scholarly journals Where Is the Ground? Quality Measures for the Planar Digital Terrain Model in Terrestrial Laser Scanning

2015 ◽  
pp. 343-353 ◽  
Author(s):  
Marcin Bator ◽  
Leszek J. Chmielewski ◽  
Arkadiusz Orłowski
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Terrestrial Laser Scanning ◽  
Quality Measures ◽  
Terrain Model ◽  
Digital Terrain

scholarly journals Terrestrial Laser Scanning (TLS) as a detection method of the natural river valley microtopography – case study of the Upper Biebrza

2014 ◽  
Vol 46 (4) ◽  
pp. 276-278 ◽  
Author(s):  
Marcin Brach ◽  
Jarosław Chormański
Keyword(s):  
Laser Scanning ◽  
Detection Method ◽  
Laser Scanner ◽  
Digital Terrain Model ◽  
Terrestrial Laser Scanning ◽  
River Valley ◽  
Gis Analysis ◽  
Terrain Model ◽  
Digital Terrain

Abstract Terrestrial Laser Scanning (TLS) as a detection method of the natural river valley microtopography - case study of the Upper Biebrza. This paper concerns the use of Terrestrial Laser Scanning (TLS) methods and the Geographic Information Systems (GIS) analysis to determine microtopography of a natural river valley, case study of the upper Biebrza valley. The scientific problem analyzed in this paper is a morphology of the selected segments of the valley covered by sedge ecosystems which in natural stage form a characteristic tussocks from their root systems. In order to capture the microtopography it was necessary to remove vegetation from the selected areas, and then, for a five typical location, registration of its structure using the laser scanner. As a result the point cloud was generated for each of the selected area and after GIS analysis the microtopography was obtained in form of digital terrain model (DTM). The DTM of each area represents valleys microstructure possible to obtain by use of TLS (TLS DTM), is usually not registered by the Airborne Laser Scanning (ALS), and is the main reason of inaccuracy of the DTM obtained based on ALS. The resulting TLS DTM has been processed by various filtering methods to lower the noise and fill the voids from blocking the laser beam by a tussocks. Finally, this allowed to determine the spatial structure of each measurement field.

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 TECHNIQUE OF AUTOMATIC MOBILE LASER SCANNING DATA FILTERING

2021 ◽  
Vol 26 (3) ◽  
pp. 5-19
Author(s):  
Maxim A. Altyntsev ◽  
◽  
Hamid Majid Saber Karkokli ◽  
Keyword(s):  
Laser Scanning ◽  
Single Point ◽  
Laser Scanner ◽  
Digital Terrain Model ◽  
Weather Conditions ◽  
Automatic Generation ◽  
Data Filtering ◽  
Terrain Model ◽  
Digital Terrain ◽  
Filtration Technique

The result of laser scanning is an array of laser points. The generation of a single point cloud in a given coordinate system is carried out during the registration process at the stage of preliminary field data processing. At this stage it is also often necessary to filter the data. Laser points with an erroneous position are eliminated during the data filleting. The number of erroneous laser points is determined by the of the laser scanner characteristics, surveyed area peculiarities and weather conditions. The devel-opment of methods and algorithms for filtering laser scanning data is carried out based on the analysis of the laser point spatial position and a certain set of additional characteristics, such as intensity value, echo signal, color value. The technique of mobile laser scanning data filtering for the territory of the road passing among the forest and close to individual industrial facilities and building. The main goal of the proposed filtration technique is to obtain data for automatic generation of an accurate digital terrain model. The filtration technique was developed for data acquired under the least favorable con-ditions – in wet weather. Accuracy estimation of generating digital terrain model based on filtered data was carried out.

scholarly journals Automating the creation of channel cross section data from aerial laser scanning and hydrological surveying for modeling flood events / Automatická tvorba geometrie vodních toků na základě syntézy dat z leteckého laserového skenování a hydrologického měření pro modelování povodňových událostí. j. hydrol., hydromech., 60, 2012, 4; 25 lit., 8 obr., 5 tab.

2012 ◽  
Vol 60 (4) ◽  
pp. 227-241 ◽  
Author(s):  
Radek Roub ◽  
Tomáš Hejduk ◽  
Pavel Novák
Keyword(s):  
Flow Rate ◽  
Hydrodynamic Model ◽  
Input Data ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Flood Events ◽  
Hydrodynamic Models ◽  
Terrain Model ◽  
Aerial Laser Scanning ◽  
Digital Terrain

Knowing the extent of inundation areas for individual N-year flood events, the specific flood scenarios, and having an idea about the depths and velocities in the longitudinal or transverse water course profile provided by hydrodynamic models is of key importance for protecting peoples’ lives and mitigating damage to property. Input data for creating the watercourse computational geometry are crucial for hydrodynamic models. Requirements for input data vary with respect to the hydrodynamic model used. One-dimensional (1D) hydrodynamic models in which the computing track is formed by cross-sectional profiles of the channel are characterized by lower requirements for input data. In two-dimensional (2D) hydrodynamic models, a digital terrain model is needed for the entire area studied. Financial requirements of the project increase with regard to the input data and the model used. The increase is mainly due to the high cost of the geodetic surveying of the stream channel. The paper aims at a verification and presentation of the suitability of using hydrological measurements in developing a schematization (geometry) of water courses based on topographic data gained from aerial laser scanning provided by the Czech Office for Surveying, Mapping and Cadastre. Taking into account the hydrological measurement during the schematization of the water course into the hydrodynamic model consists in the derivation of flow rate achieved at the time of data acquisition using the method of aerial laser scanning by means of hydrological analogy and in using the established flow rate values as a basis for deepening of the digital terrain model from aerial laser scanning data. Thus, the given principle helps to capture precisely the remaining part of the channel profile which is not reflected in the digital terrain model prepared by the method of aerial laser scanning and fully correct geometry is achieved for the hydrodynamic model.

scholarly journals Threat of Pollution Hotspots Reworking in River Systems: Case Study of the Ploučnice River (Czech Republic)

2019 ◽  
Vol 8 (1) ◽  
pp. 37 ◽  
Author(s):  
Jitka Elznicová ◽  
Tomáš Matys Grygar ◽  
Jan Popelka ◽  
Martin Sikora ◽  
Petr Novák ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Digital Terrain Model ◽  
Terrain Model ◽  
Non Invasive ◽  
Digital Terrain ◽  
Quality Of Water ◽  
Lateral Channel ◽  
Floodplain Development ◽  
Channel Deposits

As fluvial pollution may endanger the quality of water and solids transported by rivers, mapping and evaluation of historically polluted fluvial sediments is an urgent topic. The Ploučnice River and its floodplain were polluted by local uranium mining from 1971–1989. We have studied this river since 2013 using a combination of diverse methods, including geoinformatics, to identify pollution hotspots in floodplains and to evaluate the potential for future reworking. Archival information on pollution history and past flooding was collected to understand floodplain dynamics and pollution heterogeneity. Subsequently, a digital terrain model based on laser scanning data and data analysis were used to identify the sites with river channel shifts. Finally, non-invasive geochemical mapping was employed, using portable X-ray fluorescence and gamma spectrometers. The resulting datasets were processed with geostatistical tools. One of the main outputs of the study was a detailed map of pollution distribution in the floodplain. The results showed a relationship between polluted sediment deposition, past channel shifts and floodplain development. We found that increased concentration of pollution occurred mainly in the cut-off meanders and lateral channel deposits from the mining period, the latter in danger of reworking (reconnecting to the river) in the coming decades.

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 A novel automated method for the improvement of photogrammetric DTM accuracy in forests

2018 ◽  
Vol 142 (11-12) ◽  
pp. 576-577 ◽  
Author(s):  
Mateo Gašparović ◽  
Ivan Balenović ◽  
Ante Seletković ◽  
Anita Simic Milas
Keyword(s):  
Quercus Robur ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
Light Detection And Ranging ◽  
Mean Square ◽  
Terrain Model ◽  
Digital Terrain ◽  
Automated Method ◽  
Airborne Laser ◽  
Fraxinus Angustifolia

Digitalni model reljefa (DTM, engl. Digital Terrain Model) ima široku i važnu primjenu u mnogim djelatnostima, uključujući i šumarstvo. Međutim, precizno modeliranje terena, odnosno izrada DTM-a u šumama, bilo korištenjem terenskih metoda ili metoda daljinskih istraživanja, izazovan je i vrlo zahtjevan zadatak. U većini razvijenih zemalja svijeta, zračno lasersko skeniranje (ALS, engl. Airborne Laser Scanning) bazirano na LiDAR (engl. Light Detection and Ranging) tehnologiji trenutno predstavlja glavnu metodu za izradu DTM-a. Uslijed mogućnosti laserskog zračenja da penetrira kroz krošnje drveća, LiDAR tehnologija se pokazala kao efektivna i brza metoda za izradu DTM-a u šumskim područjima s vrlo velikom točnošću. Međutim, u mnogim zemljama svijeta, uključujući i Hrvatsku, zračno lasersko skeniranje nije u potpunosti provedeno, tj. samo su manji dijelovi zemlje pokriveni s podacima zračnog laserskog skeniranja. U tim slučajevima, DTM temeljen na stereo-fotogrametrijskoj izmjeri aerosnimaka potpomognut s terenskim podacima najčešće predstavlja glavni izvor informacija za izradu DTM-a. Poznato je da tako izrađen DTM u šumskim predjelima ima manju točnost od DTM-a dobivenog na temelju zračnog laserskog skeniranja zbog pokrivenosti terena vegetacijom. Također, u okviru nedavno provedenog istraživanja (Balenović i dr., 2018) utvrđeno je da takvi službeni fotogrametrijski digitalni podaci terena u šumskim predjelima sadrže određen broj tzv. grubih grešaka, koje mogu značajno utjecati na točnost izrađenog DTM-a. Nakon vizualnog detektiranja i manualnog uklanjanja tih pogrešaka, Balenović i dr. (2018) utvrdili su značajno poboljšanje točnosti fotogrametrijskog DTM-a. Stoga je glavni cilj ovoga rada razviti automatsku metodu za detekciju i eliminaciju vertikalnih pogrešaka u fotogrametrijskim digitalnim podacima terena te na taj način poboljšati točnost fotogrametrijskog DTM-a u nizinskim šumskim područjima Hrvatske. Ideja je razviti brzu, jednostavnu i učinkovitu metodu koja će biti primjenjiva i za druga šumska područja sličnih karakteristika, a za koja ne postoje DTM dobiven zračnim laserskim skeniranjem. Istraživanje je provedeno u nizinskim šumama na području gospodarske jedinice Jastrebarski lugovi, u neposrednoj blizini Jastrebarskog (Slika 1). Istraživanjem je obuhvaćena površina od 2.005,74 ha, na kojoj su u najvećoj mjeri zastupljene jednodobne sastojine hrasta lužnjaka (Quercus robur L.), a u ma­njoj mjeri jednodobne sastojine poljskog jasena (Fraxinus angustifolia L.) te jednodobne sastojine običnoga graba (Carpinus betulus L.). Nadmorska visina područja istraživanja kreće se u rasponu od 105 do 121 m. Fotogrametrijski DTM (DTM<sub>PHM</sub>) je izrađen iz digitalnih vektorskih podataka terena (prijelomnice, linije oblika, markantne točke terena i pravokutne mreže visinskih točaka) nabavljenih iz Državne geodetske uprave (Slika 2). Ti podaci predstavljaju nacionalni standard i jedini su dostupni podaci za izradu DTM-a u Hrvatskoj. Detaljan opis vektorskih podataka dan je u radu Balenović i dr. (2018). Prvo je iz digitalnih terenskih podataka izrađena nepravilna mreža trokuta, koja je potom linearnom interpolacijom pretvorena u rasterski DTM<sub>PHM</sub> prostorne rezolucije (veličine piksela) 0,5 m. Automatska metoda za detekciju i eliminaciju vertikalnih pogrešaka fotogrametrijskog DTM-a u nizinskim šumskim područjima razvijena je u slobodnom programskom paketu Grass GIS (Slika 3). Kombinacijom vrijednosti nagiba i tangencijalne zakrivljenosti terena rasterskog DTM<sub>PHM</sub> (Slika 4), automatskom metodom su detektirane 91 grube greške (engl. outliers). Drugim riječima, utvrđeno je da 91 točkasti vektorski objekt pogrešno prikazuje stvarnu visinu terena. Navedeni broj čini 3,2 % od ukupnog broja točkastih objekata korištenih za izradu DTM<sub>PHM</sub>-a. Nakon eliminacije detektiranih pogrešaka izrađen je novi, korigirani fotogrametrijski DTM (DTM<sub>PHMc</sub>). Za ocjenu vertikalne točnosti izvornog (DTM<sub>PHM</sub>) i korigiranog DTM-a (DTM<sub>PHMc</sub>) korišten je visoko precizni DTM dobiven zračnim laserskim skeniranjem (DTM<sub>LiD</sub>). U tu svrhu su izrađeni rasteri razlika između DTM<sub>PHM </sub>i DTM<sub>LiD</sub>, te između DTM<sub>PHMc </sub>i DTM<sub>LiD</sub>. Kako je preliminarnom analizom utvrđeno da vertikalne razlike između DTM<sub>PHM </sub>i DTM<sub>LiD</sub> nisu normalno distribuirane (Slika 5), za ocjenu točnosti su uz normalne mjere točnosti korištene i tzv. robusne mjere točnosti (Tablica 2). Dobiveni rezultati ukazuju na poboljšanje vertikalne točnosti fotogrametrijskog DTM-a primjenom razvijene automatske metode. To je posebice uočljivo na podpodručjima 2 i 3 (Slika 6 i 7) u kojima se nakon uklanjanja detektiranih grešaka, korijen srednje kvadratne pogreške (RMSE, engl. root mean square error) smanjio za 8 % odnosno 50 % (Tablica 2). Na temelju dobivenih rezultata i usporedbe s DTM<sub>LiD</sub>, može se zaključiti da predložena metoda uspješno detektira i eliminira vertikalne pogreške fotogrametrijskog DTM-a u nizinskim šumskim područjima, te slijedom toga poboljšava njegovu vertikalnu točnost.

scholarly journals Reduction Method for Mobile Laser Scanning Data

2018 ◽  
Vol 7 (7) ◽  
pp. 285 ◽  
Author(s):  
Wioleta Błaszczak-Bąk ◽  
Zoltan Koppanyi ◽  
Charles Toth
Keyword(s):  
Data Reduction ◽  
Point Cloud ◽  
Laser Scanning ◽  
Digital Terrain Model ◽  
New Approach ◽  
Terrain Model ◽  
Digital Terrain ◽  
Airborne Laser ◽  
Short Time ◽  
Mls Method

Mobile Laser Scanning (MLS) technology acquires a huge volume of data in a very short time. In many cases, it is reasonable to reduce the size of the dataset with eliminating points in such a way that the datasets, after reduction, meet specific optimization criteria. Various methods exist to decrease the size of point cloud, such as raw data reduction, Digital Terrain Model (DTM) generalization or generation of regular grid. These methods have been successfully applied on data captured from Airborne Laser Scanning (ALS) and Terrestrial Laser Scanning (TLS), however, they have not been fully analyzed on data captured by an MLS system. The paper presents our new approach, called the Optimum Single MLS Dataset method (OptD-single-MLS), which is an algorithm for MLS data reduction. The tests were carried out in two variants: (1) for raw sensory measurements and (2) for a georeferenced 3D point cloud. We found that the OptD-single-MLS method provides a good solution in both variants; therefore, the choice of the reduction variant depends only on the user.

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 The Petawawa Research Forest: Establishment of a remote sensing supersite

2019 ◽  
Vol 95 (03) ◽  
pp. 149-156 ◽  
Author(s):  
Joanne C. White ◽  
Hao Chen ◽  
Murray E. Woods ◽  
Brian Low ◽  
Sasha Nasonova
Keyword(s):  
Remote Sensing ◽  
Laser Scanning ◽  
New Technologies ◽  
Open Data ◽  
Digital Terrain Model ◽  
Lessons Learned ◽  
Remotely Sensed Data ◽  
The Public ◽  
Terrain Model ◽  
Digital Terrain

The pace of technological change in forest inventory and monitoring over the past 50 years has been remarkable, largely asa result of the increased availability of various forms of remotely sensed data. Benchmarking sites, with the requisite refer-ence and baseline data for evaluating the capacities of new technologies, algorithms, and approaches, can be extremely valu-able for sparking innovation, as well as for enabling transparent and scientifically sound assessments of technologies, newdata streams, and associated information outcomes. Herein we describe the establishment of a remote sensing supersite atthe Petawawa Research Forest (PRF) in southern Ontario, Canada, and summarize the open access datasets that have beencompiled and made available to the public. The PRF is approximately 10 000 ha in size and represents a complex assemblageof tree species and forest structures. More than 1900 data records, including multiple airborne laser scanning datasets andassociated derivatives (i.e., digital terrain model, canopy height model), airborne imagery, satellite remote sensing timeseries, and ground plot data, among others, have been made openly available for download from Canada’s National ForestInformation System. We identify issues and present opportunities associated with the establishment of a remote sensingsupersite at the PRF, as well as share some of the lessons learned to foster the establishment and open data sharing for othernational and international remote sensing supersites. The PRF supersite can be accessed from the following link: https://opendata.nfis.org/mapserver/PRF.html .

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