements in artificial intelligence (AI) and machine learning (ML), enabling automated data processing, improved accuracy, and enhanced analytical capabilities.

This is a collection of Digital Surface Models and Highest Hit rasters covering selected U.S. Forest Service and adjoining lands in the Southwest Region, encompassing Arizona and New Mexico. The data are presented in a time-enabled format, allowing the end-user to view available data year-by-year, or all available years at once, within a GIS system. The data encompass varying years, varying resolutions, and varying geographic extents, dependent upon available data as provided by the region. DSM and Highest Hit rasters represent elevation of Earth's surface, including its natural and human-made features, such as vegetation and buildings.The data contains an attribute table. Notable attributes that may be of interest to an end-user are:lowps: the pixel size of the source raster, given in meters.highps: the pixel size of the top-most pyramid for the raster, given in meters.beginyear: the first year of data acquisition for an individual dataset.endyear: the final year of data acquisition for an individual dataset.dataset_name: the name of the individual dataset within the collection.metadata: A URL link to a file on IIPP's Portal containing metadata pertaining to an individual dataset within the image service.resolution: The pixel size of the source raster, given in meters.Terrain-related imagery are primarily derived from Lidar, stereoscopic aerial imagery, or Interferometric Synthetic Aperture Radar datasets. Consequently, these derivatives inherit the limitations and uncertainties of the parent sensor and platform and the processing techniques used to produce the imagery. The terrain images are orthographic; they have been georeferenced and displacement due to sensor orientation and topography have been removed, producing data that combines the characteristics of an image with the geometric qualities of a map. The orthographic images show ground features in their proper positions, without the distortion characteristic of unrectified aerial or satellite imagery. Digital orthoimages produced and used within the Forest Service are developed from imagery acquired through various national and regional image acquisition programs. The resulting orthoimages can be directly applied in remote sensing, GIS and mapping applications. They serve a variety of purposes, from interim maps to references for Earth science investigations and analysis. Because of the orthographic property, an orthoimage can be used like a map for measurement of distances, angles, and areas with scale being constant everywhere. Also, they can be used as map layers in GIS or other computer-based manipulation, overlaying, and analysis. An orthoimage differs from a map in a manner of depiction of detail; on a map only selected detail is shown by conventional symbols whereas on an orthoimage all details appear just as in original aerial or satellite imagery.Tribal lands have been masked from this public service in accordance with Tribal agreements.

1:250,000- and 1:63,360-scale USGS quadrangle index maps (ESRI Shapefile format)

The LIDAR Composite DSM (Digital Surface Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The DSM (Digital Surface Model) is produced from the last or only laser pulse returned to the sensor and includes heights of objects, such as vehicles, buildings and vegetation, as well as the terrain surface

Produced by the Environment Agency in 2022, the DSM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalogue which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

This data release provides a series of five bathymetric digital elevation models (DEMs) of Suisun Bay, CA generated from single-beam hydrographic surveys collected from 1866 to 1990. The DEMs were constructed based upon historical United States Coast and Geodetic Survey and National Ocean Service (NOS) surveys collected in 1866, 1886, 1923, 1941, and 1990. Depth soundings from the pre-1930s surveys were manually digitized and georeferenced while the later surveys were obtained in digital format, and all information compiled into a geographic information system (GIS). Using surface modeling software, the soundings from each survey were supplemented with hand-drawn contours and shorelines obtained from topographic sheets to generate bathymetric DEMs at a horizontal resolution of 25 m. The bathymetric DEMs are provided in GeoTIFF format, vertically referenced to the Mean Lower Low Water (MLLW) tidal epoch referenced at the time of data collection.

This layer is a high-resolution tree canopy change-detection layer for Baltimore City, MD. It contains three tree-canopy classes for the period 2007-2015: (1) No Change; (2) Gain; and (3) Loss. It was created by extracting tree canopy from existing high-resolution land-cover maps for 2007 and 2015 and then comparing the mapped trees directly. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed by development, storms, or disease were assigned to the Loss class. Trees planted during the interval were assigned to the Gain category, as were the edges of existing trees that expanded noticeably. Direct comparison was possible because both the 2007 and 2015 maps were created using object-based image analysis (OBIA) and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs). OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset will be subjected to manual review and correction. 2006 LiDAR and 2014 LiDAR data was also used to assist in tree canopy change.

LiDAR (Light Detection and Ranging) is a remote sensing technology, i.e. the technology is not in direct contact with what is being measured. From satellite, aeroplane or helicopter, a LiDAR system sends a light pulse to the ground. This pulse hits the ground and returns back to a sensor on the system. The time is recorded to measure how long it takes for this light to return. Knowing this time measurement scientists are able to create topography maps.LiDAR data are collected as points (X,Y,Z (x & y coordinates) and z (height)). The data is then converted into gridded (GeoTIFF) data to create a Digital Terrain Model and Digital Surface Model of the earth. This LiDAR data was collected between June and October 2018.An ordnance datum (OD) is a vertical datum used as the basis for deriving heights on maps. This data is referenced to the Malin Head Vertical Datum which is the mean sea level of the tide gauge at Malin Head, County Donegal. It was adopted as the national datum in 1970 from readings taken between 1960 and 1969 and all heights on national grid maps are measured above this datum. Digital Terrain Models (DTM) are bare earth models (no trees or buildings) of the Earth’s surface.Digital Surface Models (DSM) are earth models in its current state. For example, a DSM includes elevations from buildings, tree canopy, electrical power lines and other features.Hillshading is a method which gives a 3D appearance to the terrain. It shows the shape of hills and mountains using shading (levels of grey) on a map, by the use of graded shadows that would be cast by high ground if light was shining from a chosen direction.This data shows the hillshade of the DTM.This data was collected by BlueSky and GeoAeroSpace and provided to the Geological Survey Ireland. All data formats are provided as GeoTIFF rasters but are at different resolutions. Data resolution is 1m.Both a DTM and DSM are raster data. Raster data is another name for gridded data. Raster data stores information in pixels (grid cells). Each raster grid makes up a matrix of cells (or pixels) organised into rows and columns. This data has a grid cell size of 1 meter by 1 meter. This means that each cell (pixel) represents an area of 1 meter squared.

File List bathymetry_30s.7z (MD5: dd855211bbcdee7d6862414da23d6da2) biogeo01_07_30s.7z (MD5: 396525db0abd9de2ede3d8fdeb15e8ee) biogeo08_17_30s.7z (MD5: 96c2417eed84e85f9896536b934c53e1) Monthly_Variables_30s.7z (MD5: 89016a8d17e8d8a1dddef0a121a83f5d)

     Additional high resolution raster files:

Sea_Ice_30s.7z (MD5: 547d355294c530f63b9b0a73dedd2f3a)

     Low resolution MARSPEC data files:

MARSPEC_2o5m.7z (MD5: 923c97d185adb0c72f158a84e2981391) MARSPEC_5m.7z (MD5: 95f7c3739c4f2889c2eff18afeffa489) MARSPEC_10m.7z (MD5: d91f3127f46f7004d116f14328bf4b71) Description Ecological niche models are widely used in terrestrial studies to address critical ecological and evolutionary questions related to past and future climate change, local adaptation and speciation, the discovery of rare endemics, and biological invasions. However the application of niche models to similar questions in marine ecosystems has lagged behind, in part due to the lack of a centralized high-resolution spatial data set representing both benthic and pelagic marine environments. Here we describe the creation of MARSPEC, a high-resolution GIS database of ocean climate layers intended for marine ecological niche modeling and other applications in marine spatial ecology. MARSPEC combines information related to topographic complexity of the seafloor with bioclimatic measures of sea surface temperature and salinity for the world ocean. We derived seven geophysical variables from a high-resolution raster grid representing depth of the seafloor (bathymetry) to characterize six facets of topographic complexity (east-west and north-south components of aspect, slope, concavity of the seafloor, and plan and profile curvature) and distance from shore. We further derived 10 bioclimatic variables describing the annual mean, range, variance and extreme values for temperature and salinity from long-term monthly climatological means obtained from remotely sensed and in situ oceanographic observations. All variables were clipped to a common land mask, interpolated to a nominal 1-km (30 arc-second) grid, and converted to an ESRI raster grid file format compatible with popular GIS programs. MARSPEC is a 10-fold improvement in spatial resolution over the next-best data set (Bio-ORACLE) and is the only high-resolution global marine data set to combine variables from the benthic and pelagic environments into a single database. Additionally, we provide the monthly climatological layers used to derive the bioclimatic variables, allowing users to calculate equivalent MARSPEC variables from anomaly data for past and future climate scenarios. A detailed description of GIS processing steps required to calculate the MARSPEC variables can be found in the metadata.

      Key words: climate change; ecological niche modeling; GIS; marine spatial ecology; ocean climate; salinity; sea surface temperature; species distribution modeling.

Note: Geoscience Australia no longer supports users' external hard drives. The data can either be downloaded from the ELVIS Portal or from the Related links. The 1 second Shuttle Radar Topography Mission (SRTM) Digital Elevation Models Version 1.0 package comprises three surface models: the Digital Elevation Model (DEM), the Smoothed Digital Elevation Model (DEM-S) and the Hydrologically Enforced Digital Elevation Model (DEM-H). The DEMs were derived from the SRTM data acquired by NASA in February 2000 and were publicly released under Creative Commons licensing from November 2011 in ESRI Grid format.

DEM represents ground surface topography, with vegetation features removed using an automatic process supported by several vegetation maps. This provides substantial improvements in the quality and consistency of the data relative to the original SRTM data, but is not free from artefacts. Man-made structures such as urban areas and power line towers have not been treated. The removal of vegetation effects has produced satisfactory results over most of the continent and areas with defects identified in supplementary layers distributed with the data, and described in the User Guide.

DEM-S represents ground surface topography, excluding vegetation features, and has been smoothed to reduce noise and improve the representation of surface shape. An adaptive smoothing process applied more smoothing in flatter areas than hilly areas, and more smoothing in noisier areas than in less noisy areas. This DEM-S supports calculation of local terrain shape attributes such as slope, aspect and curvature that could not be reliably derived from the unsmoothed 1 second DEM because of noise.

DEM-H is a hydrologically enforced version of the smoothed DEM-S. The DEM-H captures flow paths based on SRTM elevations and mapped stream lines, and supports delineation of catchments and related hydrological attributes. The dataset was derived from the 1 second smoothed Digital Elevation Model (DEM-S) by enforcing hydrological connectivity with the ANUDEM software, using selected AusHydro V1.6 (February 2010) 1:250,000 scale watercourse lines and lines derived from DEM-S to define the watercourses. The drainage enforcement has produced a consistent representation of hydrological connectivity with some elevation artefacts resulting from the drainage enforcement.

Further information can be found in the supplementary layers supplied with the data and in the User Guide.

This data release provides a series of six bathymetric digital elevation models (DEMs) of San Pablo Bay, CA generated from single-beam hydrographic surveys collected from 1856 to 1983. The DEMs were constructed based upon historical United States Coast and Geodetic Survey and National Ocean Service (NOS) surveys collected in 1856, 1887, 1898, 1922, 1951, and 1983. Depth soundings from the pre-1930s surveys were manually digitized and georeferenced while the later surveys were obtained in digital format, and all information compiled into a geographic information system (GIS). Using surface modeling software, the soundings from each survey were supplemented with hand-drawn contours and shorelines obtained from topographic sheets to generate bathymetric DEMs at a horizontal resolution of 25 m. The bathymetric DEMs are provided in GeoTIFF format, vertically referenced to the Mean Lower Low Water (MLLW) tidal epoch referenced at the time of data collection.