Aspect measures the direction in which a land surface slope faces. The direction is expressed in degrees from north.

The aspect products were derived from the Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016), which was derived from the 1 arc-second resolution SRTM data acquired by NASA in February 2000. The calculation of aspect from DEM-S accounted for the varying spacing between grid points in the geographic projection.

The aspect data are available at 1 arc-second and 3 arc-second resolution

The 3” resolution version of the aspect product has been masked by the 3” water and ocean mask datasets. Lineage: Source data 1. 1 arc-second SRTM-derived Smoothed Digital Elevation Model (DEM-S; ANZCW0703014016).
2. 1 arc-second aspect product 3. 3 arc-second resolution SRTM water body and ocean mask datasets

Aspect calculation Aspect was calculated at 1 arc-0second resolution from DEM-S using the finite difference method (Gallant and Wilson, 2000). The different spacing in the E-W and N-S directions due to the geographic projection of the data was accounted for by using the actual spacing in metres of the grid points calculated from the latitude.

The 3 arc-second resolution version of the aspect product was derived from the 1 arc-second slope and aspect products by reconstructing the x and y components of the surface normal vector, averaging those components, then calculating aspect from the aggregated components.

The aspect calculation was performed on 1° x 1° tiles, with overlaps to ensure correct values at tile edges. The data were masked using the 1" or 3” resolution water and ocean mask datasets.

References Gallant, J.C. and Wilson, J.P. (2000) Primary topographic attributes, chapter 3 in Wilson, J.P. and Gallant, J.C. Terrain Analysis: Principles and Applications, John Wiley and Sons, New York.

This is an aspect-slope raster that was initially created from a 30-foot resolution digital elevation model (DEM) of the Los Angeles County area and resampled to a 50-foot resolution image.Data source: 2006 Digital Elevation Model (DEM) – LARIAC – Public Domain

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.

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.

The kml file contains polygons of bamboo stands in Nagano Prefecture. The csv file contains latitude, longtitude, elevation, area, slope direction and slope aspect of each bamboo stand.

The structure of the critical zone is a product of feedbacks between hydrologic, climatic, biotic, and chemical processes. Ample research within snow-dominated systems has shown that aspect-dependent solar radiation inputs can produce striking differences in vegetation composition, topography, and soil depth between opposing hillslopes. However, more research is needed to understand the role of microclimates on critical zone development within rain-dominated systems, especially below the soil and into weathered bedrock. To address this need, we characterized the critical zone of a north-facing and south-facing slope within a first-order headwater catchment located in central coastal California. We combined terrain analysis of vegetation distribution and topography with field-based soil pit characterization, geophysical surveys and hydrologic measurements between slope-aspects. We observed thicker soil profiles, higher shallow soil moisture, and denser vegetation on north facing slopes, which matched previously documented observations in snow-dominated sites. However, average topographic gradient and saprolite thickness were uniform across our study hillslopes, which did not match common observations from the literature. These results suggest dominant processes for critical zone evolution are not necessarily transferable across climates. Thus, there is a continued need to expand critical zone research, especially in rain-dominated systems. Here, we present four non-exclusive, testable hypotheses of mechanisms that may explain these unexpected similarities in slope and saprolite thickness between hillslopes with opposing aspects. Specifically, we propose both past and present ecohydrologic functions must be taken into account to understand what shaped the present day critical zone.

This dataset is about: Gridded results of slope aspect of swath bathymetric mapping of Disko Bay, Western Greenland, 2007-2008. Please consult parent dataset @ https://doi.org/10.1594/PANGAEA.770250 for more information.

This datalayer is part of a group of layers used for research in the Ipswich River Watershed. This is the aspect model for the study area. The source elevation tile data was provided on the MassGIS website www.state.ma.us/mgis/massgis.htm in ESRI-format shapefile format and imported into IDRISI software using the ShapeIdr command. The resulting vector elevation files were converted to raster format using successive Lineras macro commands. This has the effect of mosaicing the tiles as well. The raster image was filtered once using a low-pass (mean) filter, then masked to the Ipswich study area parameters (extent). The aspect map was created using the surface analysis module. This datalayer was produced as part of a research project concerning the Ipswich River Watershed.

Water stored in the subsurface plays a crucial role in the terrestrial water cycle by influencing vegetation growth, streamflow, and groundwater recharge. Past studies on the impact of aspect-driven differences in incoming solar radiation have largely focused on resulting vegetation and shallow soil moisture patterns. However, few studies have quantified moisture below soil, in weathered bedrock, limiting our understanding of hillslope-scale water cycling patterns and proper water resource management. In a Mediterranean California coast range catchment with a dry growing season and vegetation type differences between aspects, our study challenges the notion that equator-facing slopes are consistently drier than pole-facing slopes. In the 2023 water year, we quantified subsurface moisture using surface and downhole geophysical measurements. Despite greater incoming solar radiation, grass-dominated equator-facing slopes showed greater moisture content than pole-facing slopes with oak trees. These findings underscore the intricate link between vegetation type and subsurface moisture, which is crucial for understanding water resources in watersheds with clear aspect-driven ecosystem differences.

Slope aspect can cause environmental heterogeneity over relatively short distances, which in turn affects plant distribution, community structure, and ecosystem function. However, the response and adaptation strategies of plants to slope aspects via regulating their physiological and morphological properties still remain poorly understood, especially in alpine ecosystems. Here, we selected four common species, including Bistorta macrophylla, Bistorta vivipara, Cremanthodium discoideum, and Deschampsia littoralis, to test how biomass allocation and functional traits of height, individual leaf area, individual leaf mass, and specific leaf area (SLA) respond to variation in slope aspect in the Minshan Mountain, eastern Tibetan Plateau. We found that the slope aspect affected SLA and stem, flower mass fraction with higher values at southwest slope aspect, which is potentially related to light environment. The low-temperature environment caused by the slope aspect facilitates the accumulation of root biomass especially at the northeast slope aspect. Cremanthodium discoideum and D. littoralis invested more in belowground biomass in southeast and southwest slope aspects, although a large number of significant isometric allocations were found in B. macrophylla and B. vivipara. Finally, we found that both biotic and abiotic factors are responsible for the variation in total biomass with contrasting effects across different species. These results suggest that slope aspect, as an important topographic variable, strongly influences plant survival, growth, and propagation. Therefore, habitat heterogeneity stemming from topographic factors (slope aspect) can prevent biotic homogenization and thus contribute to the improvement of diverse ecosystem functioning.

The SVTM Modelling Grid Collection refers to a suite of around 80 environmental layers that are used for species distribution modelling (SDM). Environmental layers comprise climate, terrain and soil variables for the state of NSW. Layers are used as covariates for the modelling of plant community types within NSW.\r \r Climate variables, such as annual temperature, precipitation, solar radiation and others are generated by ANUCLIM (Version 6.1 MTHCLIM module), and the Bureau of Meteorology, Gridded climate data (http://www.bom.gov.au/climate/averages/climatology/gridded-data-info/gridded-climate-data.shtml). ANUCLIM input includes a digital elevation model - the elevation model used for these climate surfaces was the 1 second smoothed DEMS from the Shuttle Radar Topographic Mission (SRTM DEM-S see Gallant et al. 2011). The same DEM was used to create topographic variables, such as slope, aspect, roughness and topographic position index. Soil variables, such as clay, sand, silt content, organic carbon, pH, total nitrogen, and others are products of the Soil and Landscape Grid of Australia's, Australia-wide Soil Attribute Maps (https://www.clw.csiro.au/aclep/soilandlandscapegrid/ProductDetails-SoilAttributes.html). Soil attributes are modelled from measured soil attribute data from existing databases in the national soil site data collation and environmental parameters. \r \r All grids have a common projection, grid cell resolution and snapped to the same spatial extent. The grid cell resolution is 1 second or approximately 30m.\r \r NOTE: This asset does not refer to a distinct layer, rather a collection of related environmental datasets used for vegetation modelling as part of the State Vegetation Type Map Modelling Grid Collection. This list of environmental datasets is attached as a resource. Further information can be found at https://www.environment.nsw.gov.au/vegetation/state-vegetation-type-map.htm.\r

This dataset has been created to meet the needs of the research community of Arizona State University. Aspect can be thought of as the slope direction. It identifies the down-slope direction of the maximum rate of change in value (elevation) from each DEM cell to its neighbor cells. The values of the output grid are the compass direction of the aspect. The data is derived from the 30 meter Digital Elevation Model created for Central Arizona - Phoenix LTER (dem30_utm).

This layer provides aspect values calculated dynamically using the server-side aspect function applied to a Terrain layer. The values are float, and represent the orientation of the downward sloping terrain 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 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.For more details such as Data Sources, Mosaic method used in this layer, please see the Terrain layer.This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.

This map provides a colorized representation of aspect, generated dynamically using the server-side aspect function on the Terrain service. 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. If you require access to numeric (float) aspect values, use the Terrain: Aspect layer, which returns orientation values from 0 to 360 degrees. 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.

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

In addition to this statewide 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).

Slope/aspect categories within mule deer winter range in the Cariboo Region.

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 Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_SC) dataset, which provides global slope and curvature elevation data at 1 arc second spacing. NASADEM data products were derived from original telemetry data from the Shuttle Radar Topography Mission (SRTM), a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM’s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and flew for 11 days. In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy. Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling. NASADEM are distributed in 1° by 1° tiles and consist of all land between 60° N and 56° S latitude. This accounts for about 80% of Earth’s total landmass. NASADEM_SC data product layers include slope, aspect angle, profile curvature, plan curvature, and an updated SRTM water body dataset (water mask). A low-resolution browse image showing slope is also available for each NASADEM_SC granule.

The elevation was accessed for the area of interest in 90 m spatial resolution from the TanDEM-X 90 m digital elevation model (DEM) product (Krieger et al, 2013). Prior to spatial topographical parameters extraction, the DEM was resampled from the 90-m cell spacing to a 30-m resolution. The result was classified into 589 different possible combinations of elevation, slope angle, aspect. For the classification we used the possible combinations of elevation, slope, and aspect which were grouped into the following categories:

Elevation:

0-400 m

400-450m

450-500m

500-600m

600-650m

650-700m

700-1000m

1000-1500m

Slope:

0-2°

2-4°

4-6°

6-8°

8-10°

10-12°

12-16°

16-18°

18-20°

20-25°

25-50°

Aspect:

0-45°

45-90°

90-135°

135-180°

180-225°

225-270°

270-315°

315-360°

Format: Geotiff; projection UTM58N and 30x30 m tiles; extent: 642010.1, 654910.1, 7462218, 7492908 m (xmin, xmax, ymin, ymax)