Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 128, Issue , 2017, Pages 298-313

  Matikainen, Leena ^a   Karila, Kirsi ^a   Hyyppä, Juha ^a   Litkey, Paula ^a   Puttonen, Eetu ^a   Ahokas, Eero ^a  

^a FINNISH GEOSPATIAL RESEARCH INSTITUTE   (Finland)

Author keywords

Change detection; Land cover; Laser scanning; Lidar; Multispectral; Updating

Indexed keywords

ANTENNAS; AUTOMATION; DECISION TREES; FORESTRY; LASER APPLICATIONS; MAPPING; OPTICAL RADAR; SCANNING; SURFACE ANALYSIS;

CHANGE DETECTION; LAND COVER; LASER SCANNING; MULTI-SPECTRAL; UPDATING;

CLASSIFICATION (OF INFORMATION);

ACCURACY ASSESSMENT; AIRBORNE SENSING; DETECTION METHOD; LAND COVER; LASER METHOD; LIDAR; SATELLITE DATA; SENSOR; SPECTRAL ANALYSIS; SUBURBAN AREA;

FINLAND;

EID: 85018472685     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2017.04.005     Document Type: Article

References (55)

1. Ahokas, E., Kaasalainen, S., Hyyppä, J., Suomalainen, J., Calibration of the Optech ALTM 3100 laser scanner intensity data using brightness targets. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci., XXXVI(Part 1), 2006 7 p.
2. Ahokas, E., Hyyppä, J., Yu, X., Liang, X., Matikainen, L., Karila, K., Litkey, P., Kukko, A., Jaakkola, A., Kaartinen, H., Holopainen, M., Vastaranta, M., Towards automatic single-sensor mapping by multispectral airborne laser scanning. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XLI-B3 (2016), 155–162.
3. Axelsson, P., DEM generation from laser scanner data using adaptive TIN models. Int. Archiv. Photogram. Rem. Sens. XXXIII:Part B4 (2000), 110–117.
4. Baatz, M., Schäpe, A., Multiresolution segmentation – an optimization approach for high quality multi-scale image segmentation. Strobl, J., Blaschke, T., Griesebner, G., (eds.) Angewandte Geographische Informationsverarbeitung XII: Beiträge Zum AGIT-Symposium Salzburg 2000, 2000, Wichmann, Heidelberg, 12–23.
5. Bakuła, K., Multispectral airborne laser scanning – a new trend in the development of LiDAR technology. Archiwum Fotogrametrii, Kartografii i Teledetekcji 27 (2015), 25–44.
6. Bakuła, K., Kupidura, P., Jełowicki, Ł., Testing of land cover classification from multispectral airborne laser scanning data. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XLI-B7 (2016), 161–169.
7. Breiman, L., Random forests. Mach. Learn. 45:1 (2001), 5–32.
8. Breiman, L., Cutler, A., 2004. Random Forests. < http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm> (accessed 15 November, 2016).
9. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J., Classification and Regression Trees. 1984, Wadsworth Inc, Belmont, CA, USA.
10. Brenner, C., Building extraction. Vosselman, G., Maas, H.-G., (eds.) Airborne and Terrestrial Laser Scanning, 2010, Whittles Publishing, Dunbeath, Scotland, UK, 169–212.
11. Briese, C., Pfennigbauer, M., Ullrich, A., Doneus, M., Multi-wavelength airborne laser scanning for archaeological prospection. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XL-5/W2 (2013), 119–124.
12. Champion, N., Rottensteiner, F., Matikainen, L., Liang, X., Hyyppä, J., Olsen, B.P., A test of automatic building change detection approaches. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XXXVIII:Part 3/W4 (2009), 145–150.
13. Chen, Y., Räikkönen, E., Kaasalainen, S., Suomalainen, J., Hakala, T., Hyyppä, J., Chen, R., Two-channel hyperspectral LiDAR with a supercontinuum laser source. Sensors 10 (2010), 7057–7066.
14. Clode, S., Rottensteiner, F., Kootsookos, P., Zelniker, E., Detection and vectorization of roads from lidar data. Photogramm. Eng. Remote Sens. 73:5 (2007), 517–535.
15. Eitel, J.U.H., Höfle, B., Vierling, L.A., Abellán, A., Asner, G.P., Deems, J.S., Glennie, C.L., Joerg, P.C., LeWinter, A.L., Magney, T.S., Mandlburger, G., Morton, D.C., Müller, J., Vierling, K.T., Beyond 3-D: The new spectrum of lidar applications for earth and ecological sciences. Remote Sens. Environ. 186 (2016), 372–392.
16. Fernandez-Diaz, J.C., Carter, W.E., Glennie, C., Shrestha, R.L., Pan, Z., Ekhtari, N., Singhania, A., Hauser, D., Sartori, M., Capability assessment and performance metrics for the Titan multispectral mapping lidar. Rem. Sens., 8(11), 2016, 936.
17. Guo, L., Chehata, N., Mallet, C., Boukir, S., Relevance of airborne lidar and multispectral image data for urban scene classification using Random Forests. ISPRS J. Photogram. Rem. Sens. 66 (2011), 56–66.
18. Hakala, T., Suomalainen, J., Kaasalainen, S., Full waveform active hyperspectral lidar. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XXXIX-B7 (2012), 459–462.
19. Hakala, T., Nevalainen, O., Kaasalainen, S., Mäkipää, R., Technical note: multispectral lidar time series of pine canopy chlorophyll content. Biogeosciences 12:5 (2015), 1629–1634.
20. Haralick, R.M., Shanmugam, K., Dinstein, I., Textural features for image classification. IEEE Trans. Syst. Man Cybernet. 3:6 (1973), 610–621.
21. Höfle, B., Pfeifer, N., Correction of laser scanning intensity data: data and model-driven approaches. ISPRS J. Photogram. Rem. Sens. 62:6 (2007), 415–433.
22. Holland, D.A., Sanchez-Hernandez, C., Gladstone, C., Detecting changes to topographic features using high resolution imagery. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XXXVII:Part B4 (2008), 1153–1158.
23. Hopkinson, C., Chasmer, L., Gynan, C., Mahoney, C., Sitar, M., Multisensor and multispectral LiDAR characterization and classification of a forest environment. Can. J. Remote. Sens. 42:5 (2016), 501–520.
24. Hu, X., Tao, C.V., Hu, Y., Automatic road extraction from dense urban area by integrated processing of high resolution imagery and lidar data. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XXXV:Part B3 (2004), 320–324.
25. Hug, C., Extracting artificial surface objects from airborne laser scanner data. Gruen, A., Baltsavias, E.P., Henricsson, O., (eds.) Automatic Extraction of Man-Made Objects From Aerial and Space Images (II), 1997, Birkhäuser Verlag, Basel, Switzerland, 203–212.
26. Kaasalainen, S., Ahokas, E., Hyyppä, J., Suomalainen, J., Study of surface brightness from backscattered laser intensity: calibration of laser data. IEEE Geosci. Remote Sens. Lett. 2:3 (2005), 255–259.
27. Kaasalainen, S., Pyysalo, U., Krooks, A., Vain, A., Kukko, A., Hyyppä, J., Kaasalainen, M., Absolute radiometric calibration of ALS intensity data: effects on accuracy and target classification. Sensors 11:11 (2011), 10586–10602.
28. Karila, K., Matikainen, L., Puttonen, E., Hyyppä, J., Feasibility of multispectral airborne laser scanning data for road mapping. IEEE Geosci. Remote Sens. Lett. 14:3 (2017), 294–298.
29. Leigh, H.W., Magruder, L.A., Using dual-wavelength, full-waveform airborne lidar for surface classification and vegetation characterization. J. Appl. Rem. Sens., 10(4), 2016, 045001.
30. Luzum, B., Starek, M., Slatton, K.C., 2004. Normalizing ALSM intensities. Geosensing Engineering and Mapping (GEM) Center Report No. Rep_2004-07-001, Civil and Coastal Engineering Department, University of Florida, Gainesville, FL, USA.
31. Malpica, J.A., Alonso, M.C., Papí, F., Arozarena, A., Martínez De Agirre, A., Change detection of buildings from satellite imagery and lidar data. Int. J. Remote Sens. 34:5 (2013), 1652–1675.
32. Mathworks, 2016. Online Documentation for Statistics and Machine Learning Toolbox, Version R2016a.
33. Matikainen, L., Karila, K., Segment-based land cover mapping of a suburban area – comparison of high-resolution remotely sensed datasets using classification trees and test field points. Rem. Sens. 3:8 (2011), 1777–1804.
34. Matikainen, L., Hyyppä, J., Hyyppä, H., Automatic detection of buildings from laser scanner data for map updating. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XXXIV:Part 3/W13 (2003), 218–224.
35. Matikainen, L., Hyyppä, J., Ahokas, E., Markelin, L., Kaartinen, H., Automatic detection of buildings and changes in buildings for updating of maps. Rem. Sens. 2:5 (2010), 1217–1248.
36. Matikainen, L., Hyyppä, J., Litkey, P., Multispectral airborne laser scanning for automated map updating. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XLI-B3 (2016), 323–330.
37. Miller, C.I., Thomas, J.J., Kim, A.M., Metcalf, J.P., Olsen, R.C., 2016. Application of image classification techniques to multispectral lidar point cloud data. In: Proc. SPIE 9832 (Laser Radar Tehnology and Applications XXI), 98320X, 12 p.
38. Morsy, S., Shaker, A., El-Rabbany, A., LaRocque, P.E., Airborne multispectral lidar data for land-cover classification and land/water mapping using different spectral indexes. ISPRS Ann. Photogram. Rem. Sens. Spatial Inform. Sci. III-3 (2016), 217–224.
39. Murakami, H., Nakagawa, K., Hasegawa, H., Shibata, T., Iwanami, E., Change detection of buildings using an airborne laser scanner. ISPRS J. Photogram. Rem. Sens. 54 (1999), 148–152.
40. Pfennigbauer, M., Ullrich, A., 2011. Multi-wavelength airborne laser scanning. In: Proc. 2011 International Lidar Mapping Forum, ILMF, New Orleans, 10 p.
41. Puttonen, E., Hakala, T., Nevalainen, O., Kaasalainen, S., Krooks, A., Karjalainen, M., Anttila, K., Artificial target detection with a hyperspectral LiDAR over 26-h measurement. Opt. Eng., 54(1), 2015, 013105.
42. Puttonen, E., Briese, C., Mandlburger, G., Wieser, M., Pfennigbauer, M., Zlinszky, A., Pfeifer, N., Quantification of overnight movement of birch (betula pendula) branches and foliage with short interval terrestrial laser scanning. Front. Plant Sci., 7, 2016, 222.
43. QGIS Development Team, 2016. QGIS Geographic Information System. Open Source Geospatial Foundation. < http://qgis.osgeo.org> (accessed 17 February, 2017).
44. Richter, R., Kyprianidis, J.E., Döllner, J., Out-of-core GPU-based change detection in massive 3D point clouds. Trans. GIS 17:5 (2013), 724–741.
45. Rottensteiner, F., Trinder, J., Clode, S., Kubik, K., Building detection by fusion of airborne laser scanner data and multi-spectral images: Performance evaluation and sensitivity analysis. ISPRS J. Photogram. Rem. Sens. 62 (2007), 135–149.
46. Teo, T.-A., Shih, T.-Y., Lidar-based change detection and change-type determination in urban areas. Int. J. Remote Sens. 34:3 (2013), 968–981.
47. Vauhkonen, J., Hakala, T., Suomalainen, J., Kaasalainen, S., Nevalainen, O., Vastaranta, M., Holopainen, M., Hyyppä, J., Classification of spruce and pine trees using active hyperspectral LiDAR. IEEE Geosci. Remote Sens. Lett. 10:5 (2013), 1138–1141.
48. Vosselman, G., Kessels, P., Gorte, B., The utilisation of airborne laser scanning for mapping. Int. J. Appl. Earth Obs. Geoinf. 6 (2005), 177–186.
49. Wagner, W., Radiometric calibration of small-footprint full-waveform airborne laser scanner measurements: basic physical concepts. ISPRS J. Photogram. Rem. Sens. 65:6 (2010), 505–513.
50. Wagner, W., Ullrich, A., Ducic, V., Melzer, T., Studnicka, N., Gaussian decomposition and calibration of a novel small-footprint full-waveform digitising airborne laser scanner. ISPRS J. Photogram. Rem. Sens. 60:2 (2006), 100–112.
51. Wang, C.-K., Tseng, Y.-H., Chu, H.-J., Airborne dual-wavelength LiDAR data for classifying land cover. Rem. Sens. 6:1 (2014), 700–715.
52. Wichmann, V., Bremer, M., Lindenberger, J., Rutzinger, M., Georges, C., Petrini-Monteferri, F., Evaluating the potential of multispectral airborne lidar for topographic mapping and land cover classification. ISPRS Ann. Photogram. Rem. Sens. Spatial Inform. Sci. II-3/W5 (2015), 113–119.
53. Yan, W.Y., Shaker, A., El-Ashmawy, N., Urban land cover classification using airborne LiDAR data: a review. Remote Sens. Environ. 158 (2015), 295–310.
54. Zha, Y., Gao, J., Ni, S., Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. Int. J. Remote Sens. 24:3 (2003), 583–594.
55. Zou, X., Zhao, G., Li, J., Yang, Y., Fang, Y., 3D land cover classification based on multispectral lidar point clouds. Int. Archiv. Photogram. Rem. Sens. Spatial Inform. Sci. XLI-B1 (2016), 741–747.