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Projects / Programmes source: ARIS

Processing of massive geometric LIDAR data

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Research activity

Code Science Field Subfield
2.07.03  Engineering sciences and technologies  Computer science and informatics  Programming technologies - software 

Code Science Field
P170  Natural sciences and mathematics  Computer science, numerical analysis, systems, control 

Code Science Field
1.02  Natural Sciences  Computer and information sciences 
Keywords
LiDAR, point-based rendering, lossless data compression, segmentation, digital elevation model
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (18)
no. Code Name and surname Research area Role Period No. of publications
1.  11983  PhD Anton Biasizzo  Computer science and informatics  Researcher  2010 - 2013  149 
2.  04967  PhD Andrej Brodnik  Computer intensive methods and applications  Researcher  2010 - 2013  449 
3.  10075  MSc Dušan Fajfar  Mathematics  Researcher  2010 - 2013  88 
4.  21317  PhD Sebastian Krivograd  Computer science and informatics  Researcher  2010  81 
5.  29530  PhD Uroš Legat  Computer science and informatics  Junior researcher  2010 - 2012  24 
6.  21318  PhD Bogdan Lipuš  Computer science and informatics  Researcher  2010 - 2011  54 
7.  29243  PhD Domen Mongus  Computer science and informatics  Junior researcher  2010 - 2012  277 
8.  05601  PhD Franc Novak  Computer science and informatics  Researcher  2010 - 2013  316 
9.  18291  PhD Gregor Papa  Computer science and informatics  Researcher  2010 - 2013  352 
10.  22681  Miloš Pegan  Computer science and informatics  Researcher  2010 - 2013  21 
11.  17166  PhD Gregor Pipan  Interdisciplinary research  Researcher  2010 - 2013  44 
12.  15459  MSc Martin Puhar  Computer science and informatics  Researcher  2010 - 2013  64 
13.  28150  Blaž Repnik  Computer science and informatics  Researcher  2012 - 2013  32 
14.  28149  PhD Bojan Rupnik  Administrative and organisational sciences  Researcher  2012 - 2013  68 
15.  26035  PhD Denis Špelič  Computer science and informatics  Researcher  2010 - 2012  62 
16.  21555  PhD Marjan Šterk  Computer science and informatics  Researcher  2012 - 2013  69 
17.  32484  Tine Šukljan  Computer science and informatics  Researcher  2010 - 2013  5 
18.  06671  PhD Borut Žalik  Computer science and informatics  Head  2010 - 2013  850 
Organisations (5)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,664 
2.  0796  University of Maribor, Faculty of Electrical Engineering and Computer Science  Maribor  5089638003  27,536 
3.  1504  IGEA, svetovanje in storitve s področja nepremičnin, infrastrukture in prostora, d.o.o. (Slovene)  Brezovica pri Ljubljani  5336236000  296 
4.  1669  University of Primorska, Andrej Marušič Insitute  Koper  1810014007  10,776 
5.  2012  XLAB software development and consulting Ltd.  Ljubljana  1639714  322 
Abstract
Acquisition and processing of geometric data from the Earth surface are complex processes that used to be considered difficult, slow and expensive. However, modern technologies enabled development of devices capable of fast and data capturing. The focus has therefore been moved to data storage and processing. LiDAR (Light Detection and Ranging) scanners can capture up to 24 points in a square metre, with the acquisition speed as high as 200.000 points per second. The results of this are huge amounts of geometric data – 3D points with attached specific data that exceed the storage capacities of a computer system. Their storage and processing require special approaches. The development of software for huge datasets processing hardly follows capabilities of data capture devices. This implies many challenges and problems in the field of geometric data processing. In the proposed project, we deal with some of them in close cooperation with final users. These problems are represented in greater detail in continuation. The companies Igea, d.o.o., X-Lab, d.o.o, Dat-Con, d.o.o. and GeoIn, d.o.o., which partially fund the proposed project, are either data providers or distributors. The expected solutions will directly support the quality of their services. To achieve the set goals, thorough theoretical knowledge of the field, new theoretical solutions and practical experiences are necessary. Proven excellence of our previous research results and successful transfers to practice provide a good starting point. The project activities will run in three main directions, where the particular solutions will supplement each other. Visualization of geometric data represents the most natural way for results adequacy evaluation. Because of huge amounts of data, a LOD-based (level of details) approach will be used. Since we deal with unstructured data, we will focus on point-based rendering (PBR) method and graphic processors utilization. Existing PBR visualization of LiDAR data still does not reach the satisfactory quality and, therefore, improvements are extremely important from theoretical and also practical point of view. Data acquired from capture devices are stored in files. Owing to their size, archiving is exposed to enormous problems and the data transfer through internet is practically impossible. General-purpose data compression algorithms only partially facilitate this problem. The solution lies in design of domain-specific algorithms for compression of geometric data. We intend to implement data compression and decompression algorithms as streaming algorithms with prediction, also suitable for hardware implementations. Here we will rely upon the modern concepts of high-level synthesis and corresponding platforms from the field of highly efficient reconfigurable computer systems. Feature detection (segmentation) in unstructured geometric data is vital for numerous applications. Known approaches often prove inefficient and numerically intensive. In the proposed project, we intend to develop algorithms which utilize fast geometric techniques to early eliminate those data that certainly do not represent a desired feature. In this way, we will significantly reduce data amounts and enable use of known approaches on the remaining data. This will considerably improve the method efficiency. The improved visualization, domain-specific realization of data compression algorithms, their hardware implementation and innovative approaches to data segmentation algorithms design will be incorporated into a framework of user tools intended for direct practical use. The achieved theoretical results will be published in scientific publications. An important project goal is also the LiDAR data incorporation into the existing distributed geographic information systems (GIS). The accuracy and actuality of visualized data will be considerably improved and, consequently, the usability of such GIS-based applications in everyday practice will be intensified
Significance for science
In this project, key software infrastructure for LiDAR data processing was developed, including efficient archiving of LiDAR datasets enabling their transmission over the internet, its visualization and point filtering for the generation of digital terrain models. This infrastructure opens the door for numerous new researches in computer science as well as in remote sensing and environmental sciences. Additionally to obvious advantages provided by the developed data compression algorithms when considering the costs of environmental studies using LiDAR, these methods have been already implemented in hardware to support further improvements of the sensor systems. One such hardware solution was implemented by the consortium, too, while other researchers have exploited the identified structural characteristics used for data compression to improve its sampling, for example [Put13]. We have also shown that these approaches can be extended into general geometric data compression and integrated into web visualization. This enabled visual analytics of practically unlimited amounts of data, providing significant improvements for experts in various fields of environmental studies. At the same time, different data types (i.e. SAR or orthophoto images) can be considered in this way. The developed 3D graphic engine has been extended with attribute-based visualization, capable of enhancing the dimensionality of data representation by automatic colouring of features based on their geometric properties. As a case study, the microscopic images of biological cells have been visualized [Hor13]. The functional and domain extendibility offers significant advances, especially when considering recognition of geometric patterns in 3D point-clouds. Here, the scientific impacts of the project are the most remarkable. The introduced methodology has led to the development of a new class of hierarchical multi-resolution algorithms for generation of digital terrain models [Che13], currently recognised as the most efficient [Mon14]. Due to numerous studies of the Earth's surface and their importance for the safety of people and the quality of life, the effectiveness of this type of algorithms is substantial. They provide the basis for accurate monitoring of natural phenomena such as landslides, erosion due to the water, and flood simulations [Che13, Gua13, Tsa14]. At the same time, the digital terrain model can also be considered as the background when identifying objects on the Earth's surface, making the developed method a major breakthrough in the field of Earth observations [Mon14]. It may also be extended to other types of data, for example point-clouds, obtained from stereo-pair satellite images, as shown by [Tsa14]. [Che13] Chen, C., Li, Y., Li, W., Dai, H. (2013). A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing 82(1), 1-9. [Gua13] Guan, H., Li, J., Zhong, L., Yongtao, Y., & Chapman, M. (2013). Process virtualization of large-scale lidar data in a cloud computing environment. Computers & Geosciences, 60, 109-116. [Hor13] Horvat, D., Žalik, B., Rupnik, M., Mongus, D. (2013). Visualising the attributes of biological cells, based on human perception. Lecture notes in computer science, 7947. Berlin; Heidelberg: Springer, 386-399. [Mon14] Mongus, D., Lukač, N., Žalik, B. (2014). Ground and building extraction from LiDAR data based on differential morphological profiles and locally fitted surfaces. In press, 1-12. [Put13] Puttonen, E., Lehtomäki, M., Kaartinen, H., Zhu, L., Kukko, A., & Jaakkola, A. (2013). Improved sampling for terrestrial and mobile laser scanner point cloud data. Remote Sensing, 5(4), 1754-1773. [Tsa14] Tsanis, I. K., Seiradakis, K. D., Daliakopoulos, I. N., Grillakis, M. G., & Koutroulis, A. G. (2014). Assessment of GeoEye-1 stereo-pair-generated DEM in flood mapping of an ungauged basin. Journal of Hydroinformatics, 16(1).
Significance for the country
With the development of the advanced algorithms for archiving, visualization, and processing of LiDAR data, all being among the most efficient ones, and publications in the most prestigious scientific journals, significant contributions to the reputation of Slovenia and the Slovenian scientific excellence have been made. At the same time, the applicative nature of the project required to focus on transferring the research results into practice. The companies co-founding this project were regularly informed about the research results, while promoting the developed prototypes to the general public was of vital importance for the success of the project. Co-founders have recognised high commercial potential in LiDAR data as well as the developed algorithms for their processing. Thus, Dat-Con d.o.o., engaged in the development of special solutions for the terrain guarding, intensively promoted the results of the project to its partners in Asia and South America. Although the LiDAR technology is still relatively unknown in this part of the world, the initial market research showed encouraging results and further investments in promotional material have been made. XLAB d.o.o., the winner of the prestigious Silver Gazelle Slovenia and Gazelle of central Slovenia awards in 2011, already integrated individual solutions (advanced visualization, progressive compression) from this project into its advanced and fully customizable 3D geographic information system Gaea+ [Pla11]. Yet another important impact of this project is being made by Igea d.o.o., which has been for years engaged in the development of the digital cadastre and the standardized web services for GIS data access. They are planning to improve the existing 2D cadastre with the 3D functionalities provided by the LiDAR data that shall effectively make 3D digital cadastre even more important source of digital information for numerous end-users, including ministries (Ministry of agriculture and the environment, Ministry of Defence, Ministry of the Interior), the state authorities (Surveying and Mapping Authority of the Republic of Slovenia), public institutions (Slovenia forest service, Housing Fund of the Republic of Slovenia), public companies (water management, Electro-Slovenia, DARS), local communities, and private companies dealing with spatial and urban planning , biomass production, or reconstruction after disasters like landslides. By presenting the results of the project to experts on various workshops, a close links with the Surveying and Mapping Authority of the Republic of Slovenia (GURS) have been established. Benefits of the developed solutions for lossless LiDAR data compression will save them almost ninety percent of the costs associated with the storage of LiDAR data, while significantly improving their organization and the availability of data to the users. Finally, a comparative study of the efficiency of methods for generating digital terrain models has been made in cooperation with the Geodetic Institute of Slovenia, where our method proved to be the most efficient and suitable for the national project of LiDAR data acquisition in Slovenia [Mon13]. Thus, the algorithm along with the end-user application was prepared and tested in the production environment, allowing us to gain the information about the user experience. Based on this, we developed a comprehensive customer solution that will, in addition to the Geodetic Institute of Slovenia, be used by the Forest Service of the Republic of Slovenia for the planning and analysis of the transferability of forest roads. [Mon13] Mongus, D., Triglav, M., Žalik, B. (2013). Analiza samodejne metode za generiranje digitalnih modelov reliefa iz podatkov lidar na območju Slovenije, Geodetski vestnik, 57(2), 245-258. [Pla11] Alpine association of Slovenia, available on: http://www.pzs.si/vsebina.php?pid=94 [XLa14] XLab, Gaea+, available on: http://www.gaeaplus.eu/en/
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