Abstract
Airborne laser scanning (ALS) is a technique used to obtain Digital Surface Models (DSM) and Digital Terrain Models (DTM) efficiently, and filtering is the key procedure used to derive DTM from point clouds. Generating seed points is an initial step for most filtering algorithms, whereas existing algorithms usually define a regular window size to generate seed points. This may lead to an inadequate density of seed points, and further introduce error type I, especially in steep terrain and forested areas. In this study, we propose the use of objectbased analysis to derive surface complexity information from ALS datasets, which can then be used to improve seed point generation.We assume that an area is complex if it is composed of many small objects, with no buildings within the area. Using these assumptions, we propose and implement a new segmentation algorithm based on a grid index, which we call the Edge and Slope Restricted Region Growing (ESRGG) algorithm. Surface complexity information is obtained by statistical analysis of the number of objects derived by segmentation in each area. Then, for complex areas, a smaller window size is defined to generate seed points. Experimental results show that the proposed algorithm could greatly improve the filtering results in complex areas, especially in steep terrain and forested areas.
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Acknowledgements
The authors would like to thank the anonymous reviewers for providing comments to improve the quality of this paper, and iSPACE of Research Studios Austria FG (RSA) (http://ispace.researchstudio. at/) for providing the ALS datasets. The study described in this paper is funded by the National Natural Science Foundation of China (Grant No. 41301493), the High Resolution Earth Observation Science Foundation of China (GFZX04060103-5-17), and Special Fund for Surveying and Mapping Scientific Research in the Public Interest (201412007).
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Menglong Yan received his B.Sc. degree in remote sensing from Wuhan University, Wuhan, China, in 2007, and his Ph.D. in geographic information science and remote sensing from Peking University, Beijing, China, in 2012.
He is currently an Assistant Researcher at the Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences in China. His research interests include LiDAR data processing and high resolution remote sensing image processing.
Thomas Blaschke is currently a Full Professor at the University of Salzburg, Deputy Chair for the Department of Geoinformatics – Z_GIS, Head of iSPACE Research Studio, and Director of Doctoral College GIScience, Austria. His prior positions include several lecturer, senior lecturer, and professor positions in Germany, Austria, and the UK, as well as temporary affiliations as guest professor and visiting scientist in Germany and the US, including a Fulbright professorship.
His research interests include methodological issues of the integration of GIS, remote sensing, and image processing, including aspects relating to participation and human-environment interaction. His academic record yields 340 + scientific publications, including approximately 100 journal publications. He has authored, coauthored, or edited 17 books, and received several academic awards, including the Christian-Doppler Prize in 1995. He is currently, and has in the past, served as project leader in various international and national research projects and on various editing boards of international journals, conference committees, and for a number of national research councils.
Hongzhao Tang received his B.Eng. degree in geomatics engineering fromWuhan University,Wuhan, China, in 2007, a B.Eng. degree in photogrammetry and remote sensing from Peking University, Beijing, China, in 2010, and an M.Sc. degree in Ecology from Colorado State University, USA, in 2013.
He is currently a Research Engineer at the Satellite Surveying and Mapping Application Center, National Administration of Surveying, Mapping and Geoinformation, in China. His major research interests include hyperspectral remote sensing, remote sensing sensor calibration, and atmospheric correction.
Chenchao Xiao received his B.Sc. and M.Sc. degrees in geographical information systems from Nanjing Normal University, Nanjing, China, in 2004 and 2007, respectively, and his Ph.D. in geographical information science from Peking University, Beijing, China, in 2011.
He is currently the Director of the Institute of Remote Sensing Application Techniques, Aero Geophysical Survey and Remote Sensing Center, Ministry of Land and Resources in China. His research interests include high resolution remote sensing image processing, digital terrain analysis, and remote sensing application.
Xian Sun received his B.Sc. degree in electronic and information engineering from Beijing University of Aeronautics and Astronautics, Beijing, China, in 2004, and his Ph.D. degree in signal and information processing from the Graduate University of the Chinese Academy of Sciences, Beijing, China, in 2009.
He is currently an Associate Researcher at the Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences in China. His research interests include remote sensing image interpretation, computer vision, statistical and structural pattern recognition, machine learning, and data mining with applications to remote sensing.
Daobing Zhang received his B.Sc. degree in communication and signal processing from the Graduate University of the Chinese Academy Sciences, Beijing, China, in 2004, and his Ph.D. degree in optics engineering from the Graduate University of the Chinese Academy Sciences, Beijing, China, in 2007.
He is currently an Associate Researcher at the Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Institute of Electronics, Chinese Academy of Sciences in China. His research interests include high resolution remote sensing image processing and interpretation.
Kun Fu received his B.Sc. degree in electronic and information engineering from The National University of Defense Technology, Changsha, China, in 1995, and his Ph.D. degree in communication and signal processing from The National University of Defense Technology, Changsha, China, in 2001.
He is currently Head and Professor of the Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems at the Institute of Electronics, Chinese Academy of Sciences in China. His research interests include remote sensing image processing, remote sensing image interpretation, and data mining.
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Yan, M., Blaschke, T., Tang, H. et al. Using object-based analysis to derive surface complexity information for improved filtering of airborne laser scanning data. Front. Earth Sci. 11, 11–19 (2017). https://doi.org/10.1007/s11707-016-0567-2
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DOI: https://doi.org/10.1007/s11707-016-0567-2