scholarly journals Photogrammetric surveying forests and woodlands with UAVs: techniques for automatic removal of vegetation and digital terrain model production for hydrological applications

2019 ◽  
Vol 7 (1) ◽  
pp. 1-20
Author(s):  
Fotis Giagkas ◽  
Petros Patias ◽  
Charalampos Georgiadis
Keyword(s):  
Vegetation Type ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Aerial Images ◽  
Surface Model ◽  
Terrain Model ◽  
Vegetation Height ◽  
Digital Terrain ◽  
Dense Point ◽  
Height Model

The purpose of this study is the photogrammetric survey of a forested area using unmanned aerial vehicles (UAV), and the estimation of the digital terrain model (DTM) of the area, based on the photogrammetrically produced digital surface model (DSM). Furthermore, through the classification of the height difference between a DSM and a DTM, a vegetation height model is estimated, and a vegetation type map is produced. Finally, the generated DTM was used in a hydrological analysis study to determine its suitability compared to the usage of the DSM. The selected study area was the forest of Seih-Sou (Thessaloniki). The DTM extraction methodology applies classification and filtering of point clouds, and aims to produce a surface model including only terrain points (DTM). The method yielded a DTM that functioned satisfactorily as a basis for the hydrological analysis. Also, by classifying the DSM–DTM difference, a vegetation height model was generated. For the photogrammetric survey, 495 aerial images were used, taken by a UAV from a height of ∼200 m. A total of 44 ground control points were measured with an accuracy of 5 cm. The accuracy of the aerial triangulation was approximately 13 cm. The produced dense point cloud, counted 146 593 725 points.

scholarly journals Automated Generation of Digital Terrain Model using Point Clouds of Digital Surface Model in Forest Area

2011 ◽  
Vol 3 (5) ◽  
pp. 845-858 ◽  
Author(s):  
Kande R.M.U. Bandara ◽  
Lal Samarakoon ◽  
Rajendra P. Shrestha ◽  
Yoshikazu Kamiya
Keyword(s):  
Digital Terrain Model ◽  
Point Clouds ◽  
Forest Area ◽  
Surface Model ◽  
Digital Surface Model ◽  
Automated Generation ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals LOD2 Building Generation Experiences and Comparisons

2018 ◽  
Vol 8 (2) ◽  
pp. 59-64
Author(s):  
Iuliana Maria Pârvu ◽  
F. Remondino ◽  
E. Ozdemir
Keyword(s):  
Knowledge Transfer ◽  
Digital Terrain Model ◽  
Point Clouds ◽  
Surface Model ◽  
Ancillary Data ◽  
Terrain Model ◽  
Digital Terrain ◽  
Research Activities ◽  
Building Models ◽  
Technical Details

Abstract The VOLTA project is a RISE Marie-Curie action designed to realize Research & Innovation (R&I) among intersectoral partners to exchange knowledge, methods and workflows in the geospatial field. To accomplish its objectives, the main R&I activities of VOLTA are divided in four interlinked Work Packages with two transversal ones responsible for knowledge transfer & training as well as dissemination of the project results. The research activities and knowledge transfer are performed with a series of secondments between partners. The consortium is composed of 13 partners from academic & research institutions, industrial partners and national mapping agencies. The Romanian National Center of Cartography is part of this research project and in this article the achievements of the secondment at Bruno Kessler Foundation in Trento (Italy) are given. The main goal of the exchange was to generate level of detail - LOD2 building models in an automated manner from photogrammetric point clouds and without any ancillary data. To benchmark existing commercial solutions for the realization of LOD2 building models, we tested Building Reconstruction. This program generates LOD2 models starting from building footprints, digital terrain model (DTM) and digital surface model (DSM). The presented work examined a research and a commercial-based approach to reconstruct LOD2 building models from point clouds. The full paper will report all technical details of the work with insight analyses and comparisons.

Das aktuelle Vegetationshöhenmodell der Schweiz: spezifische Anwendungen im Waldbereich

2016 ◽  
Vol 167 (3) ◽  
pp. 128-135 ◽  
Author(s):  
Christian Ginzler ◽  
Martina L. Hobi
Keyword(s):  
Spatial Resolution ◽  
Forest Canopy ◽  
Current Model ◽  
Digital Terrain Model ◽  
National Forest Inventory ◽  
Aerial Images ◽  
Surface Model ◽  
Vegetation Height ◽  
Very High ◽  
Height Model

Current model of canopy heights in Switzerland: specific applications in forestry A national vegetation height model was calculated for Switzerland for the first time last year using digital aerial images. The ADS80 stereo aerial images, which were routinely gathered by the Swiss Federal Office of Topography (swisstopo), contain information about the height of vegetation in forests. We used the stereo aerial images to first calculate a digital surface model (DSM) with a very high spatial resolution (1 × 1 m). The DSM was then normalized to obtain the actual vegetation heights using a digital terrain model (DTM) based on laser data with the buildings masked out, and to produce a vegetation height model (VHM). Such a model could be calculated in the framework of the Swiss National Forest Inventory (NFI) with consistent methods and a very high level of detail. For covering the whole of Switzerland, we used summer aerial images from the years 2007 to 2012. The VHM reached almost nationwide coverage (98% of the country's surface area). Some areas, such as steep mountainsides or very bright glaciers, were problematic for calculating the model, and appear in it as gaps. Vegetation height information collected with this method is most useful for analyzing entire forest stands, but the data do not have a high enough spatial resolution for single-tree-based analyses. The VHM can be applied in a wide variety of ways. Here, we describe three of these: 1) generating forest masks, 2) extracting forest canopy gaps, and 3) detecting changes in the stocking of a forested area.

Automated method of а topographic plan creation based on survey from a drone

2018 ◽  
Vol 939 (9) ◽  
pp. 30-36 ◽  
Author(s):  
D.V. Beregovoi ◽  
M.G. Mustafin
Keyword(s):  
Digital Terrain Model ◽  
Field Work ◽  
Optimal Number ◽  
Reference Points ◽  
Surface Model ◽  
Speed Increase ◽  
Terrain Model ◽  
Digital Terrain ◽  
Automated Method ◽  
Dense Point

The authors show an automated method for performing the main stages of creating a topographic plan. The optimal number and location of the reference points for creation a digital terrain model using drones is determined. The necessary components of a multi-rotor helicopter are described. They are required for lifting the camera into the air and increasing the duration of the flight. On the basis of the research, a significant speed increase of the field work was achieved using effective satellite and linear-angular measurements for determination of the reference points’ coordinates and productive survey from anunmanned aerial vehicle. Algorithms forconstructing an orthophoto and a digital terrain model as well as automated filtering of the resulting dense point cloud for creating a digital surface model are presented. The high-accurate modification of the OBIA (Object-Based Image Analysis) algorithm for classification of ground objects is determined. At the end of the article, the algorithm for automated vectorization of the raster classification using the ArcGIS geoinformation software and converting of the received objects to convention for creating an electronic topographic plan is given.

scholarly journals UAV-Based Terrain Modeling under Vegetation in the Chinese Loess Plateau: A Deep Learning and Terrain Correction Ensemble Framework

2020 ◽  
Vol 12 (20) ◽  
pp. 3318 ◽  
Author(s):  
Jiaming Na ◽  
Kaikai Xue ◽  
Liyang Xiong ◽  
Guoan Tang ◽  
Hu Ding ◽  
...  
Keyword(s):  
Deep Learning ◽  
Loess Plateau ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Terrain Correction ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
Terrain Model ◽  
Vegetation Height ◽  
Digital Terrain

Accurate topographic mapping is a critical task for various environmental applications because elevation affects hydrodynamics and vegetation distributions. UAV photogrammetry is popular in terrain modelling because of its lower cost compared to laser scanning. However, this method is restricted in vegetation area with a complex terrain, due to reduced ground visibility and lack of robust and automatic filtering algorithms. To solve this problem, this work proposed an ensemble method of deep learning and terrain correction. First, image matching point cloud was generated by UAV photogrammetry. Second, vegetation points were identified based on U-net deep learning network. After that, ground elevation was corrected by estimating vegetation height to generate the digital terrain model (DTM). Two scenarios, namely, discrete and continuous vegetation areas were considered. The vegetation points in the discrete area were directly removed and then interpolated, and terrain correction was applied for the points in the continuous areas. Case studies were conducted in three different landforms in the loess plateau of China, and accuracy assessment indicated that the overall accuracy of vegetation detection was 95.0%, and the MSE (Mean Square Error) of final DTM (Digital Terrain Model) was 0.024 m.

scholarly journals Comparison of Digital Elevation Models by Visibility Analysis in Landscape

2016 ◽  
Vol 19 (2) ◽  
pp. 28-31
Author(s):  
Jozef Sedláček ◽  
Ondřej Šesták ◽  
Miroslava Sliacka
Keyword(s):  
Field Survey ◽  
Reference Model ◽  
Digital Terrain Model ◽  
Surface Model ◽  
Digital Surface Model ◽  
Visibility Analysis ◽  
Terrain Model ◽  
Digital Terrain ◽  
Model Average ◽  
Digital Elevation

Abstract The paper investigates suitability of digital surface model for visibility analysis in GIS. In experiment there were analysed viewsheds from 14 observer points calculated on digital surface model, digital terrain model and its comparison to field survey. Data sources for the investigated models were LiDAR digital terrain model and LiDAR digital surface model with vegetation distributed by the Czech Administration for Land Surveying and Cadastre. The overlay method was used for comparing accuracy of models and the reference model was LiDAR digital surface model. Average equalities in comparison with LiDAR digital terrain model, ZABAGED model and field survey were 15.5 %, 17.3% and 20.9%, respectively.

scholarly journals Application of the global SRTM and AW3D30 digital elevation models to mapping folds at cave sites

2021 ◽  
Vol 50 (1) ◽  
pp. 75-89
Author(s):  
Mark Abolins ◽  
Albert Ogden
Keyword(s):  
Cell Size ◽  
Forest Canopy ◽  
Digital Elevation Models ◽  
Digital Terrain Model ◽  
Surface Model ◽  
M Cell ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
The Mean

A novel method to map and quantitatively describe very gentle folds (limb dip <5°) at cratonic cave sites was evaluated at Snail Shell and Nanna caves, central Tennessee, USA. Elevations from the global SRTM digital terrain model (DTM) were assigned to points on late Ordovician geologic contacts, and the elevations of the points were used to interpolate 28 m cell size natural neighbor digital elevation models (DEM’s) of the contacts. The global Forest Canopy Height Dataset was subtracted from the global 28 m cell size AW3D30 digital surface model (DSM) to create a DTM, and that DTM was applied in the same way. Comparison of mean and modal strikes of the interpolated surfaces with mean and modal cave passage trend shows that many passages are sub-parallel to the trend of an anticline. WithiSn 500 m of the caves, the SRTM- and AW3D30-based interpolated surfaces have mean strikes within 8° of the mean strike of an interpolated reference surface created with a high resolution (~0.76 m cell size and 10 cm RMSE) Tennessee, USA LiDAR DTM. This evaluation shows that the SRTM- and AW3D30-based method has the potential to reveal a relationship between the trend of a fold, on one hand, and cave passages, on the other, at sites where a geologic contact varies in elevation by >35 m within an area of <12.4 km2 and the mean dip of bedding is >0.9°.

scholarly journals METHODS FOR THE UPDATE AND VERIFICATION OF FOREST SURFACE MODEL

2016 ◽  
Vol XLI-B4 ◽  
pp. 51-54
Author(s):  
M. Rybansky ◽  
M. Brenova ◽  
P. Zerzan ◽  
J. Simon ◽  
T. Mikita
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Geographic Location ◽  
Canopy Height ◽  
Aerial Photographs ◽  
Surface Model ◽  
Vegetation Growth ◽  
Terrain Model ◽  
Digital Terrain ◽  
Pulse Echo

The digital terrain model (DTM) represents the bare ground earth's surface without any objects like vegetation and buildings. In contrast to a DTM, Digital surface model (DSM) represents the earth's surface including all objects on it. The DTM mostly does not change as frequently as the DSM. The most important changes of the DSM are in the forest areas due to the vegetation growth. Using the LIDAR technology the canopy height model (CHM) is obtained by subtracting the DTM and the corresponding DSM. The DSM is calculated from the first pulse echo and DTM from the last pulse echo data. The main problem of the DSM and CHM data using is the actuality of the airborne laser scanning. <br><br> This paper describes the method of calculating the CHM and DSM data changes using the relations between the canopy height and age of trees. To get a present basic reference data model of the canopy height, the photogrammetric and trigonometric measurements of single trees were used. Comparing the heights of corresponding trees on the aerial photographs of various ages, the statistical sets of the tree growth rate were obtained. These statistical data and LIDAR data were compared with the growth curve of the spruce forest, which corresponds to a similar natural environment (soil quality, climate characteristics, geographic location, etc.) to get the updating characteristics.

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

2021 ◽  
Vol 21 (11) ◽  
pp. 3539-3562
Author(s):  
Natalie Brožová ◽  
Tommaso Baggio ◽  
Vincenzo D'Agostino ◽  
Yves Bühler ◽  
Peter Bebi
Keyword(s):  
Surface Roughness ◽  
Natural Hazard ◽  
Flow Direction ◽  
Mass Movement ◽  
Digital Terrain Model ◽  
Surface Model ◽  
European Alps ◽  
Terrain Model ◽  
Digital Terrain ◽  
Disturbed Forest

Abstract. Surface roughness influences the release of avalanches and the dynamics of rockfall, avalanches and debris flow, but it 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 photogrammetric digital surface model (DSM) with different resolutions (0.1, 0.5 and 1 m) and different moving-window areas (9, 25 and 49 m2). 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 channelised paths. We simulated avalanches on different elevation models (lidar-based) to observe a potential influence of a DSM and a digital terrain model (DTM) using the simulation tool Rapid Mass Movement Simulation (RAMMS). In this way, we accounted for the surface roughness based on a DSM instead of a DTM, which resulted in shorter simulated avalanche runouts by 16 %–27 % in the two study areas. Surface roughness above a treeline, which in comparison to the forest is not represented within the RAMMS, is therefore underestimated. We conclude that using DSM-based surface roughness in combination with DTM-based surface roughness and considering the directional roughness is promising for achieving better assessment of terrain in an alpine landscape, which might improve the natural hazard modelling.

scholarly journals PEMANFAATAN DTM HASIL FOTOGRAMETRI UAV UNTUK ESTIMASI KETINGGIAN GENANGAN AIR BANJIR HASIL DETEKSI CITRA SAR

2021 ◽  
Vol 17 (1) ◽  
pp. 39-48
Author(s):  
Hariady Indra Mantong
Keyword(s):  
Water Level ◽  
Feature Matching ◽  
Control Point ◽  
Digital Terrain Model ◽  
Accurate Method ◽  
Hydraulic Modeling ◽  
Surface Model ◽  
Terrain Model ◽  
Digital Terrain ◽  
Level Measurement

Utilization of The Unmanned Aerial Vehicle (UAV) or Drone has brought revolution in digital photogrammetry. The feature matching on surface reconstruction or Digital Surface Model (DSM) are quickly finished. However, DSM doesn’t represent itself as a part of topography, that is why DSM should be converted into Digital Terrain Model (DTM). This research is to investigate the accuracy of UAV photogrammetry’s DTM  for hydraulic modeling purpose. This study has produced 4 sets of DTMs; 2 sets of DTMs with different grid resolution which are 2 cm & 40 cm, also the 2 other sets of DTM with extra fine nature algorithm and set of filtering parameters adjustment; bulge, offset, spike and standard deviation. Every DTM are validated by Ground Control Point (GCP) from Real Time Kinematic-Different Global Positioning System (RTK-DGPS) measurement. According to the validation, the adjustment of filtering parameters is the most accurate method with Root Mean Square Error (RMSE) of 6,17 cm for 2 cm resolution; and 5,22 cm for 40 cm resolution. Next, DTM UAV is used to estimate the flood water level from Synthetic Aperture Radar (SAR) Image detection with 46 flood images on Glane and Losser area, east part of Overijssel, The Netherlands, since October 2014 to December 2017, then validated with the insitu water level measurement and resulted RMSE 6,72 cm for set of UAV DTM’s 40 cm resolution with the filtering parameters adjustment. Therefore, this DTM UAV can be used as a topography parameter in hydraulic modeling, especially at the similar flat-surface terrain where this research have been conducted.  Keywords: UAV photogrammetry, SAR detection, DTM production

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