I need to obtain a grid of bare ground elevation (removing all edifices, trees, roads and man-made elements) for quantitative geomorphological analysis from a high resolution (1 m) DSM obtained by orthoimages (not from LIDAR). Is there any suggestion you can provide me to filter my original grid?
This filtering process is usually performed on a lidar point cloud and not an interpolated derivative. It is unlikely that you will have satisfactory results attempting to filter the DSM. I would highly recommend tracking down the original lidar data.
You could attempt to treat your DSM as a point cloud by converting it to points and then running a filter intended for lidar point clouds. Depending on the algorithm, you may get a suitable result for generating a bare earth DEM. However, it may end up oversmoothed and not supporting the current resolution of your DSM.
Some recommended "free" lidar filtering software:
Airborne LIDAR Data Processing and Analysis Tools (ALDPAT)
GRASS GIS specifically, v.lidar.correction
Idaho State University Boise Center Aerospace Lab IDL Virtual Machine software (BCAL)
USFS-PNW lidar processing and visualization software (FUSION)
USFS-RMRS Multiscale Curvature Classification (MCC)
How to obtain a DTM/DEM from DSM - Geographic Information Systems
A digital elevation model (DEM) is a digital model or 3D representation of a terrain’s surface — commonly for a planet (including Earth), moon, or asteroid — created from terrain elevation data.
In most cases the term digital surface model represents the earth’s surface and includes all objects on it. In contrast to a DSM, the digital terrain model (DTM) represents the bare ground surface without any objects like plants and buildings.
DEM is often used as a generic term for DSMs and DTMs, only representing height information without any further definition about the surface. Other definitions equalise the terms DEM and DTM, or define the DEM as a subset of the DTM, which also represents other morphological elements. There are also definitions which equalise the terms DEM and DSM. On the Web definitions can be found which define DEM as a regularly spaced GRID and a DTM as a three-dimensional model (TIN). Most of the data providers (USGS, ERSDAC, CGIAR, Spot Image) use the term DEM as a generic term for DSMs and DTMs. All datasets which are captured with satellites, airplanes or other flying platforms are originally DSMs (like SRTM or the ASTER GDEM). It is possible to compute a DTM from high resolution DSM datasets with complex algorithms. In the following the term DEM is used as a generic term for DSMs and DTMs.
Types of DEM
Height map of Earth’s surface (including water and ice) in equirectangular projection, normalized as 8-bit grayscale, where lighter values indicate higher elevation.
A DEM can be represented as a raster (a grid of squares, also known as a heightmap when representing elevation) or as a vector-based triangular irregular network (TIN). The TIN DEM dataset is also referred to as a primary (measured) DEM, whereas the Raster DEM is referred to as a secondary (computed) DEM. The DEM could be acquired through techniques such as photogrammetry, lidar, IfSAR, land surveying, etc. DEMs are commonly built using data collected using remote sensing techniques, but they may also be built from land surveying. DEMs are used often in geographic information systems, and are the most common basis for digitally produced relief maps. While a DSM may be useful for landscape modeling, city modeling and visualization applications, a DTM is often required for flood or drainage modeling, land-use studies, geological applications, and other applications.
Representation of Elevation Data
2. Raster (Example GRID and ASCII), which could be square, rectangular, hexagonal, triangular in shape) (GRID and ASCII stands for “Generic Region for Information Display” and “American Standard Code for Information Interchange” respectively)
2. Vector (Example TIN, which is triangular only and stands for “Triangulated Irregular Network”).
Digital Elevation Models
A digital elevation model is a three-dimensional, computer-generated representation of a terrain surface. A DEM is a ‘bare-earth’ elevation model, meaning it is free of vegetation, structures, and other non-terrain objects. DEMs can be represented as a grid of squares, or as a vector-based triangular irregular network (TIN). They are critically important for land-use planning, infrastructural project management, soil science, hydrology, and flow-direction studies. DEMs are often used in geographic information systems and digitally-produced relief maps.
USGS EROS Archive - Digital Elevation - Interferometric Synthetic Aperture Radar (IFSAR) - Alaska
Interferometric Synthetic Aperture Radar (IFSAR) data were used to generate Digital Surface Model (DSM) and Digital Terrain Model (DTM) data for Alaska (2010-2012).
Susitna Flats State Game Refuge (July 2010)
The U.S. Geological Survey (USGS) National Geospatial Program (NGP) developed the Alaska Mapping Initiative (AMI) to collaborate with State and other Federal partners in Alaska to acquire 3-dimensional elevation data to improve statewide topographic mapping products. AMI coordinates Federal activities through the Alaska Mapping Executive Committee (AMEC) and State efforts through Alaska’s Statewide Digital Mapping Initiative (SDMI) to ensure a unified approach for consistent data acquisition and enhancement of elevation data products.
AMI attained interferometric synthetic aperture radar (IFSAR) data to generate Digital Elevation Models (DEMs). This radar mapping technology is an effective tool for collecting data under challenging circumstances such as cloud cover, extreme weather conditions, rugged terrain, and remote locations. Airborne IFSAR data were flown over south-central Alaska in summer 2010 and over northwestern Alaska in 2012. Additional areas may become available as projects are inspected for quality and released for dissemination. A coverage map in EarthExplorer indicates the extent of distributable data.
IFSAR Alaska Products
Elevation products generated from IFSAR data include Digital Surface Model (DSM) and Digital Terrain Model (DTM) data.
DSMs provide elevation values of landscape features on the earth's surface. This topographic product contains the height of the highest surface on the ground including vegetation, man-made structures, and bare earth.
DTMs provide elevation values of the underlying terrain of the earth’s surface. This topographic product reflects the height of bare earth where the elevations of vegetation and man-made features have been removed.
The USGS Earth Resources Observation and Science (EROS) Center distributes IFSAR Alaska products in Georeferenced Tagged Image File Format (GeoTIFF). The pixel values for the grayscale images represent elevation numbers.
|Projection||Alaska Albers Conical Equal Area|
|Vertical Accuracy||3-meter Confidence Level of 90% for a 0-10 degree slope|
|Horizontal Accuracy||12.2-meter Circular Error of 90% (CE90) 13.9-meter Circular Error of 95% (CE95) 5.682-meter Root Mean Square Error (RMSE) for x and y|
|Raster Size||15 minute tiles|
|File Size||50 - 100 megabytes|
DEM products meet the horizontal accuracy requirements for USGS maps and orthophotos at 1:24,000-scale.
Coverage Maps indicating the availability of IFSAR Alaska products are available for download.
EarthExplorer can be used to search, preview, and download IFSAR Alaska data. The collection is located under the Digital Elevation category.
How to obtain a DTM/DEM from DSM - Geographic Information Systems
DTM is often used as a generic term for DSMs and DTMs, only representing height information without any further definition about the surface Other definitions equalise the terms DEM and DTM,or define the DEM as a subset of the DTM, which also represents other morphological elements.
There are also definitions which equalise the terms DEM and DSM.On the Web definitions can be found which define DEM as a regularly spaced GRID and a DTM as a three-dimensional model (TIN). Most of the data providers (USGS, ERSDAC, CGIAR, Spot Image) use the term DEM as a generic term for DSMs and DTMs. All datasets which are captured with satellites, airplanes or other flying platforms are originally DSMs (like SRTM or the ASTER GDEM). It is possible to compute a DTM from high resolution DSM datasets with complex algorithms (Li et al., 2005). In the following the term DEM is used as a generic term for DSMs and DTMs.
A DEM can be represented as a raster (a grid of squares, also known as a heightmap when representing elevation) or as a vector-based (TIN). The TIN DEM dataset is also referred to as a primary (measured) DEM, whereas the Raster DEM is referred to as a secondary (computed) DEM. The DEM could be acquired through techniques such as photogrammetry, lidar, IfSAR, land surveying, etc. (Li et al. 2005). DEMs are commonly built using data collected using remote sensing techniques, but they may also be built from land surveying. DEMs are used often in geographic information systems, and are the most common basis for digitally-produced relief maps.
While a DSM may be useful for landscape modeling, city modeling and visualization applications, a DTM is often required for flood or drainage modeling, land-use studies, geological applications, and other applications.
Your best source of data for the UK is data.gov.uk.
The LIDAR DSM (Digital Surface Model) Time Stamped Tiles product is an archive of raster elevation data produced by the Environment Agency. Site specific surveys have been carried out across England since 1998, with certain areas, such as the coastal zone, being surveyed multiple times.
The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering
75% of England at 2m spatial resolution.
National LIDAR Programme will have updated elevation data by 2021. You can see a map of which areas have been surveyed so far here. The Yorkshire Dales area is listed as "planned" with no target date specified.
The Environment Agency National LIDAR Programme aims to provide accurate elevation data at 1m spatial resolution for all of England by 2021.
The HIDROPIXEL high-resolution pixel-to-pixel distributed hydrological simulation approach was proposed based on digital elevation model (DEM) and adaptations of the curve number and unit hydrograph methods. This paper presents a reference evaluation of HIDROPIXEL, showing how sensible the model is to spatial resolution and assessing the effect of different DEM data sources. A small peri-urban Brazilian catchment (
6 km 2 ) is studied using a 1 m LiDAR DEM (
6 million pixels) and aggregated 2 m, 10 m, and 30 m, and SRTM 30 m resolutions. Peak flows were satisfactorily reproduced, with model performance decreasing with the spatial resolution coarsening, which tended to shorten the flow paths and underestimate the drainage area. For short and concentrated rain events, peak times were anticipated. Best results were obtained by adjusting the initial losses parameter. This methodology could easily be applied to other catchments, incorporating high-resolution DEM and simulating both land-use changes and spatial rainfall variability.
Above-ground biomass (AGB) is an essential indicator for assessing ecosystem health and carbon storage in desert shrub-related research. Above-ground volume (AGV) of vegetation is a crucial parameter to estimate the AGB. In unmanned aerial vehicle (UAV) remote sensing, the AGV and AGB are mainly estimated by vegetation feature metrics (for example, spectral indices, textural, and structural metrics). However, there is limited study on the AGV and AGB estimation in desert shrub communities by using UAV, and it is difficult to determine the contribution of these metrics to AGV models under eliminating the influence of background factors. Taking a typical desert shrub area in Inner Mongolia, China as an example, this study develops an improved approach to extracted three types of feature metrics simultaneously using UAV RGB (Red, Green, Blue) images. First, digital orthophoto map (DOM) and digital surface model (DSM) were created through the photogrammetric procedure based on UAV RGB images. Second, the digital terrain model (DTM) for canopy height calculation was generated based on DOM and DSM by object-oriented image binary classification and ground elevation interpolation. Here, we recommended the ENVI Landsat Gap-fill tool to interpolate the ground elevation of vegetation areas. Meanwhile, 21 spectral indices, eight textural metrics, and five structural metrics were extracted. Finally, single-variable and multi-variable commonly used regression models were established based on these metrics and measured AGV with a leave-one-out cross-validation. Results showed that: (1) in the proposed model, the contribution of structural, textural, and spectral metric to shrub AGV models was 86.68, 7.08, and 6.24%, respectively. (2) The horizontal and vertical structural metrics, textural metrics, or spectral indices reflected the one-dimensional change of AGV, which had a saturation effect. (3) The canopy volume, combining the horizontal and vertical characteristics of vegetation canopy, could describe the overall change of AGV and played the most essential role in AGV modelling (R 2 = 0.928, relative RMSE = 26.8%). The study findings provide a direct reference in determining suitable vegetation feature metrics for monitoring shrub AGV. The proposed approach for DTM generation and AGV estimation is more efficient, accurate and low-cost than before, and it can be a useful bridge between ground-based investigation and satellite remote sensing.
Mappers may prepare digital elevation models in a number of ways, but they frequently use remote sensing rather than direct survey data. One powerful technique for generating digital elevation models is interferometric synthetic aperture radar: two passes of a radar satellite (such as RADARSAT-1 or TerraSAR-X or Cosmo SkyMed), or a single pass if the satellite is equipped with two antennas (like the SRTM instrumentation), suffice to generate a digital elevation map tens of kilometers on a side with a resolution of around ten meters [ citation needed ] . Alternatively, other kinds of stereoscopic pairs can be employed using the digital image correlation method, where two optical images acquired with different angles taken from the same pass of an airplane or an Earth Observation Satellite (such as the HRS instrument of SPOT5 or the VNIR band of ASTER). [ 10 ]
In 1986, the SPOT 1 satellite provided the first usable elevation data for a sizeable portion of the planet's landmass, using two-passes stereoscopic correlation. Later, further data were provided by the European Remote-Sensing Satellite (ERS) using the same method, the Shuttle Radar Topography Mission using single-pass SAR and the ASTER instrumentation on the Terra satellite using double-pass stereo pairs. [ 10 ]
The HRS instrument on SPOT 5 has acquired over 100 million square kilometers of stereo pairs.
Older methods of generating DEMs often involve interpolating digital contour maps that may have been produced by direct survey of the land surface this method is still used in mountain areas, where interferometry is not always satisfactory. Note that the contour line data or any other sampled elevation datasets (by GPS or ground survey) are not DEMs, but may be considered digital terrain models. A DEM implies that elevation is available continuously at each location in the study area.
The quality of a DEM is a measure of how accurate elevation is at each pixel (absolute accuracy) and how accurately is the morphology presented (relative accuracy). Several factors play an important role for quality of DEM-derived products:
- terrain roughness
- sampling density (elevation data collection method)
- grid resolution or pixel size algorithm
- vertical resolution
- terrain analysis algorithm
- Reference3D products include quality masks that give information on: the coastline, lake, snow, clouds, correlation etc.
What is the difference between DEM, DSM, and DTM?
DEM: As discussed above, DEM is an elevation model of Earth’s bare topography.
DSM: It is an elevation model that includes above-the-ground features, such as vegetation and man-made objects.
DTM: When data from DEM is processed further, you get DTM. Basically, DTM is DEM of much greater accuracy because its terrain data is augmented with additional information, such as contour lines obtained by land surveys.
In essence, you can call DEM a superset of both DSM and DTM.
What is terrain analysis GIS?
Read rest of the answer. Similarly, it is asked, what is terrain mapping and analysis?
Surface analysis is often referred to as terrain (elevation) analysis. In addition, surface analysis techniques can also be applied to more esoteric mapping efforts such as probability of tornados or concentration of infant mortalities in a given region.
Furthermore, what is flow direction in GIS? Flow direction determines which direction water will flow in a given cell. Based on the direction of the steepest descent in each cell, we measure flow direction. In a given grid cell, water can flow to one or more of its eight adjacent cells. Slope is the ultimate factor how water flows in this model.
Also, what is digital terrain model in GIS?
A digital terrain model (DTM) can be described as a three &ndash dimensional representation of a terrain surface consisting of X, Y, Z coordinates stored in digital form. It includes not only heights and elevations but other geographical elements and natural features such as rivers, ridge lines, etc.