Dataset Summary: This datasheet describes three 2-foot resolution rasters that cover the extent of Santa Cruz County – slope percent, slope degrees, and aspect. These rasters are derived directly from the 2-foot resolution Santa Cruz County Digital Terrain Models (DTMs), which were derived from 2020 QL1 lidar. These rasters represent the state of the landscape when countywide lidar data was collected in 2020. QL1 lidar was collected in western Santa Cruz County by Quantum Spatial and in eastern Santa Cruz County by the Sanborn Map Company. Figure 1 shows the respective areas of lidar collection. This deliverable is a combination of these two lidar datasets. The horizontal coordinate system of these rasters, State Plane CA Zone III (WKID 6420), is the native horizontal resolution of the 2020 point clouds. Figure 1. Sources of lidar data for Santa Cruz County

Table 1 provides links to download these lidar derived rasters.
These three lidar derivatives provide information about the surface of the earth. The two slope rasters depict the steepness of the ground for each 2-foot x 2-foot cell of the raster surface. One of the slope rasters represents slope in degrees, the other in percent. Aspect (or ‘slope direction’) shows the downslope direction of the maximum rate of change in elevation value from each cell to its neighbors.
The two slope and 1 aspect rasters were derived from the Santa Cruz County Digital Terrain Model using the ‘slope’ and ‘aspect’ functions in ArcGIS Pro Spatial Analyst. Table 1. lidar derivatives for Santa Cruz County

Dataset

Description

Link to Datasheet

Link to Data

Slope (Percent)

Steepness of the ground in percent for each 2-foot x 2-foot raster cell. Units in percent.

https://vegmap.press/scz_slope_and_aspect_datasheet

https://vegmap.press/scz_slope_percent

Slope (Degrees)

Steepness of the ground in degrees for each 2-foot x 2-foot raster cell. Units in degrees.

https://vegmap.press/scz_slope_and_aspect_datasheet

https://vegmap.press/scz_slope_degrees

Aspect

Aspect (or ‘slope direction’) shows the downslope direction of the maximum rate of change in elevation value from each cell to its neighbors.

https://vegmap.press/scz_slope_and_aspect_datasheet

https://vegmap.press/scz_aspect

Related Datasets: Other related lidar derived topography derivatives are available for Santa Cruz County. The following is a list of those rasters, with links to their datasheets: HillshadeDigital Terrain Model (western areas of the county)Digital Terrain Model (eastern areas of the county)5-meter resolution slope and aspect

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.

This dataset has been deprecated. Please use our 2017 Digital Elevation Models instead. The Digital Surface Model (DSM) is a 3-foot pixel resolution raster in GeoTIFF format. This was created using all points (excluding NOISE) from our 2007 LiDAR data without incorporating the breaklines. Merrick and Co. MARS (ver. 8.0.4, build 8185) software was used to create the GeoTIFF images. The DSMs were developed using LiDAR data. LiDAR is an acronym for LIght Detection And Ranging. Light detection and ranging is the science of using a laser to measure distances to specific points. A specially equipped airplane with positioning tools and LiDAR technology was used to measure the distance to the surface of the earth. The classified points were developed using data collected in April to May 2007. The LiDAR points, specialized software, and technology provide the ability to create a high precision three-dimensional digital elevation and/or terrain models (DEM/DTM) as well as digital surface models (DSM). The use of LiDAR significantly reduces the cost for developing this information. The DSMs are intended to correspond to the orthometric heights of the surface of the county including above ground features such as buildings, vegetation cover, utility structures, vehicles ... etc. DSM data are used by county agencies and others to study drainage issues such as flooding and erosion; contour generation; slope and aspect; and hill shade images. Elevation data and models are used in several different ways including: Visualization representations of the elevation data. Examples include: - A hillshaded or shaded relief image - An image representing slope - An image representing aspect Analysis of the elevation data and analytical products which can be generated. Examples include: - Viewshed calculations for visibility and line-of-sight analysis - Areas of highest Solar energy potential - Uses in disaster management - Industrial planning - Calculation of cartographic contours - Calculation of profiles along straight lines or line segments These data are derived from other data sources, no accuracy measurements or tests were conducted. Primary use and intent for these data are for visualizations and topographic analysis. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

In addition to this statewide 3DEP hydro-flattened base-earth DEM, the IGIO has also published this data as an Esri Imagery Service, allowing users to conveniently visualize the DEM data by applying visual enhancements to create dynamic hillshade, shaded relief, slope, and aspect-ratio raster maps.This image service has a series of image processing templates (or raster functions) integrated and ready to use out of the box. By default, the DEM is symbolized as a shaded relief - a hillshade with an elevation color ramp applied on top of it. If users would like to view the data differently in ArcGIS Online or desktop applications, they can select from one of the other raster functions. These raster functions include the bare-earth DEM, grayscale hillshade, slope (RGB), slope (degrees), aspect (RGB), and aspect (numeric values).

Download In State Plane Projection Here The 2017 Digital Terrain Model (DTM) is a 2 foot pixel resolution raster in Erdas IMG format. This was created using the ground (class = 2) lidar points and incorporating the breaklines. The DTMs were developed using LiDAR data. LiDAR is an acronym for LIght Detection And Ranging. Light detection and ranging is the science of using a laser to measure distances to specific points. A specially equipped airplane with positioning tools and LiDAR technology was used to measure the distance to the surface of the earth to determine ground elevation. The classified points were developed using data collected in April to May 2017. The LiDAR points, specialized software, and technology provide the ability to create a high precision three-dimensional digital elevation and/or terrain models (DEM/DTM). The use of LiDAR significantly reduces the cost for developing this information. The DTMs are intended to correspond to the orthometric heights of the bare surface of the county (no buildings or vegetation cover). DTM data is used by county agencies to study drainage issues such as flooding and erosion; contour generation; slope and aspect; and hill shade images. This dataset was compiled to meet the American Society for Photogrammetry and Remote Sensing (ASPRS) Accuracy Standards for Large-Scale Maps, CLASS 1 map accuracy. The U.S. Army Corps of Engineers Engineering and Design Manual for Photogrammetric Production recommends that data intended for this usage scale be used for any of the following purposes: route location, preliminary alignment and design, preliminary project planning, hydraulic sections, rough earthwork estimates, or high-gradient terrain / low unit cost earthwork excavation estimates. The manual does not recommend that these data be used for final design, excavation and grading plans, earthwork computations for bid estimates or contract measurement and payment. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

The Lidar DEM service has been published with several Raster Function Templates to allow users to view Hillshade, Slope, Aspect, Shaded Relief, and Spectrum rendering. The Lidar data are available in Web Mercator and State Plane projections. Refer to the appropriate section below for instructions to access and apply the templates in your maps.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This layer is a hydro-flattened bare earth digital elevation model (DEM) derived from the classified Lidar point cloud covering the state of Connecticut.

The land base of the Pacific Northwest includes large areas that could support hardwoods or a hardwood component. Often, however, site index, the most commonly used measure of a site's potential productivity, is not available for red alder as other species occupy the site. In order to make site-specific management decisions, the suitability for red alder production can be assessed by geographic and topographic position, soil moisture and aeration during the growing season, and soil fertility and physical condition (Harrington 1986). The difficulty of weighing these physical factors to determine site suitability appears to be a major impediment to the establishment of red alder plantations. Additionally, forest managers are lacking a planning tool that would consider red alder in the landscape for long term management plans. To assist forest managers in their planning and site selection efforts, we developed a GIS-based Red Alder Site Suitability Model based on physical criteria identified by Harrington (1986) as most influential on the productivity of red alder. The major components of the model are elevation, topographic position, slope, aspect, soil type, and soil depth. The model was implemented in a GIS (ESRI ArcPro v.3.0) raster environment with topographic position, slope, aspect, and elevation derived from a 10-meter digital elevation model (DEM), using lidar data where available. Topographic position class of valley, lower slope, flat slope, middle slope, upper slope, or ridgetop was derived from the topographic position index (TPI) using standard deviation thresholds as described by Weiss (2001). The soil texture and depth were derived from Washington DNR’s corporate soil data layer. Each pixel was then classified and assigned one of four suitability categories: High, Medium, Low, and No Potential. Because of the level of spatial detail of the model, forest managers can assess the potential of red alder management on any given site, such as planned timber harvest. Additionally, the model can be used at a larger scale, i.e. planning for future product diversification in a watershed.The model has been cursorily field-verified on existing red alder plantations and compared with locations and site index of natural red alder stands for DNR's forest inventory system. Initial results indicate that the model is accurate in identifying sites with potential for intensive red alder management. Local knowledge will still be an important factor in the application of the model. Frost pockets or areas susceptible to other physical damage such as ice damage (i.e. within the east wind drafts of the Columbia River Gorge) are not identified in by this model. The usefulness of this model will be determined by the experience of the field staff over time. References:Harrington, Constance A. 1986. A method of site quality evaluation for red alder. Gen. Tech. Rep. PNW-GTR-192. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 22 p. https://doi.org/10.2737/PNW-GTR-192Weiss, A. 2001. Topographic position and landforms analysis. In Poster presentation, ESRI user conference, San Diego, CA (Vol. 200). http://www.jennessent.com/downloads/tpi-poster-tnc_18x22.pdf

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This layer is a hydro-flattened bare earth digital elevation model (DEM) derived from the classified Lidar point cloud covering the state of Connecticut.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This dataset covers 116 square miles of Connecticut's coast. Raster functions can be applied using the link below.Dataset InformationExtent: Coastal Connecticut, 116 sq milesDates: 2012 (November 11 - December 16), leaf offData Info: Digital Elevation Model (DEM), which is a bare earth elevation raster, with no functions applied. Functions can be applied to service include aspect, hillshade, shaded relief, and slope. Pixel Resolution: 1 meter DEM raster derived from Lidar point cloud Projection: Geographic, NAD83 meters, NAVD88 metersService Projection: WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857)More Information- Raster Functions- More Information- MetadataCredit and FundingNOAA Office for Coastal Management, US Army Corps of Engineers. Fugro Earthdata, Inc. collected the data.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This dataset covers 1772 square miles of eastern Connecticut. Raster functions can be applied using the link below.Dataset InformationExtent: Eastern Connecticut, 1772 sq milesDates: 2010 (November 3 - December 11), leaf offData Info: Digital Elevation Model (DEM), which is a bare earth elevation raster, with no functions applied. Functions can be applied to service include aspect, hillshade, shaded relief, and slope. Pixel Resolution: 1 meter DEM raster derived from Lidar point cloud Projection: UTM Zone 18N, NAD83 meters, NAVD88 metersService Projection: WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857)More Information- Raster Functions- More Information- MetadataCredit and FundingUSDA Natural Resource Conservation Service (NRCS). Dewberry and Earth Eye LLC collected the data.

2010 Boulder Creek, Colorado Snow-Off LiDAR Surveys

LiDAR was acquired for a 600 km² area inside the Boulder Creek watershed during a snow-off (August, 2010) time slice, near Boulder Colorado. This data was collected in collaboration between the National Center for Airborne Laser Mapping (NCALM) project and the Boulder Creek Critical Zone Observatory (CZO), both funded by the National Science Foundation (NSF). The dataset contains 1 m Digital Surface Models (first-stop), Digital Terrain Models (bare-earth), and 10 points/m² LAS-formated point cloud tiles. The DSMs and DTMs are available in GeoTIFF format, approx. 1-2 GB each, with associated shaded relief models, for a total of 15 GB of data. The Digital Terrain Model (DTM) is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. Accessory layers consist of index map layers for point cloud tiles, DEM extent, and flight lines. Other LiDAR DSMs, DTMs, and point cloud data available in this series include snow-on data for 2010. Together, the LiDAR Digital Elevation Models (DEM) and point cloud data will be of interest to land managers, scientists, and others for study of topography, snow, ecosystems and environmental change. The Boulder Creek CZO will be using the LiDAR data to further their mission of focusing on how water, atmosphere, ecosystems, & soils interact and shape the Earth's surface. The "Critical Zone" lies between rock and sky. It is essential to life - including human food production - and helps drive Earth's carbon cycle, climate change, stream runoff, and water quality.

PLEASE READ the FGDC-compliant metadata files that are available for each dataset (in .html, .txt, and .xml formats). These files provide numerous details that may be of interest. Also included are flight lines, survey reports, reference materials, and DEM extent shapefiles.

Publications associated with this dataset can be found at NCALM's Data Tracking Center

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This dataset covers 455 square miles of southwestern Connecticut. Raster functions can be applied using the link below.Dataset InformationExtent: Southwestern Connecticut, 455 sq miles Date: 2011Data Info: Digital Elevation Model (DEM), which is a bare earth elevation raster, with no functions applied. Functions can be applied to service include aspect, hillshade, shaded relief, and slope. Pixel Resolution: 2 meter DEM raster derived from Lidar point cloud Projection: UTM Zone 18, NAD83 meters, NAVD88 metersService Projection: WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857)More Information- Raster Functions- More Information- MetadataCredit and FundingThis dataset was collected as part of the New England Lidar program with credit to the United States Geological Survey (USGS) and State of Maine's GIS Office. Photo Science Inc. collected the data.

The Solar Radiation Potential Model (SRPM) was derived from the Lake County 2007 Digital Surface Model (DSM). The DSM is a 3-foot pixel resolution raster in GeoTIFF format, created using all points (excluding NOISE) from our 2007 LiDAR data without incorporating the breaklines. The SRPM was created using the ArcGIS 'Area Solar Radiation' geoprocessing tool. Due to the number of variables and parameters, the default values of the geoprocessing tool were used.The solar radiation analysis tools in the ArcGIS Spatial Analyst extension enables one to map and analyze the effects of the sun over a geographic area for specific time periods. It accounts for atmospheric effects, site latitude and elevation, steepness (slope) and compass direction (aspect), daily and seasonal shifts of the sun angle, and effects of shadows cast by surrounding topography. The resultant outputs can be easily integrated with other GIS data and can help model physical and biological processes as they are affected by the sun.These data are derived from other data sources, no accuracy measurements or tests were conducted. Primary use and intent for these data are for visualizations and topographic analysis. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This dataset covers 658 square miles of northwestern Connecticut. Raster functions can be applied using the link below.

Eighteen high-resolution ecological descriptors of vegetation and terrain for Denmark "EcoDes-DK15"

The data are derived from the nationwide airborne laser scanning / LiDAR campaign of Denmark from 2014-2015 provided by the Danish Agency for Data Supply and Efficiency.

Detailed documentation for the data set can be found in the accompanying manuscript and GitHub repository:

Assmann, J. J., Moeslund, J. E., Treier, U. A., and Normand, S.: EcoDes-DK15: High-resolution ecological descriptors of vegetation and terrain derived from Denmark's national airborne laser scanning data set, Earth Syst. Sci. Data Discuss. [preprint], https://doi.org/10.5194/essd-2021-222, in review, 2021.

https://github.com/jakobjassmann/ecodes-dk-lidar

Files are compressed using bzip2 and tar archiving. The compressed archives can be extracted using commonly available archiving tools (for example 7z on Windows, the archiving tool on macOS and bz2 on Linux).

A small example "teaser" subset (5 MB) of the data set, covering the Husby Klit area from Figure 6 in the manuscript, can be found here.

Abstract (from manuscript)

Biodiversity studies could strongly benefit from three-dimensional data on ecosystem structure derived from contemporary remote sensing technologies, such as Light Detection and Ranging (LiDAR). Despite the increasing availability of such data at regional and national scales, the average ecologist has been limited in accessing them due to high requirements on computing power and remote-sensing knowledge. We processed Denmark’s publicly available national Airborne Laser Scanning (ALS) data set acquired in 2014/15 together with the accompanying elevation model to compute 70 rasterized descriptors of interest for ecological studies. With a grain size of 10 m, these data products provide a snapshot of high-resolution measures including vegetation height, structure and density, as well as topographic descriptors including elevation, aspect, slope and wetness across more than forty thousand square kilometres covering almost all of Denmark’s terrestrial surface. The resulting data set is comparatively small (~87 GB, compressed 16.4 GB) and the raster data can be readily integrated into analytical workflows in software familiar to many ecologists (GIS software, R, Python). Source code and documentation for the processing workflow are openly available via a code repository, allowing for transfer to other ALS data sets, as well as modification or re-calculation of future instances of Denmark’s national ALS data set. We hope that our high-resolution ecological vegetation and terrain descriptors (EcoDes-DK15) will serve as an inspiration for the publication of further such data sets covering other countries and regions and that our rasterized data set will provide a baseline of the ecosystem structure for current and future studies of biodiversity, within Denmark and beyond.

Acknowledgements (from manuscript)

We would like to thank Andràs Zlinszky for his contributions to earlier versions of the data set and Charles Davison for feedback regarding data use and handling. Funding for this work was provided by the Carlsberg Foundation (Distinguished Associate Professor Fellowships) and Aarhus University Research Foundation (AUFF-E-2015-FLS-8-73) to Signe Normand (SN). This work is a contribution to SustainScapes – Center for Sustainable Landscapes under Global Change (grant NNF20OC0059595 to SN).

Data were collected in collaboration between the National Center for Airborne Laser Mapping (NCALM) project and the Boulder Creek Critical Zone Observatory (CZO), both funded by the National Science Foundation (NSF). The dataset contains 1 m Digital Surface Models (first-stop), Digital Terrain Models (bare-earth), and 10 points/m² LAS-formated point cloud tiles. The DSMs and DTMs are available in GeoTIFF format with associated shaded relief models. The Digital Terrain Model (DTM) is a ground-surface elevation dataset better suited for derived layers such as slope angle, aspect, and contours. Accessory layers consist of index map layers for point cloud tiles, DEM extent, and flight lines. Other LiDAR DSMs, DTMs, and point cloud data available in this series include snow-off data for 2010. Together, the LiDAR Digital Elevation Models (DEM) and point cloud data will be of interest to land managers, scientists, and others for study of topography, snow, ecosystems and environmental change. The Boulder Creek CZO will be using the LiDAR data to further their mission of focusing on how water, atmosphere, ecosystems, & soils interact and shape the Earth's surface. The "Critical Zone" lies between rock and sky. It is essential to life - including human food production - and helps drive Earth's carbon cycle, climate change, stream runoff, and water quality.

Read the FGDC-compliant metadata files that are available for each dataset (in .html, .txt, and .xml formats). These files provide numerous details that may be of interest. Also included are flight lines, survey reports, reference materials, and DEM extent shapefiles.

IMPORTANT NOTE: Due to weather and equipment failures the snow-on surveys were flown during 2 different time periods in May, between which there were substantial snow accumulations. Do not combine data from May 5/9, 2010 and May 20/21, 2010.

Publications associated with this dataset can be found at NCALM's Data Tracking Center

The Solar Radiation Potential Model (SRPM) was derived from the Lake County 2007 Digital Surface Model (DSM). The DSM is a 3-foot pixel resolution raster in GeoTIFF format, created using all points (excluding NOISE) from our 2007 LiDAR data without incorporating the breaklines. The SRPM was created using the ArcGIS 'Area Solar Radiation' geoprocessing tool. Due to the number of variables and parameters, the default values of the geoprocessing tool were used.The solar radiation analysis tools in the ArcGIS Spatial Analyst extension enables one to map and analyze the effects of the sun over a geographic area for specific time periods. It accounts for atmospheric effects, site latitude and elevation, steepness (slope) and compass direction (aspect), daily and seasonal shifts of the sun angle, and effects of shadows cast by surrounding topography. The resultant outputs can be easily integrated with other GIS data and can help model physical and biological processes as they are affected by the sun.These data are derived from other data sources, no accuracy measurements or tests were conducted. Primary use and intent for these data are for visualizations and topographic analysis. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

The Solar Radiation Potential Model (SRPM) was derived from the Lake County 2007 Digital Surface Model (DSM). The DSM is a 3-foot pixel resolution raster in GeoTIFF format, created using all points (excluding NOISE) from our 2007 LiDAR data without incorporating the breaklines. The SRPM was created using the ArcGIS 'Area Solar Radiation' geoprocessing tool. Due to the number of variables and parameters, the default values of the geoprocessing tool were used.

The solar radiation analysis tools in the ArcGIS Spatial Analyst extension enables one to map and analyze the effects of the sun over a geographic area for specific time periods. It accounts for atmospheric effects, site latitude and elevation, steepness (slope) and compass direction (aspect), daily and seasonal shifts of the sun angle, and effects of shadows cast by surrounding topography. The resultant outputs can be easily integrated with other GIS data and can help model physical and biological processes as they are affected by the sun.

These data are derived from other data sources, no accuracy measurements or tests were conducted. Primary use and intent for these data are for visualizations and topographic analysis. This dataset does not take the place of an on-site survey for design, construction or regulatory purposes.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This layer is a hydro-flattened bare earth digital elevation model (DEM) derived from the classified Lidar point cloud covering the state of Connecticut.This service (called Statewide2023) will persist as other elevation dates become available. Connect to the Elevation service to always have the latest and greatest service without changing the connection. Visit the CT ECO Map and Image Services page for a complete list of available elevation services. 2023 Statewide Extent: ConnecticutDates: 2023 (March 27 - April 13), between snow melt and leaf outData Info: statewide Digital Elevation Model (DEM), which is a bare earth elevation raster with no functions applied Pixel Resolution: 2 foot DEM raster derived from QL1+ Lidar point cloud with a minimum of 15 points per square meter inland and 20 points per square meter along the coast. The bare earth elevation from the points were averaged to get the elevation value for each pixel in the DEM. Projection: CT State Plane NAD 83 (2011) Feet (EPSG 6434)Service Projection: WGS 1984 Web Mercator Auxiliary Sphere (EPSG 3857)More Information- All About the 2023 Data Collection (Imagery and Lidar)- All about Connecticut Lidar Elevation- Lidar Elevation on CT ECO Explained- Metadata xml formatTips- The elevation service contains processing templates like hillshade, slope, and aspect, that can be applied to change the appearance of the layer. - Symbology is another useful and easy way to display the elevation differently. Credit and Funding