scholarly journals DTM generation in forest regions from satellite stereo imagery

2014 ◽  
Vol XL-1 ◽  
pp. 401-405 ◽  
Author(s):  
J. Tian ◽  
T. Krauss ◽  
P. Reinartz
Keyword(s):  
Extraction Method ◽  
Laser Scanning ◽  
Single Channel ◽  
Median Filter ◽  
Digital Terrain Model ◽  
Classification Method ◽  
Surface Model ◽  
Probability Maps ◽  
Forest Regions ◽  
Stereo Imagery

Satellite stereo imagery is becoming a popular data source for derivation of height information. Many new Digital Surface Model (DSM) generation and evaluation methods have been proposed based on these data. A novel Digital Terrain Model (DTM) extraction method based on the DSM from satellite stereo imagery is proposed in this paper. Instead of directly filtering the DSM, firstly a single channel based classification method is proposed. In this step, no multi-spectral information is used, because for some stereo sensors, like Cartosat-1, only panchromatic channels are available. The proposed classification method adopts the random forests method to get initial probability maps of the four main classes in forest regions (high-forest, low-forest, ground, and buildings). To cover the pepper and salt effect of this pixel based classification method, the probability maps are further filtered based on the adaptive Wiener filtering. Then a cube-based greedy strategy is applied in generating the final classification map from these refined probability maps. Secondly, the height distances between neighboring regions are calculated along the boundary regions. These height distances can be used to estimate the relative region heights. Thirdly, the DTM is extracted by subtracting these relative region heights from the DSM in the order of: buildings &ndash; low forest &ndash; high forest. In the end, the extracted DTM is further smoothed using median filter. <br><br> The proposed DTM extraction method is finally tested on satellite stereo imagery captured by Cartosat-1. Quality evaluation is performed by comparing the extracted DTMs to a reference DTM, which is generated from the last return airborne laser scanning point cloud.

scholarly journals AUTOMATIC ROOFTOP EXTRACTION IN STEREO IMAGERY USING DISTANCE AND BUILDING SHAPE REGULARIZED LEVEL SET EVOLUTION

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 393-397 ◽  
Author(s):  
J. Tian ◽  
T. Krauß ◽  
P. d’Angelo
Keyword(s):  
Level Set ◽  
Active Contour Model ◽  
Digital Terrain Model ◽  
Surface Model ◽  
Building Shape ◽  
Fitting Procedure ◽  
Level Set Function ◽  
Stereo Imagery ◽  
3D Information ◽  
High Level

Automatic rooftop extraction is one of the most challenging problems in remote sensing image analysis. Classical 2D image processing techniques are expensive due to the high amount of features required to locate buildings. This problem can be avoided when 3D information is available. In this paper, we show how to fuse the spectral and height information of stereo imagery to achieve an efficient and robust rooftop extraction. In the first step, the digital terrain model (DTM) and in turn the normalized digital surface model (nDSM) is generated by using a newly step-edge approach. In the second step, the initial building locations and rooftop boundaries are derived by removing the low-level pixels and high-level pixels with higher probability to be trees and shadows. This boundary is then served as the initial level set function, which is further refined to fit the best possible boundaries through distance regularized level-set curve evolution. During the fitting procedure, the edge-based active contour model is adopted and implemented by using the edges indicators extracted from panchromatic image. The performance of the proposed approach is tested by using the WorldView-2 satellite data captured over Munich.

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 MODELING CITIES FOR 3D_GIS PURPOSES

2018 ◽  
Vol XLII-4 ◽  
pp. 135-142
Author(s):  
E. G. V. de Jesus ◽  
A. L. de Amorim ◽  
N. J. Groetelaars ◽  
V. O. Fernandes
Keyword(s):  
Data Model ◽  
Geometric Modeling ◽  
Laser Scanning ◽  
Semantic Representation ◽  
Digital Terrain Model ◽  
Surface Model ◽  
Geography Markup Language ◽  
Terrain Model ◽  
Digital Terrain ◽  
First Results

<p><strong>Abstract.</strong> 3D Geographic Information Systems (3D GIS) are systems that are capable of making spatial analyses that consider the tridimentional and semantic representation of objects. These systems make these analyses through its planialtimetric coordinates. The City Geography Markup Language (CityGML) is used for the representation of cities and urban applications. The CityGML is an international standardized data model based on XML used to store and exchange information through 3D representation of cities. This standardized data model has 5 Levels of Detail – LOD, varying from LOD 0 (least detailed) to 4 (most detailed). The main challenges for the implementation of these systems refer to the techniques used for obtaining data and the data format, and also all the software used in the geometric modeling of the urban model. The data related to the buildings were manipulated with the QGIS software in this study. This made it possible to obtain the height of the buildings by the elevation difference between the Digital Surface Model and the Digital Terrain Model. This paper presents and discusses the first results of the geometric modeling made in the campus of the Federal University of Bahia (UFBA), by using airborne laser scanning data, integrating QGIS, Rhinoceros and CityGML.</p>

scholarly journals Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling

2018 ◽  
Vol 18 (2) ◽  
pp. 583-597 ◽  
Author(s):  
Ákos Török ◽  
Árpád Barsi ◽  
Gyula Bögöly ◽  
Tamás Lovas ◽  
Árpád Somogyi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Cross Sections ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Field Measurements ◽  
Satellite System ◽  
Surface Model ◽  
Rockfall Hazard ◽  
Terrain Model ◽  
Remote Sensing Techniques

Abstract. Steep, hardly accessible cliffs of rhyolite tuff in NE Hungary are prone to rockfalls, endangering visitors of a castle. Remote sensing techniques were employed to obtain data on terrain morphology and to provide slope geometry for assessing the stability of these rock walls. A RPAS (Remotely Piloted Aircraft System) was used to collect images which were processed by Pix4D mapper (structure from motion technology) to generate a point cloud and mesh. The georeferencing was made by Global Navigation Satellite System (GNSS) with the use of seven ground control points. The obtained digital surface model (DSM) was processed (vegetation removal) and the derived digital terrain model (DTM) allowed cross sections to be drawn and a joint system to be detected. Joint and discontinuity system was also verified by field measurements. On-site tests as well as laboratory tests provided additional engineering geological data for slope modelling. Stability of cliffs was assessed by 2-D FEM (finite element method). Global analyses of cross sections show that weak intercalating tuff layers may serve as potential slip surfaces. However, at present the greatest hazard is related to planar failure along ENE–WSW joints and to wedge failure. The paper demonstrates that RPAS is a rapid and useful tool for generating a reliable terrain model of hardly accessible cliff faces. It also emphasizes the efficiency of RPAS in rockfall hazard assessment in comparison with other remote sensing techniques such as terrestrial laser scanning (TLS).

scholarly journals Synthesis of Leaf-on and Leaf-off Unmanned Aerial Vehicle (UAV) Stereo Imagery for the Inventory of Aboveground Biomass of Deciduous Forests

2019 ◽  
Vol 11 (7) ◽  
pp. 889 ◽  
Author(s):  
Wenjian Ni ◽  
Jiachen Dong ◽  
Guoqing Sun ◽  
Zhiyu Zhang ◽  
Yong Pang ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Point Cloud ◽  
Forest Canopy ◽  
Deciduous Forest ◽  
Ground Surface ◽  
Digital Terrain Model ◽  
Canopy Height ◽  
Surface Model ◽  
Lidar Data ◽  
Stereo Imagery

Applications of stereo imagery acquired by cameras onboard unmanned aerial vehicles (UAVs) as practical forest inventory tools are hindered by the unavailability of ground surface elevation. It is still a challenging issue to remove the elevation of ground surface in leaf-on stereo imagery to extract forest canopy height without the help of lidar data. This study proposed a method for the extraction of forest canopy height through the synthesis of UAV stereo imagery of leaf-on and leaf-off, and further demonstrated that the extracted forest canopy height could be used for the inventory of deciduous forest aboveground biomass (AGB). The points cloud of the leaf-on and leaf-off stereo imagery was firstly extracted by an algorithm of structure from motion (SFM) using the same ground control points (GCP). The digital surface model (DSM) was produced by rasterizing the point cloud of UAV leaf-on. The point cloud of UAV leaf-off was processed by iterative median filtering to remove vegetation points, and the digital terrain model (DTM) was generated by the rasterization of the filtered point cloud. The mean canopy height model (MCHM) was derived from the DSM subtracted by the DTM (i.e., DSM-DTM). Forest AGB maps were generated using models developed based on the MCHM and sampling plots of forest AGB and were evaluated by those of lidar. Results showed that forest AGB maps from UAV stereo imagery were highly correlated with those from lidar data with R2 higher than 0.94 and RMSE lower than 10.0 Mg/ha (i.e., relative RMSE 18.8%). These results demonstrated that UAV stereo imagery could be used as a practical inventory tool for deciduous forest AGB.

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. &lt;br&gt;&lt;br&gt; 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 Archaeological Surveying of Subarctic and Arctic Landscapes: Comparing the Performance of Airborne Laser Scanning and Remote Sensing Image Data

2021 ◽  
Vol 13 (4) ◽  
pp. 1917
Author(s):  
Alma Elizabeth Thuestad ◽  
Ole Risbøl ◽  
Jan Ingolf Kleppe ◽  
Stine Barlindhaug ◽  
Elin Rose Myrvoll
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Image Data ◽  
Remote Sensing Image ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Detection Rates ◽  
Airborne Laser ◽  
Pros And Cons

What can remote sensing contribute to archaeological surveying in subarctic and arctic landscapes? The pros and cons of remote sensing data vary as do areas of utilization and methodological approaches. We assessed the applicability of remote sensing for archaeological surveying of northern landscapes using airborne laser scanning (LiDAR) and satellite and aerial images to map archaeological features as a basis for (a) assessing the pros and cons of the different approaches and (b) assessing the potential detection rate of remote sensing. Interpretation of images and a LiDAR-based bare-earth digital terrain model (DTM) was based on visual analyses aided by processing and visualizing techniques. 368 features were identified in the aerial images, 437 in the satellite images and 1186 in the DTM. LiDAR yielded the better result, especially for hunting pits. Image data proved suitable for dwellings and settlement sites. Feature characteristics proved a key factor for detectability, both in LiDAR and image data. This study has shown that LiDAR and remote sensing image data are highly applicable for archaeological surveying in northern landscapes. It showed that a multi-sensor approach contributes to high detection rates. Our results have improved the inventory of archaeological sites in a non-destructive and minimally invasive manner.

scholarly journals DTM-based analysis of the spatial distribution of topolineaments

2020 ◽  
Vol 12 (1) ◽  
pp. 1185-1199
Author(s):  
Mirosław Kamiński
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Research Area ◽  
Tectonic Structures ◽  
Empirical Bayesian ◽  
Scanning Method ◽  
Empirical Bayesian Kriging ◽  
Terrain Model ◽  
Digital Terrain ◽  
Airborne Laser

AbstractThe research area is located on the boundary between two Paleozoic structural units: the Radom–Kraśnik Block and the Mazovian–Lublin Basin in the southeastern Poland. The tectonic structures are separated by the Ursynów–Kazimierz Dolny fault zone. The digital terrain model obtained by the ALS (Airborne Laser Scanning) method was used. Classification and filtration of an elevation point cloud were performed. Then, from the elevation points representing only surfaces, a digital terrain model was generated. The model was used to visually interpret the course of topolineaments and their automatic extraction from DTM. Two topolineament systems, trending NE–SW and NW–SE, were interpreted. Using the kernel density algorithm, topolineament density models were generated. Using the Empirical Bayesian Kriging, a thickness model of quaternary deposits was generated. A relationship was observed between the course of topolineaments and the distribution and thickness of Quaternary formations. The topolineaments were compared with fault directions marked on tectonic maps of the Paleozoic and Mesozoic. Data validation showed consistency between topolineaments and tectonic faults. The obtained results are encouraging for further research.

scholarly journals Spatio-Temporal Change Monitoring of Outside Manure Piles Using Unmanned Aerial Vehicle Images

Drones ◽  
2020 ◽  
Vol 5 (1) ◽  
pp. 1
Author(s):  
Geonung Park ◽  
Kyunghun Park ◽  
Bonggeun Song
Keyword(s):  
Point Source ◽  
Laser Scanning ◽  
Image Data ◽  
Surface Model ◽  
Point Source Pollution ◽  
Efficient Management ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Agricultural Areas ◽  
Water Quality Deterioration

Water quality deterioration due to outdoor loading of livestock manure requires efficient management of outside manure piles (OMPs). This study was designed to investigate OMPs using unmanned aerial vehicles (UAVs) for efficient management of non-point source pollution in agricultural areas. A UAV was used to acquire image data, and the distribution and cover installation status of OMPs were identified through ortho-images; the volumes of OMP were calculated using digital surface model (DSM). UAV- and terrestrial laser scanning (TLS)-derived DSMs were compared for identifying the accuracy of calculated volumes. The average volume accuracy was 92.45%. From April to October, excluding July, the monthly average volumes of OMPs in the study site ranged from 64.89 m3 to 149.69 m3. Among the 28 OMPs investigated, 18 were located near streams or agricultural waterways. Establishing priority management areas among the OMP sites distributed in a basin is possible using spatial analysis, and it is expected that the application of UAV technology will contribute to the efficient management of OMPs and other non-point source pollutants.

scholarly journals Segmentation and Multi-Scale Convolutional Neural Network-Based Classification of Airborne Laser Scanner Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3347 ◽  
Author(s):  
Zhishuang Yang ◽  
Bo Tan ◽  
Huikun Pei ◽  
Wanshou Jiang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Region Growing ◽  
Point Clouds ◽  
Classification Method ◽  
Multi Scale ◽  
Airborne Laser

The classification of point clouds is a basic task in airborne laser scanning (ALS) point cloud processing. It is quite a challenge when facing complex observed scenes and irregular point distributions. In order to reduce the computational burden of the point-based classification method and improve the classification accuracy, we present a segmentation and multi-scale convolutional neural network-based classification method. Firstly, a three-step region-growing segmentation method was proposed to reduce both under-segmentation and over-segmentation. Then, a feature image generation method was used to transform the 3D neighborhood features of a point into a 2D image. Finally, feature images were treated as the input of a multi-scale convolutional neural network for training and testing tasks. In order to obtain performance comparisons with existing approaches, we evaluated our framework using the International Society for Photogrammetry and Remote Sensing Working Groups II/4 (ISPRS WG II/4) 3D labeling benchmark tests. The experiment result, which achieved 84.9% overall accuracy and 69.2% of average F1 scores, has a satisfactory performance over all participating approaches analyzed.

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