scholarly journals NEW DTM EXTRACTION APPROACH FROM AIRBORNE IMAGES DERIVED DSM

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 75-82 ◽  
Author(s):  
Y. A. Mousa ◽  
P. Helmholz ◽  
D. Belton
Keyword(s):  
Interpolation Method ◽  
Digital Terrain Model ◽  
Window Size ◽  
Group Iii ◽  
Terrain Model ◽  
Digital Terrain ◽  
Surface Models ◽  
Extraction Algorithm ◽  
Ground Point

In this work, a new filtering approach is proposed for a fully automatic Digital Terrain Model (DTM) extraction from very high resolution airborne images derived Digital Surface Models (DSMs). Our approach represents an enhancement of the existing DTM extraction algorithm <i>Multi-directional and Slope Dependent (MSD)</i> by proposing parameters that are more reliable for the selection of ground pixels and the pixelwise classification. To achieve this, four main steps are implemented: Firstly, 8 well-distributed scanlines are used to search for minima as a ground point within a pre-defined filtering window size. These selected ground points are stored with their positions on a 2D surface to create a network of ground points. Then, an initial DTM is created using an interpolation method to fill the gaps in the 2D surface. Afterwards, a pixel to pixel comparison between the initial DTM and the original DSM is performed utilising pixelwise classification of ground and non-ground pixels by applying a vertical height threshold. Finally, the pixels classified as non-ground are removed and the remaining holes are filled. The approach is evaluated using the Vaihingen benchmark dataset provided by the ISPRS working group III/4. The evaluation includes the comparison of our approach, denoted as Network of Ground Points (NGPs) algorithm, with the DTM created based on MSD as well as a reference DTM generated from LiDAR data. The results show that our proposed approach over performs the MSD approach.

scholarly journals Možnosti srovnávací analýzy plužiny zaniklých středověkých vsí. Vypovídací hodnota vybraných lokalit a role digitálního modelu reliéfu z dat leteckého laserového skenování

2021 ◽  
Vol 6 (1-2) ◽  
pp. 177-196
Author(s):  
Ondřej Malina ◽  
Lukáš Holata ◽  
Jindřich Plzák
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Specific Data ◽  
Archaeological Heritage ◽  
Terrain Model ◽  
Digital Terrain ◽  
Airborne Laser ◽  
Data Source ◽  
Definition Of

The paper deals with the plowlands of deserted medieval villages (DMVs) representing a specific data source of medieval settlement research. Its basic priorities are based on the needs of archaeological heritage protection for a better definition of DMVs’ hinterlands, which are significantly less distinguishable in comparison with villages’ intravilans. At the same time, not much attention was paid to this area, even in known or well-surveyed sites. These issues are important especially in the context of what exactly we are looking for within the DMVs, how we define it and where we can find the best examples worthy of protection or further study. The basis of the presented work is the processing of a digital terrain model derived from airborne laser scanning data. The primary procedure consists of the ALS data processing into a DEM, its subsequent visualization, and classification of objects in DMVs’ hinterlands, which is further supplemented by selected examples of field verification. The informative value of the hinterlands is also discussed on the example of several differently preserved sites.

scholarly journals Aerial Laser Scanning Data as a Source of Terrain Modeling in a Fluvial Environment: Biasing Factors of Terrain Height Accuracy

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2063 ◽  
Author(s):  
Zsuzsanna Szabó ◽  
Csaba Albert Tóth ◽  
Imre Holb ◽  
Szilárd Szabó
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Threshold Value ◽  
Noise Filtering ◽  
Terrain Model ◽  
Digital Terrain ◽  
Natural Neighbor ◽  
Wide Range ◽  
Ground Point

Airborne light detection and ranging (LiDAR) scanning is a commonly used technology for representing the topographic terrain. As LiDAR point clouds include all surface features present in the terrain, one of the key elements for generating a digital terrain model (DTM) is the separation of the ground points. In this study, we intended to reveal the efficiency of different denoising approaches and an easy-to-use ground point classification technique in a floodplain with fluvial forms. We analyzed a point cloud from the perspective of the efficiency of noise reduction, parametrizing a ground point classifier (cloth simulation filter, CSF), interpolation methods and resolutions. Noise filtering resulted a wide range of point numbers in the models, and the number of points had moderate correlation with the mean accuracies (r = −0.65, p < 0.05), indicating that greater numbers of points had larger errors. The smallest differences belonged to the neighborhood-based noise filtering and the larger cloth size (5) and the smaller threshold value (0.2). The most accurate model was generated with the natural neighbor interpolation with the cloth size of 5 and the threshold of 0.2. These results can serve as a guide for researchers using point clouds when considering the steps of data preparation, classification, or interpolation in a flat terrain.

Countrywide surface models from historical panchromatic and true color stereo imagery – a retrospective analysis of forest structures in Switzerland

2020 ◽  
Author(s):  
Christian Ginzler ◽  
Mauro Marty ◽  
Lars T. Waser
Keyword(s):  
Forest Inventory ◽  
Digital Terrain Model ◽  
National Forest Inventory ◽  
Aerial Images ◽  
National Forest ◽  
Terrain Model ◽  
Digital Terrain ◽  
Surface Models ◽  
Stereo Imagery ◽  
True Color

&lt;p&gt;&lt;strong&gt;Countrywide surface models from historical panchromatic and true color stereo imagery &amp;#8211; a retrospective analysis of forest structures in Switzerland&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Mauro Marty&lt;sup&gt;1&lt;/sup&gt;, Lars T. Waser&lt;sup&gt;1&lt;/sup&gt;, Christian Ginzler&lt;sup&gt;1&lt;/sup&gt;&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;sup&gt;1&lt;/sup&gt; Swiss Federal Institute for Forest, Snow and Landscape Research WSL, &lt;br&gt;Z&amp;#252;rcherstrasse 111, CH - 8903 Birmensdorf, Switzerland&lt;/p&gt;&lt;p&gt;Remote sensing methods allow the acquisition of 3D structures of forests over large areas. Active systems, such as Airborne Laser Scanning (ALS) and Synthetic Aperture Radar (SAR) and passive systems, such as multispectral sensors, have been established to acquire 3D and 2.5D data of the earth's surface. Nationwide calculations of surface models with photogrammetric methods from digital stereo aerial images or ALS data are already in operation in some countries (e.g. Switzerland, Austria, some German states).&lt;/p&gt;&lt;p&gt;The availability of historical stereo aerial images allows the calculation of digital surface models from the past using photogrammetric methods. We present a workflow with which we have calculated nationwide surface models for Switzerland for the 1980s, 1990s and 2000s. Current surface models are available from the National Forest Inventory (LFI) Switzerland.&lt;/p&gt;&lt;p&gt;In the context of the Swiss land use and land cover statistics, the Federal Office of Topography (swisstopo) scanned and oriented the analogue black and white stereo aerial photographs with a mean scale of ~1:30'000 of the nationwide flights of 1979 - 84 and1993 - 1997 with 14 &amp;#181;m. The true colour image data from 1998 &amp;#8211; 2007 were scanned for the production of the orthoimages swissimage by swisstopo. All these data &amp;#8211; the scanned images and the orientation parameters - are also available to the National Forest Inventory (NFI). Within the framework of the NFI, we developed a highly automated workflow to generate digital surface models (DSMs) from many thousands of overlapping frame images covering the whole country. In total, more than 25'000 individual stereo models were processed to nationwide surface models. For their normalization, the digital terrain model of Switzerland 'swissAlti3D' was used. As the image orientation in some areas showed high vertical inaccuracies, corrections had to be made. Data from the Swiss land use and land cover statistics were used for this purpose. At places with constant surface cover since the 1980s (e.g. grassland), correction grids were calculated using the digital terrain model and applied to the surface models.&lt;/p&gt;&lt;p&gt;The results are new data sets on the 2.5D surface of Switzerland from the 1980s, 1990s and 2000s with a high spatial resolution of 1 m. It can be stated that the completeness of the image correlation in forested areas was quite satisfactory. In open areas with agricultural land, however, the matching points were often reduced to the road network, as the meadows and fields in the scanned SW stereo aerial images had very little texture.&lt;/p&gt;&lt;p&gt;This new historical, nationwide data on the horizontal and vertical structure in forests now allows their analysis of changes over the last 40 years.&lt;/p&gt;

scholarly journals PREPROCESSING OF SATELLITE DATA FOR URBAN OBJECT EXTRACTION

2015 ◽  
Vol XL-3/W2 ◽  
pp. 115-120 ◽  
Author(s):  
T. Krauß
Keyword(s):  
Digital Terrain Model ◽  
Stereo Pair ◽  
Spectral Classification ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
Elevation Model ◽  
Processing Steps

Very high resolution (VHR) DSMs (digital surface models) derived from stereo- or multi-stereo images from current VHR satellites like WorldView-2 or Pléiades can be produced up to the ground sampling distance (GSD) of the sensors in the range of 50 cm to 1 m. From such DSMs the digital terrain model (DTM) representing the ground and also a so called nDEM (normalized digital elevation model) describing the height of objects above the ground can be derived. In parallel these sensors deliver multispectral imagery which can be used for a spectral classification of the imagery. Fusion of the multispectral classification and the nDEM allows a simple classification and detection of urban objects. In further processing steps these detected urban objects can be modeled and exported in a suitable description language like CityGML. In this work we present the pre-processing steps up to the classification and detection of the urban objects. The modeling is not part of this work. The pre-processing steps described here cover briefly the coregistration of the input images and the generation of the DSM. In more detail the improvement of the DSM, the extraction of the DTM and nDEM, the multispectral classification and the object detection and extraction are explained. The methods described are applied to two test regions from two satellites: First the center of Munich acquired by WorldView-2 and second the center of Melbourne acquired by Pl´eiades. From both acquisitions a stereo-pair from the panchromatic bands is used for creation of the DSM and the pan-sharpened multispectral images are used for spectral classification. Finally the quality of the detected urban objects is discussed.

scholarly journals Digital Modeling Phenomenon Of Surface Ground Movement

2016 ◽  
Vol 73 (2) ◽  
pp. 342
Author(s):  
Ioan Voina ◽  
Maricel Palamariu ◽  
Iohan Neuner ◽  
Tudor Salagean ◽  
Dumitru Onose ◽  
...  
Keyword(s):  
Land Surface ◽  
Interpolation Method ◽  
Digital Terrain Model ◽  
Industrial Applications ◽  
Ground Movement ◽  
Terrain Model ◽  
Software Applications ◽  
Specialized Software ◽  
Digital Terrain ◽  
Work Area

With the development of specialized software applications it was possible to approach and resolve complex problems concerning automating and process optimization for which are being used field data. Computerized representation of the shape and dimensions of the Earth requires a detailed mathematical modeling, known as "digital terrain model". The paper aims to present the digital terrain model of Vulcan mining, Hunedoara County, Romania. Modeling consists of a set of mathematical equations that define in detail the surface of Earth and has an approximate surface rigorously and mathematical, that calculated the land area. Therefore, the digital terrain model means a digital representation of the earth's surface through a mathematical model that approximates the land surface modeling, which can be used in various civil and industrial applications in. To achieve the digital terrain model of data recorded using linear and nonlinear interpolation method based on point survey which highlights the natural surface studied. Given the complexity of this work it is absolutely necessary to know in detail of all topographic elements of work area, without the actions to be undertaken to project and manipulate would not be possible. To achieve digital terrain model, within a specialized software were set appropriate parameters required to achieve this case study. After performing all steps we obtained digital terrain model of Vulcan Mine. Digital terrain model is the complex product, which has characteristics that are equivalent to the specialists that use satellite images and information stored in a digital model, this is easier to use.

A Self-interpolation Method for Digital Terrain Model Generation

2021 ◽  
pp. 352-363
Author(s):  
Leonardo Ramos Emmendorfer ◽  
Isadora Bicho Emmendorfer ◽  
Luis Pedro Melo de Almeida ◽  
Deivid Cristian Leal Alves ◽  
Jorge Arigony Neto
Keyword(s):  
Interpolation Method ◽  
Digital Terrain Model ◽  
Model Generation ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Mapping with Pléiades—End-to-End Workflow

2019 ◽  
Vol 11 (17) ◽  
pp. 2052 ◽  
Author(s):  
Roland Perko ◽  
Hannes Raggam ◽  
Peter M. Roth
Keyword(s):  
Digital Terrain Model ◽  
Building Blocks ◽  
Surface Model ◽  
Data Sets ◽  
3D Mapping ◽  
Digital Surface Model ◽  
Terrain Model ◽  
Digital Terrain ◽  
Surface Models ◽  
End To End

In this work, we introduce an end-to-end workflow for very high-resolution satellite-based mapping, building the basis for important 3D mapping products: (1) digital surface model, (2) digital terrain model, (3) normalized digital surface model and (4) ortho-rectified image mosaic. In particular, we describe all underlying principles for satellite-based 3D mapping and propose methods that extract these products from multi-view stereo satellite imagery. Our workflow is demonstrated for the Pléiades satellite constellation, however, the applied building blocks are more general and thus also applicable for different setups. Besides introducing the overall end-to-end workflow, we need also to tackle single building blocks: optimization of sensor models represented by rational polynomials, epipolar rectification, image matching, spatial point intersection, data fusion, digital terrain model derivation, ortho rectification and ortho mosaicing. For each of these steps, extensions to the state-of-the-art are proposed and discussed in detail. In addition, a novel approach for terrain model generation is introduced. The second aim of the study is a detailed assessment of the resulting output products. Thus, a variety of data sets showing different acquisition scenarios are gathered, allover comprising 24 Pléiades images. First, the accuracies of the 2D and 3D geo-location are analyzed. Second, surface and terrain models are evaluated, including a critical look on the underlying error metrics and discussing the differences of single stereo, tri-stereo and multi-view data sets. Overall, 3D accuracies in the range of 0 . 2 to 0 . 3 m in planimetry and 0 . 2 to 0 . 4 m in height are achieved w.r.t. ground control points. Retrieved surface models show normalized median absolute deviations around 0 . 9 m in comparison to reference LiDAR data. Multi-view stereo outperforms single stereo in terms of accuracy and completeness of the resulting surface models.

scholarly journals Multiscale analysis of surface roughness for the improvement of natural hazard modelling

2021 ◽  
Author(s):  
Natalie Brožová ◽  
Tommaso Baggio ◽  
Vincenzo D'Agostino ◽  
Yves Bühler ◽  
Peter Bebi
Keyword(s):  
Surface Roughness ◽  
Natural Hazard ◽  
Flow Direction ◽  
Digital Terrain Model ◽  
European Alps ◽  
Treeline Ecotone ◽  
Terrain Model ◽  
Digital Terrain ◽  
Surface Models ◽  
Disturbed Forest

Abstract. Surface roughness influences the release of avalanches and the dynamics of rockfall, avalanches and debris flow, but is often not objectively implemented in natural hazard modelling. For two study areas, a treeline ecotone and a windthrow disturbed forest landscape of the European Alps, we tested seven roughness algorithms using a digital surface models (DSM) with different resolutions (0.1, 0.5 and 1 m) and different moving window areas (9 m−2, 25 m−2 and 49 m−2). The vector ruggedness measure roughness algorithm performed best overall in distinguishing between roughness categories relevant for natural hazard modelling (including shrub forest, high forest, windthrow, snow and rocky land-cover). The results with 1 m resolution were found to be suitable to distinguish between the roughness categories of interest, and the performance did not increase with higher resolution. In order to improve the roughness calculation along the hazard flow direction, we tested a directional roughness approach that improved the reliability of the surface roughness computation in channelized paths. We simulated avalanches on a different elevation models to observe a potential influence of a DSM and a digital terrain model (DTM). Accounting for surface roughness based on a DSM instead of a DTM resulted not only in clearly higher roughness values of forest and shrub vegetation, but also in longer simulated avalanche runouts by 16–27 % in the two study areas. We conclude that directional roughness is promising for achieving better assessments of terrain topography in alpine landscapes and that applying an approach using DSM-based surface roughness could improve natural hazard modelling.

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