This raster layer is an aspect slope map that displays the cardinal direction that sloped areas face.White - Flat (-1)Red - North (0-22.5)Orange - Northeast (22.5-67.5)Yellow - East (67.5-112.5)Green - Southeast (112.5-157.5)Light Blue - South (157.5-202.5)Blue - Southwest (202.5-247.5)Deep Blue - West (247.5-292.5)Pink - Northwest (292.5-337.5)

Important Note: This item is in mature support as of July 2024 and will retire in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality Digital Surface Model (DSM) of the Arctic using optical stereo imagery. This Arctic DEM layer consists of a collection of elevation data compiled from DigitalGlobe satellite imagery.Geographic ExtentAll land area north of 60° north latitude, including all territory of Greenland, the entire state of Alaska, and the Kamchatka Peninsula of the Russian Federation.Map ProjectionThis layer is projected to WGS 1984 EPSG Alaska Polar Stereographic.The source data is projected to WGS 84 / NSIDC Sea Ice Polar Stereographic North.NOTE: By default, opening this layer in the Map Viewer will project the layer to Web Mercator. To display in the Alaska Polar projection, use Arctic DEM Web Map.Spatial Resolution2-meterAccuracyWithout ground control points absolute accuracy is approximately 4 meters in horizontal and vertical planes. Uniform ground control must be applied to achieve higher accuracy. Laser altimetry data from the NASA IceSAT spacecraft has been applied to the ArcticDEM mosaic files. Users may wish to use other sources for smaller areas, particularly on ArcticDEM strip files. Strip DEM files contain IceSAT altimetry offsets within the metadata, but have not had these values applied.The accuracy of these layers will vary as a function of location and data source. Please refer to the metadata available in the layers, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes.Height ValuesHeight values provided in meters (32-bit float)This layer provides height values as Orthometric height above the EGM2008 geoid.The ArcticDEM product is a Digital Surface Model (DSM) which includes above ground features such as man-made structures and vegetation.Data Dimensions and CompositionDEM Tiles are compiled from multiple strips that have been co-registered, blended, and feathered to reduce edge-matching artifacts. Tile sizes are standardized at 50 km x 50 km.Individual DEM strips are compiled from DigitalGlobe images. DEM strip dimensions will vary according to the sensor, off-nadir angle of collection, and the corresponding stereo-pair overlap. Most strips are between 16 km and 18 km in width, and 110 km and 120 km in length. Using this layerThe default view for this layer is the raw DEM data, returned as 32-bit floating point height values. This is ideal for computational analysis but limited in terms of visual context and analysis. This layer can be temporally filtered by acquisition date. This layer allows query, identify, and export image requests. The layer is restricted to a 4000 x 4000 pixel limit in a single request.For additional visual context and analysis, below is the full list of derivative layers available as Raster Functions. These can be accessed from within the service or as individual AGOL items: Hillshade Gray, Aspect Degrees, Aspect Map, Contour 25, Hillshade Multidirectional, Slope Map, Slope Degrees, Contour Smoothed 25, Hillshade Elevation Tinted, Height Ellipsoidal Additional Data SpecificationsThe data has not been edited to remove processing anomalies. Pits, spikes, false landforms, and other DEM anomalies may exist in this dataset. Polygonal hydrographic features have not been flattened and the data has not been hydrologically enforced.Since the DEM’s are optically derived, clouds, fog, shadows, and other atmospheric obstructions can obscure the ground resulting in data gaps.Since the DEM strips have not been edge-matched, visible seams and deviations between adjacent strips may be observed.The data spans multiple years and seasons. A single season/year mosaic is not possible for large areas.Mosaic tiles are displayed by default. Strips can be selected and displayed via image filtering.For quick and easy access to this and additional elevation layers, see the Elevation Layers group in ArcGIS Online.For more information on the source data, see ArcticDEM.

This map provides a colorized representation of aspect, generated dynamically using the server-side aspect function on the Terrain layer. The orientation of the downward sloping terrain (0° – 360°) is indicated by different colors, rotating from green (North) to blue (East), to magenta (South) to orange (West). Flat areas having no down slope direction are given a value of 361° and rendered as gray. This service can be used for visualization or analysis. Note: If you require access to numeric (float) aspect values, use the Terrain - Aspect layer, which returns orientation values from 0 to 360 degrees. Units: DegreesUpdate Frequency: QuarterlyCoverage: World/GlobalData Sources: This layer is compiled from a variety of best available sources from several data providers. To see the coverage and extents of various datasets comprising this service in an interactive map, see World Elevation Coverage Map.What can you do with this layer?Use for Visualization: Yes. This colorized aspect map is appropriate for visualizing the downslope direction of the terrain. This layer can be added to applications or maps to enhance contextual understanding.Use for Analysis: Yes. 8 bit color values returned by this service represent integer aspect values. For float values, use the Terrain - Aspect layer.For more details such as Data Sources, Mosaic method used in this layer, please see the Terrain layer. This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single export image request.

This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

An aspect map (slope direction) derived from Digital Elevation Models (DEMs) with a 3ft. grid cell size. Compass direction is rendered using the following colors: red (north), magenta (northwest), blue (west), cyan (southwest), light cyan (south), light green (southeast), light orange (east), orange (northeast). Data used to create the DEMs was derived from LiDAR collected by the NC Floodplain Mapping Program and processed by NC Department of Public Safety - Division of Emergency Management.Download county-based DEMs from the NC OneMap Direct Data Downloads. Data should not be downloaded using the map on the dataset's item page.

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

This layer provides aspect values calculated dynamically using the server-side aspect function applied on the Terrain layer. The values are float, and represent the orientation of the downward sloping terrain in degrees (0 to 360), clockwise from north. Cells in the input raster that are flat with zero slope are assigned an aspect of -1.Units: DegreesUpdate Frequency: QuarterlyCoverage: World/GlobalData Sources: This layer is compiled from a variety of best available sources from several data providers. To see the coverage and extents of various datasets comprising this service in an interactive map, see World Elevation Coverage Map.WARNING: Aspect is computed in the projection specified by the client software. The server resamples the data to the required projection and then computes aspect. The default projection for web applications is Mercator in which scale increases equally in x and y by latitude, so aspect computations are not affected. Using geographic coordinates will give distorted results. It is advised to check the client application projection prior to obtaining aspect values. What can you do with this layer?Use for Visualization: No. This layer provides numeric values indicating terrain characteristics, and is not generally appropriate for visual interpretation, unless the client application applies an additional color map. For visualization use the Terrain - Aspect Map.Use for Analysis: Yes. This layer provides numeric values indicating the orientation of the terrain within a raster cell, calculated based on the defined cell size. There is a limit of 5000 rows x 5000 columns. For more details such as Data Sources, Mosaic method used in this layer, please see the Terrain layer. This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single export image request.This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

The hachure cartographic technique sketches downhill lines along bands of equal elevation to create a topographic effect. This is a rather vintage technique, giving way in the digital age to hillshading. But, shoot, there is just something wonderful about a hachured map. It has a wonderful textural quality and effectively and efficiently conveys topographic aspect and slope. This style is in a manner in keeping with that retro hand-drawn aesthetic, with inky colors, wavy-hand linework, and grainy sketchy downhill strokes.The hachures themselves are available in a few flavors ranging from simple sketched contour lines to densely packed hachures for an almost fur-like surface. Eh, why not? Also available are a handful of tuft-like point features and a few vintage polygon fills like parchment and foxed atlas paper.Let your inner cARRRRRRtographer run wild.Thanks to cartographer Jared Fischer, of the Dept. of the Interior, for his collaboration and inspiration along the way.Find more, larger, examples here.Happy Hachure Mapping! John Nelson

Important Note: This item is in mature support as of July 2024 and will retire in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.ArcticDEM is a National Geospatial-Intelligence Agency (NGA) and National Science Foundation (NSF) public-private initiative to automatically produce a high-resolution, high-quality Digital Surface Model (DSM) of the Arctic using sub-meter, stereoscopic satellite imagery collected by DigitalGlobe’s satellite constellation.The Arctic DEM layer is rendered here as Aspect Degrees. Using the server-side aspect function, this layer dynamically calculates and returns aspect values. The values are float, and represent the orientation of the downward sloping surface in degrees (0 to 359.9), clockwise from north. Cells in the input raster that are flat with zero slope are assigned an aspect of -1.WARNING: Aspect is computed in the projection specified by the client software. The server resamples the data to the required projection and then computes aspect. The default projection for this layer is WGS_1984_EPSG_Alaska_Polar_Stereographic. Using geographic coordinates will give distorted results. It is advised to check the client application projection prior to obtaining aspect values.Geographic ExtentAll land area north of 60° north latitude, including all territory of Greenland, the entire state of Alaska, and the Kamchatka Peninsula of the Russian Federation.Map ProjectionThis web map is projected to WGS 1984 EPSG Alaska Polar Stereographic.Spatial Resolution2-meterAccuracyWithout ground control points absolute accuracy is approximately 4 meters in horizontal and vertical planes. Uniform ground control must be applied to achieve higher accuracy. Laser altimetry data from the NASA IceSAT spacecraft has been applied to the ArcticDEM mosaic files. Users may wish to use other sources for smaller areas, particularly on ArcticDEM strip files. Strip DEM files contain IceSAT altimetry offsets within the metadata, but have not had these values applied.The accuracy of these layers will vary as a function of location and data source. Please refer to the metadata available in the layers, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes.Pixel ValuesThis layer provides numeric values indicating the orientation of the surface within a raster cell, calculated based on the defined cell size.For elevation height values, please reference either Arctic DEM or Arctic DEM: Height Ellipsoidal.Data Dimensions and CompositionDEM Tiles are compiled from multiple strips that have been co-registered, blended, and feathered to reduce edge-matching artifacts. Tile sizes are standardized at 50 km x 50 km.Individual DEM strips are compiled from DigitalGlobe images. DEM strip dimensions will vary according to the sensor, off-nadir angle of collection, and the corresponding stereo-pair overlap. Most strips are between 16 km and 18 km in width, and 110 km and 120 km in length. Using this layerThis layer provides numeric values indicating the orientation of the surface within a raster cell, calculated based on the defined cell size.This layer is not generally appropriate for visual interpretation, unless the client application applies an additional color map. For visualization, use the Arctic DEM: Aspect Map.This layer can be temporally filtered by acquisition date. This layer allows query, identify, and export image requests. The layer is restricted to a 4000 x 4000 pixel limit in a single request.For additional visual context and analysis, below is the full list of layers available as Raster Functions. These can be accessed from within the service or as individual AGOL items: Arctic DEM, Hillshade Gray, Aspect Degrees, Aspect Map, Contour 25, Hillshade Multidirectional, Slope Map, Slope Degrees, Contour Smoothed 25, Hillshade Elevation Tinted, Height Ellipsoidal Additional Data SpecificationsThe ArcticDEM product is a Digital Surface Model (DSM) which includes above ground features such as man-made structures and vegetation.The data has not been edited to remove processing anomalies. Pits, spikes, false landforms, and other DEM anomalies may exist in this dataset. Polygonal hydrographic features have not been flattened and the data has not been hydrologically enforced.Since the DEM’s are optically derived, clouds, fog, shadows, and other atmospheric obstructions can obscure the ground resulting in data gaps.Since the DEM strips have not been edge-matched, visible seams and deviations between adjacent strips may be observed.The data spans multiple years and seasons. A single season/year mosaic is not possible for large areas.Mosaic tiles are displayed by default. Strips can be selected and displayed via image filtering.For quick and easy access to this and additional elevation layers, see the Elevation Layers group in ArcGIS Online.For more information on the source data, see ArcticDEM.

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

This dynamic World Elevation Terrain layer returns float values representing ground heights in meters and compiles multi-resolution data from many authoritative data providers from across the globe. Heights are orthometric (sea level = 0), and water bodies that are above sea level have approximated nominal water heights.Height units: MetersUpdate Frequency: QuarterlyCoverage: World/GlobalData Sources: This layer is compiled from a variety of best available sources from several data providers. To see the coverage and extents of various datasets comprising this service in an interactive map, see World Elevation Coverage Map.What can you do with this layer?Use for Visualization: This layer is generally not optimal for direct visualization. By default, 32 bit floating point values are returned, resulting in higher bandwidth requirements. Therefore, usage should be limited to applications requiring elevation data values. Alternatively, client applications can select from numerous additional functions, applied on the server, that return rendered data. For visualizations such as multi-directional hillshade, hillshade, elevation tinted hillshade, and slope, consider using the appropriate server-side function defined on this service.Use for Analysis: Yes. This layer provides data as floating point elevation values suitable for use in analysis. There is a limit of 5000 rows x 5000 columns.Note: This layer combine data from different sources and resamples the data dynamically to the requested projection, extent and pixel size. For analyses using ArcGIS Desktop, it is recommended to filter a dataset, specify the projection, extent and cell size using the Make Image Server Layer geoprocessing tool. The extent is factor of cell size and rows/columns limit. e.g. if cell size is 10 m, the extent for analysis would be less than 50,000 m x 50,000 m.Server Functions: This layer has server functions defined for the following elevation derivatives. In ArcGIS Pro, server function can be invoked from Layer Properties - Processing Templates.

Slope Degrees Slope Percent Aspect Ellipsoidal height Hillshade Multi-Directional Hillshade Dark Multi-Directional Hillshade Elevation Tinted Hillshade Slope Map Aspect Map Mosaic Method: This image service uses a default mosaic method of "By Attribute”, using Field 'Best' and target of 0. Each of the rasters has been attributed with ‘Best’ field value that is generally a function of the pixel size such that higher resolution datasets are displayed at higher priority. Other mosaic methods can be set, but care should be taken as the order of the rasters may change. Where required, queries can also be set to display only specific datasets such as only NED or the lock raster mosaic rule used to lock to a specific dataset.Accuracy: Accuracy will vary as a function of location and data source. Please refer to the metadata available in the layer, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes, where available.This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single request.This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

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.

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Valles Calders, upper part of the Jemez River basin by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).

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).

IMPORTANT: This is the source of the feature layer template in the LearnArcGIS Lesson: Prepare for SAR Incidents and for the MapSAR Solution. If this layer is cloned or copied, the owner of the items needs to update the item details to reflect this. Purpose: This is a feature layer template for use in missing person search operations. It is based on the MapSAR (ArcGIS Desktop) Data Model but simplified for use in web maps and apps. Please see MapSAR GitHub for more information on this project.Maps are at the core of any Search and Rescue (SAR) operation. Geographic information system (GIS) software allows rescue personnel to quickly generate maps that depict specific aspects of the operation and show what is happening on the ground over time. The maps and operations data can be shared over a network to supply an enhanced common operating picture throughout the Incident Command Post (ICP). A team of GIS and SAR professionals from Sierra Madre Search and Rescue Team, Esri, Sequoia and Kings Canyon National Park, Yosemite National Park, Grand Canyon National Park, and the Mountaineer Rescue Group came together to develop the tools and instructions to fit established SAR workflows. The goal is to meet the critical need to provide standards, documents, and training to the international SAR community and establish more widespread and effective integration of GIS into operations.See Comments below for updates to the data model.

Graphing topological features of the ocean seafloor provides insight for diverse scientific disciplines. Here, we provide visual representation of the combined slope and aspect of the swath sonar bathymetry during the POLARSTERN cruise PS101 (ARK-XXX/3). This dataset contains two raster grids in GeoTiff format (color-rgb type and value type), a symbology classification layer file, and an overview map with legend. The value-type GeoTIFF has an accompanying symbology layer file that can be applied in ArcGIS. Each pixel value has an associated color (aspect) and hue (slope) classification. This combination of aspect and slope makes this layer uniquely informative and indended for visualization purposes; see "PS101_aspect_slope_map.png (hdl:10013/epic.51997.d001)" for a map preview. The orientation aspect values are from 0 to 359 degrees and the slope values are 5, 15, 30, and 45 percent rise. Values less than 5 percent are flat areas and have no associated orientation values. The GeoTiff has a pixel size of 100 m x 100 m and was created using ArcGIS 10.5 software, in stereographic polar projection, datum WGS 84.

The zip file contains: 1. PS101_aspect_slope.tif 2. PS101_aspect_slope_value.tif 3. PS101_aspect_slope_symbology.lyr 4. PS101_aspect_slope_map.png (hdl:10013/epic.51997.d001)

Aspect and hillshade was derived primarily from the 2017 Washoe County 3DEP LIDAR with some inputs in the Tahoe Basin from the 2010 Tahoe Basin LIDAR. The two DEMs were combined into a single DEM and a hillshade and slope map was derived from that DEM. The data were then smoothed at 25x25 meters and polygons were generated to represent 45 degree increments. The polygons are visible when zooming in closer than 1:5,000 map scale.

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Catalina Mountains by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. We followed methods in Anderson and Merrill (1998) for combining gradient layers into an “ecological land units” map (also referred to as a “biophysical units” map). Our goal was to use this information to create sampling strata that capture the range of environments observed. The Anderson and Merrill (1998) method (implemented as a set of GIS scripts by F. Biasi (2001)) builds an ecological units map by classifying and combining individual environmental gradient maps in a GIS. Maps of aspect, moisture, slope, and slope shape are reclassified and assembled to produce maps of landform units. These landform units are then combined with reclassified elevation and geologic maps to produce a final ecological land units or “ELU” map. We used these methods as a guide to building an ecological land units map for Shenandoah National Park, adapting the procedures for local conditions. Individual steps in the process and maps resulting from intermediate and final stages are described in the report.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. were derived from the NVC. NatureServe developed a preliminary list of potential vegetation types. These data were combined with existing plot data (Cully 2002) to derive an initial list of potential types. Additional data and information were gleaned from a field visit and incorporated into the final list of map units. Because of the park’s small size and the large amount of field data, the map units are equivalent to existing vegetation associations or local associations/descriptions (e.g., Prairie Dog Colony). In addition to vegetation type, vegetation structures were described using three attributes: height, coverage density, and coverage pattern. In addition to vegetation structure and context, a number of attributes for each polygon were stored in the associated table within the GIS database. Many of these attributes were derived from the photointerpretation; others were calculated or crosswalked from other classifications. Table 2.7.2 shows all of the attributes and their sources. Anderson Level 1 and 2 codes are also included (Anderson et al. 1976). These codes should allow for a more regional perspective on the vegetation types. Look-up tables for the names associated with the codes is included within the geodatabase and in Appendix D. The look-up tables contain all the NVC formation information as well as alliance names, unique IDs, and the ecological system codes (El_Code) for the associations. These El_Codes often represent a one-to-many relationship; that is, one association may be related to more than one ecological system. The NatureServe conservation status is included as a separate item. Finally, slope (degrees), aspect, and elevation were calculated for each polygon label point using a digital elevation model and an ArcView script. The slope figure will vary if one uses a TIN (triangulated irregular network) versus a GRID (grid-referenced information display) for the calculation (Jenness 2005). A grid was used for the slope figure in this dataset. Acres and hectares were calculated using XTools Pro for ArcGIS Desktop.

Geographic Extent: SANDY_Restoration_DE_MD_QL2 Area of Interest covers approximately 3.096 square miles. Lot #5 contains the full project area Dataset Description: The SANDY_Restoration_DE_MD_QL2 project called for the Planning, Acquisition, processing and derivative products of LIDAR data to be collected at a nominal pulse spacing (NPS) of 0.7 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base LIDAR Specification, Version 1. The data was developed based on a horizontal projection/datum of State Plane Zone Maryland (1900), NAD83, feet and vertical datum of NAVD1988 (GEOID12A), feet. LiDAR data was delivered in RAW flight line swath format, processed to create Classified LAS 1.2 Files formatted to 3842 individual 1500m x 1500m tiles, and corresponding Intensity Images and Bare Earth DEMs tiled to the same 1500m x 1500m schema, and Breaklines in ESRI shapefile format. Ground Conditions: LiDAR was collected in Winter 2013 / Spring 2014, while no snow was on the ground and rivers were at or below normal levels. In order to post process the LiDAR data to meet task order specifications, Quantum Spatial established a total of 78 QA control points and 99 Land Cover control points that were used to calibrate the LIDAR to known ground locations established throughout the SANDY_Restoration_DE_MD_QL2 project area.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Image Service Link: https://mdgeodata.md.gov/lidar/rest/services/Caroline/MD_caroline_aspect_m/ImageServer