Mobile Laser Scanning – System development, performance and applications

Osajulkaisut: Publication 1: Antero Kukko, Sanna Kaasalainen, and Paula Litkey. 2008. Effect of incidence angle on laser scanner intensity and surface data. Applied Optics, volume 47, number 7, pages 986-992. doi:10.1364/AO.47.000986 Publication 2: Antero Kukko and Juha Hyyppä. 2009. Small-footprint laser scanning simulator for system validation, error assessment, and algorithm development. Photogrammetric Engineering and Remote Sensing, volume 75, number 9, pages 1177-1189. Publication 3: Antero Kukko, Constantin-Octavian Andrei, Veli-Matti Salminen, Harri Kaartinen, Yuwei Chen, Petri Rönnholm, Hannu Hyyppä, Juha Hyyppä, Ruizhi Chen, Henrik Haggrén, Iisakki Kosonen, and Karel Čapek. 2007. Road environment mapping system of the Finnish Geodetic Institute - FGI ROAMER -. In: Petri Rönnholm, Hannu Hyyppä, and Juha Hyyppä (editors). Proceedings of the ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007. Espoo, Finland. 12-14 September 2007. International Society for Photogrammetry and Remote Sensing. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, volume 36, part 3 / W52, pages 241-247. ISSN 1682-1777. Publication 4: Antero Kukko, Harri Kaartinen, Juha Hyyppä, and Yuwei Chen. 2012. Multiplatform mobile laser scanning: Usability and performance. Sensors, volume 12, number 9, pages 11712-11733. doi:10.3390/s120911712 Publication 5: Harri Kaartinen, Juha Hyyppä, Antero Kukko, Anttoni Jaakkola, and Hannu Hyyppä. 2012. Benchmarking the performance of mobile laser scanning systems using a permanent test field. Sensors, volume 12, number 9, pages 12814-12835. doi:10.3390/s120912814 Publication 6: P. Alho, A. Kukko, H. Hyyppä, H. Kaartinen, J. Hyyppä, and A. Jaakkola. 2009. Application of boat-based laser scanning for river survey. Earth Surface Processes and Landforms, volume 34, number 13, pages 1831-1838. doi:10.1002/esp.1879 Publication 7: Matti Vaaja, Juha Hyyppä, Antero Kukko, Harri Kaartinen, Hannu Hyyppä, and Petteri Alho. 2011. Mapping topography changes and elevation accuracies using a mobile laser scanner. Remote Sensing, volume 3, number 3, pages 587-600. doi:10.3390/rs3030587Laser scanning is a surveying technique used for mapping topography, vegetation, urban areas and infrastructure, ice, and other targets of interest. Its application on a terrestrial mobile platform is a promising method for effectively collecting three-dimensional data for complex environments and for producing model information for location-based services necessitating rapidly collected and up-to-date data. Development of mobile laser scanning (MLS) systems for such purposes is presented in this study. Different aspects of this technology were analyzed in laboratory experiments, simulations and field tests, in order to understand their effects on the ranging, intensity and point cloud data, especially in terms of point distribution and accuracy. In order to validate the performance of the developed ROAMER and AKHKA MLS systems, various three-dimensional mapping tasks were performed during an international benchmarking test, as well as in the field in numerous projects. The results showed that the proposed systems can reliably provide accurate data. It has also been shown that the various modalities of the systems allow data acquisition in numerous application scenarios and environments not previously possible. MLS improves the data output compared to terrestrial laser scanning (TLS) and outperforms airborne laser scanning (ALS) in ranging precision and point density. As a result, MLS is well suited to fill the gap between these two previously dominant 3D data acquisition techniques.Laserkeilaus on mittaustekniikka, jota käytetään maaston topografian kasvillisuuden, rakennettujen alueiden, infrastruktuurin, jään ja muiden kohteiden kartoitukseen. Tekniikan soveltaminen liikkuvalle alustalle on lupaava menetelmä monimuotoisten ympäristöjen tehokkaaseen kolmiulotteiseen mittaamiseen ja mallinnustiedon tuottamiseen paikkatietopalveluihin, jotka edellyttävät tiedon nopeaa hankintaa ja ajantasaisuutta. Tässä tutkimuksessa kehitettiin liikkuvia laserkeilausjärjestelmiä (MLS). Eri tekijöiden vaikutuksia etäisyys- ja intensiteettihavaintoihin, pistejakaumaan ja tarkkuuteen selvitettiin laboratoriokokein, simuloimalla ja koetöin. Tutkimuksessa kehitettyjen ROAMER ja AKHKA MLS-järjestelmien suorituskykyä kolmiulotteisen mittaustiedon tuottamiseen erilaisissa kartoitustehtävissä tutkittiin kansainvälisessä vertailututkimuksessa kaupunkitestikentän avulla, mutta lisäksi käytännön sovelluksissa useassa eri projektissa. Tutkimuksen tulokset osoittavat, että kehitetyt MLS järjestelmät tuottavat tarkkaa tietoa luotettavasti. Järjestelmien monikäyttöisyys mahdollistaa aineistonhankinnan eri sovellustapauksissa ja ympäristöissä tavalla, joka ei ole aikaisemmin ollut mahdollista. Liikkuva laserkeilaus parantaa merkittävästi mittauksen tehokkuutta maalaserkeilaukseen verrattuna, ja ylittää lentolaserkeilauksen suorituskyvyn etäisyysmittauksen tarkkuudessa ja pistetiheydessä. Liikkuva laserkeilaus tarjoaakin näitä kahta aikaisemmin vallitsevaa 3D-mittausteknologiaa hyvin täydentävän kartoitusmenetelmän

Hand-Held Personal Laser Scanning – Current Status and Perspectives for Forest Inventory Application

The emergence of hand-held Personal Laser Scanning (H-PLS) systems in recent years resulted in initial research on the possibility of its application in forest inventory, primarily for the estimation of the main tree attributes (e.g. tree detection, stem position, DBH, tree height, etc.). Research knowledge acquired so far can help to direct further research and eventually include H-PLS into operational forest inventory in the future. The main aims of this review are: Þ to present the current state of the art for H-PLS systems Þ briefly describe the fundamental concept and methods for H-PLS application in forest inventory Þ provide an overview of the results of previous studies Þ emphasize pros and cons for H-PLS application in forest inventory in relation to conventional field measurements and other similar laser scanning systems Þ highlight the main issues that should be covered by further H-PLS-based forest inventory studies

MEASURING LEAF WATER CONTENT USING MULTISPECTRAL TERRESTRIAL LASER SCANNING

Climate change is increasing the amount and intensity of disturbance events, i.e. drought, pest insect outbreaks and fungal pathogens, in forests worldwide. Leaf water content (LWC) is an early indicator of tree stress that can be measured remotely using multispectral terrestrial laser scanning (MS-TLS). LWC affects leaf reflectance in the shortwave infrared spectrum which can be used to predict LWC from spatially explicit MS-TLS intensity data. Here, we investigated the relationship between LWC and MS-TLS intensity features at 690 nm, 905 nm and 1550 nm wavelengths with Norway spruce seedlings in greenhouse conditions. We found that a simple ratio of 905 nm and 1550 nm wavelengths was able to explain 84% of the variation (R2) in LWC with a respective prediction accuracy of 0.0041 g/cm2. Our results showed that MS-TLS can be used to estimate LWC with a reasonable accuracy in environmentally stable conditions.Peer reviewe

Advancing Planetary Exploration - Where No LiDAR Has Gone Before

No abstract availabl

Multisource Point Clouds, Point Simplification and Surface Reconstruction

As data acquisition technology continues to advance, the improvement and upgrade of the algorithms for surface reconstruction are required. In this paper, we utilized multiple terrestrial Light Detection And Ranging (Lidar) systems to acquire point clouds with different levels of complexity, namely dynamic and rigid targets for surface reconstruction. We propose a robust and effective method to obtain simplified and uniform resample points for surface reconstruction. The method was evaluated. A point reduction of up to 99.371% with a standard deviation of 0.2 cm was achieved. In addition, well-known surface reconstruction methods, i.e., Alpha shapes, Screened Poisson reconstruction (SPR), the Crust, and Algebraic point set surfaces (APSS Marching Cubes), were utilized for object reconstruction. We evaluated the benefits in exploiting simplified and uniform points, as well as different density points, for surface reconstruction. These reconstruction methods and their capacities in handling data imperfections were analyzed and discussed. The findings are that (i) the capacity of surface reconstruction in dealing with diverse objects needs to be improved; (ii) when the number of points reaches the level of millions (e.g., approximately five million points in our data), point simplification is necessary, as otherwise, the reconstruction methods might fail; (iii) for some reconstruction methods, the number of input points is proportional to the number of output meshes; but a few methods are in the opposite; (iv) all reconstruction methods are beneficial from the reduction of running time; and (v) a balance between the geometric details and the level of smoothing is needed. Some methods produce detailed and accurate geometry, but their capacity to deal with data imperfection is poor, while some other methods exhibit the opposite characteristics

Remote Sensing methods for power line corridor surveys

AbstractTo secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments and practical monitoring conditions are needed. These should include careful quality analyses and comparisons between different data sources, methods and individual algorithms

Evaluating Factors Impacting Fallen Tree Detection from Airborne Laser Scanning Point Clouds

Fallen tree mapping provides valuable information regarding the ecological value of boreal forests. Airborne laser scanning (ALS) enables mapping fallen trees on a large scale. We compared the performance of line-detection-based individual fallen tree detection when using moderate point density ALS data (15 points/m2) and high-point-density unmanned aerial vehicle-based laser scanning (ULS) data (285 points/m2). Furthermore, we inspected the dataset and detection methodology-related factors impacting performance in each case. The results of this study showed that increasing the point density of the laser scanning dataset enables the detection of a larger proportion of fallen trees. However, based on our experiment, a line-detection-based fallen tree detection approach is sensitive to noise, thus generating a large number of false detections, especially with high-point-density data. Different types of filters, such as a simple height-based filter and machine-learning-based filters, can be used for reducing noise. However, using such filters is always a compromise, as in addition to reducing noise and thus false detections, they also reduce the number of true detections. Hence, a less noise-sensitive fallen tree detection method utilizing the finer details visible in high-density point clouds could be more suitable for high-point-density laser scanning data