Benchmarking of airborne laser scanning based feature extraction methods and mobile laser scanning system performance based on high-quality test fields

Osajulkaisut: Publication 1: Kaartinen, H., Hyyppä, J., Gülch, E., Vosselman, G., Hyyppä, H., Matikainen, L., Hofmann, A.D., Mäder, U., Persson, Å., Söderman, U., Elmqvist, M., Ruiz, A., Dragoja, M., Flamanc, D., Maillet, G., Kersten, T., Carl, J., Hau, R., Wild, E., Frederiksen, L., Holmgaard, J. and Vester, K., 2005. Accuracy of 3D city models: EuroSDR comparison. Proceedings of ISPRS Workshop "Laser scanning 2005", September 12-14, 2005, Enschede, The Netherlands, The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVI(Part 3/W19), 227-232, CD-ROM. Publication 2: Kaartinen, H. and Hyyppä, J., 2006. EuroSDR-Project Commission 3 "Evaluation of Building Extraction", Final Report, In: EuroSDR - European Spatial Data Research, Official Publication No 50, 9-77. Publication 3: Kaartinen, H. and Hyyppä, J., 2008. EuroSDR/ISPRS Project, Commission II "Tree Extraction", Final Report, EuroSDR – European Spatial Data Research, Official Publication No 53, 56 p. Publication 4: Kaartinen, H., Hyyppä, J., Yu, X., Vastaranta, M., Hyyppä, H., Kukko, A., Holopainen, M., Heipke, C., Hirschmugl, M., Morsdorf, F., Næsset, E., Pitkänen, J., Popescu, S., Solberg, S., Wolf, B.M. and Wu, J.-C., 2012. An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning. Remote Sensing, 4(4), 950-974. Publication 5: Kaartinen, H., Hyyppä, J., Kukko, A., Jaakkola, A. and Hyyppä, H., 2012. Benchmarking the Performance of Mobile Laser Scanning Systems Using a Permanent Test Field. Sensors 12(9), 12814-12835. Publication 6: Kaartinen, H., Hyyppä, J., Kukko, A., Lehtomäki, M., Jaakkola, A., Hyyppä, H., Vosselman,G., Elberink, S.O., Rutzinger; M., Pu, S. and Vaaja, M., 2013. EuroSDR-Project Commission II "Mobile Mapping - Road Environment Mapping using Mobile Laser Scanning", Final Report, In: EuroSDR - European Spatial Data Research, Official Publication No 62, 49-95.Comparing different feature extraction methods based on remote sensing or remote sensing systems is difficult as there are but few common data sets or test fields with reference data of high standard available for analysis. State-of-the-art methods and systems are often in still evolving stage and can be run only by the developers themselves. Establishing a high-quality test field is laborious, but once such a test field has been established, it becomes easier to set up the systems to collect data from the field than to collect reference data from new areas. Comparing either different systems or the same system with different parameters is easier when the number of variables is kept to a minimum; the remotely sensed areas are kept constant and any changes in them can be controlled more easily. The benchmarking results provide valuable information to both developers and users of remote sensing data products. The benchmarked feature extraction methods studied included extraction of buildings and individual trees using data from common test fields. The performance of the mobile laser scanning systems was benchmarked using data collected from an established urban test field. In all cases, it was concluded that the primary factor affecting the results was the method or the system, and this enabled a high degree of comparability for the results of the given extraction or mapping tasks.Erilaisten kaukokartoitukseen perustuvien kohdemallinnusmenetelmien tai kaukokartoitusjärjestelmien vertailu on vaikeaa koska yhteisesti käytettävissä olevia aineistoja tai testikenttiä, joista on saatavissa korkealaatuista referenssiaineistoa, on olemassa vain vähän. Uusimmat menetelmät ja järjestelmät ovat usein vielä kehitysvaiheessa ja niiden käyttö onnistuu vain niiden kehittäjiltä. Korkealaatuisen testikentän tekeminen on työlästä, mutta kun testikenttä on perustettu, on helpompaa kerätä aineistoja siltä eri järjestelmillä kuin mitata referenssiaineistoa uusilta alueilta. Eri järjestelmien tai yhden järjestelmän eri asetuksien vertailu on helpompaa kun muuttujien määrä on mahdollisimman pieni; tässä tapauksessa kaukokartoitetut alueet pysyvät vakiona ja mahdolliset muutokset niissä ovat helpommin kontrolloitavissa. Vertailujen tulokset antavat hyödyllistä tietoa sekä kaukokartoitustuotteiden kehittäjille että niiden käyttäjille. Vertaillut kohdemallinnusmenetelmät olivat rakennusten ja yksittäisten puiden mallinnus yhteisiltä testikentiltä kerättyjä aineistoja käyttäen. Liikkuvien laserkeilausjärjestelmien suorituskykyä vertailtiin käyttäen perustetulta kaupunkitestikentältä kerättyjä aineistoja. Kaikissa tapauksissa todettiin että tärkein tuloksiin vaikuttava tekijä oli menetelmä tai järjestelmä itse, joten annetun mallinnus- tai kartoitustehtävän tulokset ovat hyvin vertailukelpoisia

A Review: Remote Sensing Sensors

The cost of launching satellites is getting lower and lower due to the reusability of rockets (NASA, 2015) and using single missions to launch multiple satellites (up to 37, Russia, 2014). In addition, low-orbit satellite constellations have been employed in recent years. These trends indicate that satellite remote sensing has a promising future in acquiring high-resolution data with a low cost and in integrating high-resolution satellite imagery with ground-based sensor data for new applications. These facts have motivated us to develop a comprehensive survey of remote sensing sensor development, including the characteristics of sensors with respect to electromagnetic spectrums (EMSs), imaging and non-imaging sensors, potential research areas, current practices, and the future development of remote sensors.Peer reviewe

Single-Sensor Solution to Tree Species Classification Using Multispectral Airborne Laser Scanning

This paper investigated the potential of multispectral airborne laser scanning (ALS) data for individual tree detection and tree species classification. The aim was to develop a single-sensor solution for forest mapping that is capable of providing species-specific information, required for forest management and planning purposes. Experiments were conducted using 1903 ground measured trees from 22 sample plots and multispectral ALS data, acquired with an Optech Titan scanner over a boreal forest, mainly consisting of Scots pine (Pinus Sylvestris), Norway spruce (Picea Abies), and birch (Betula sp.), in southern Finland. ALS-features used as predictors for tree species were extracted from segmented tree objects and used in random forest classification. Different combinations of features, including point cloud features, and intensity features of single and multiple channels, were tested. Among the field-measured trees, 61.3% were correctly detected. The best overall accuracy (OA) of tree species classification achieved for correctly-detected trees was 85.9% (Kappa = 0.75), using a point cloud and single-channel intensity features combination, which was not significantly different from the ones that were obtained either using all features (OA = 85.6%, Kappa = 0.75), or single-channel intensity features alone (OA = 85.4%, Kappa = 0.75). Point cloud features alone achieved the lowest accuracy, with an OA of 76.0%. Field-measured trees were also divided into four categories. An examination of the classification accuracy for four categories of trees showed that isolated and dominant trees can be detected with a detection rate of 91.9%, and classified with a high overall accuracy of 90.5%. The corresponding detection rate and accuracy were 81.5% and 89.8% for a group of trees, 26.4% and 79.1% for trees next to a larger tree, and 7.2% and 53.9% for trees situated under a larger tree, respectively. The results suggest that Channel 2 (1064 nm) contains more information for separating pine, spruce, and birch, followed by channel 1 (1550 nm) and channel 3 (532 nm) with an overall accuracy of 81.9%, 78.3%, and 69.1%, respectively. Our results indicate that the use of multispectral ALS data has great potential to lead to a single-sensor solution for forest mapping.Peer reviewe

Soluble Urokinase Plasminogen Activator Receptor (suPAR) in the Emergency Department (Ed): A Tool for the Assessment of Elderly Patients

Emergency department (ED) overcrowding is a global issue setting challenges to all care providers. Elderly patients are frequent visitors of the ED and their risk stratification is demanding due to insufficient assessment methods. A prospective cohort study was conducted to determine the risk-predicting value of a prognostic biomarker, soluble urokinase plasminogen activator receptor (suPAR), in the ED, concentrating on elderly patients. SuPAR levels were determined as part of standard blood sampling of 1858 ED patients. The outcomes were assessed in the group o

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

Detecting changes in forest structure over time with bi-temporal terrestrial laser scanning data

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