À propos de cet article

Citez

Ahokas, E., Kaartinen, H., Hyyppä, J. 2004. A quality assessment of repeated airborne laser scanner observations. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 35, 237-242.Search in Google Scholar

Alharthy, A., Bethel, J., Mikhail, E. M. 2004. Analysis and accuracy assessment of airborne laserscanning system. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 35, 144-149.Search in Google Scholar

Antonarakis, A.S., Richards, K.S., Brasington, J. 2008. Object-based land cover classification using airborne LiDAR. Remote Sensing of Environment, 112 (6), 2988-2998. DOI: 10.1016/j.rse.2008.02.00410.1016/j.rse.2008.02.004Search in Google Scholar

Baltsavias, E.P. 1999. Airborne laser scanning: basic relations and formulas. ISPRS Journal of photogrammetry and remote sensing, 54 (2), 199-214. DOI: 10.1016/S0924-2716(99)00015-510.1016/S0924-2716(99)00015-5Search in Google Scholar

Behan, A. 2000. On the matching accuracy of rasterised scanning laser altimeter data. International Archives of Photogrammetry and Remote Sensing, 33 (B2), 75-80.Search in Google Scholar

Bowen, Z.H., Waltermire, R.G. 2002. Evaluation of light detection and ranging (LIDAR) for measuring river corridor topography. JAWRA Journal of the American Water Resources Association, 38 (1), 33-41.Search in Google Scholar

Chase, A.F. et al. 2011. Airborne LiDAR, archaeology, and the ancient Maya landscape at Caracol, Belize. Journal of Archaeological Science, 38 (2), 387-398. DOI: 10.1016/j.jas.2010.09.01810.1016/j.jas.2010.09.018Search in Google Scholar

Congalton, R.G. 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37 (1), 35-46. DOI: 10.1016/0034-4257(91)90048-b10.1016/0034-4257(91)90048-BSearch in Google Scholar

Congalton, R.G., Green, K. 2008. Assessing the accuracy of remotely sensed data: principles and practices. CRC press.10.1201/9781420055139Search in Google Scholar

County, K. 2003. LiDAR digital ground model point density, KGIS Center, Seattle, WA. Available at http://www5.kingcounty.gov/sdc/raster/elevation/LiDAR_Digital_Ground_Model_Point_Density.html/Search in Google Scholar

Dewberry, 2014. LiDAR Quality Assurance for Oahu LiDAR Produced for National Oceanic and Atmospheric Administration. Available at https://coast.noaa.gov/htdata/lidar1_z/geoid12a/data/3655/supplemental/hi2013_noaa_oahu_lidarreport_m3655.pdfSearch in Google Scholar

Filin, S. 2003. Analysis and implementation of a laser strip adjustment model. International Archives of Photogrammetry and Remote Sensing, 65–70.Search in Google Scholar

Fischler, M.A., Bolles R.C. 1981. Random sample consensus: a paradigm for model fitting with application to image analysis and automated cartography. Communications of the ACM, 24 (6), 381-395.Search in Google Scholar

Groundpoint Technologies. 2010. Accuracy assessment and quality control report for the Milwaukee, WI Project Area. Available at http://www.county.milwaukee.gov/ImageLibrary/User/bshaw/LiDARQAQC_MilwaukeeWI_final_01.pdfSearch in Google Scholar

Glennie, C. 2007. Rigorous 3D error analysis of kinematic scanning LIDAR systems. Journal of Applied Geodesy, 1 (3), 147-157.Search in Google Scholar

Gruen, A. 1985. Adaptive least squares correlation: a powerful image matching technique. South African Journal of Photogrammetry, Remote Sensing and Cartography, 14 (3), 175-187.Search in Google Scholar

Guo, B., Huang, X., Zhang, F., Sohn, G., 2015. Classification of airborne laser scanning data using JointBoost. ISPRS Journal of Photogrammetry and Remote Sensing, 100, 71-83. DOI: 10.1016/j.isprsjprs.2014.03.00410.1016/j.isprsjprs.2014.03.004Search in Google Scholar

Haala, N., Kada, M. 2010. An update on automatic 3D building reconstruction. ISPRS Journal of Photo-grammetry and Remote Sensing, 65 (6), 570-580. DOI: 10.1016/j.isprsjprs.2010.09.00610.1016/j.isprsjprs.2010.09.006Search in Google Scholar

Habib, A., Bang, K.I., Kersting, A.P., Chow, J. 2010. Alternative methodologies for LiDAR system calibration. Remote Sensing, 2 (3), 874-907. DOI: 10.3390/rs203087410.3390/rs2030874Search in Google Scholar

Habib, A., Bang, K.I., Kersting, A.P., Lee, D.C. 2009. Error budget of LiDAR systems and quality control of the derived data. Photogrammetric Engineering and Remote Sensing, 75 (9), 1093-1108. DOI: 10.14358/PERS.75.9.109310.14358/PERS.75.9.1093Search in Google Scholar

Habib, A.F., Kersting, A.P., Ruifang, Z., Al-Durgham, M., Kim, C., Lee, D.C. 2008. LiDAR strip adjustment using conjugate linear features in overlapping strips. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, 385-390.Search in Google Scholar

Habib, A.F., Rens, J.V. 2007. Quality assurance and quality control of Lidar systems and derived data. In: Advanced Lidar Workshop, University of Northern Iowa.10.1201/9781420051438.ch9Search in Google Scholar

Heidemann, H.K. 2014. Lidar base specification version 1.0: US Geological survey techniques and methods. Book, 11, 63.Search in Google Scholar

Kim, H.B., Sohn, G. 2010. 3D classification of power-line scene from airborne laser scanning data using random forests. International Archives of Photo-grammetry and Remote Sensing, 38, 126-132.Search in Google Scholar

Lari, Z., Habib, A. 2012. Alternative methodologies for the estimation of local point density index: Moving towards adaptive LiDAR data processing. International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 39, 127-132.Search in Google Scholar

Latypov, D. 2002. Estimating relative lidar accuracy information from overlapping flight lines. ISPRS Journal of Photogrammetry and Remote Sensing, 56 (4), 236-245. DOI: 10.1016/S0924-2716(02)00047-310.1016/S0924-2716(02)00047-3Search in Google Scholar

Liu, X. 2011. Accuracy assessment of LiDAR elevation data using survey marks. Survey Review, 43 (319), 80-93.Search in Google Scholar

Liu, Z.S., Liu, B.Y., Wu, S.H., Li, Z.G., Wang, Z.J. 2008. High spatial and temporal resolution mobile incoherent Doppler lidar for sea surface wind measurements. Optics letters, 33 (13), 1485-1487.Search in Google Scholar

Luethy, J., Ingensand, H. 2004. How to evaluate the quality of airborne laser scanning data. Proceedings of NATSCAN-Conference on Laser-Scanners for Forest- and Landscape Assessment, Freiburg, Germany, October 3-6, 2004. International Archives of Photogrammetry and Remote Sensing, 36 (8/W2), 313-317.Search in Google Scholar

Maas, H.G. 2003. Planimetric and height accuracy of airborne laserscanner data: User requirements and system performance. Proceedings of Photogram-metric Week, Vol. 49, 117-125.Search in Google Scholar

Maas, H.G. 2002. Methods for measuring height and planimetry discrepancies in airborne laserscanner data. Photogrammetric Engineering and Remote Sensing, 68 (9), 933–940.Search in Google Scholar

Maltamo, M., Næsset, E., Vauhkonen, J. 2014. Forestry applications of airborne laser scanning. Concepts and case studies. Managing for Ecosystems, 27, 2014.Search in Google Scholar

Matikainen, L., Hyyppä, J., Kaartinen, H. 2009. Comparison between first pulse and last pulse laser scanner data in the automatic detection of buildings. Photogrammetric Engineering and Remote Sensing, 75 (2), 133-146.Search in Google Scholar

Polish Ministry of the Interior and Administration. 2011. Ordinance of the Minister of Interior and Administration of 3 November 2011 on aerial and satellite imagery databases and orthophotomaps and numerical terrain models.Search in Google Scholar

Renslow, M.S. 2012. Manual of Airborne Topographic LiDAR. American Society for Photogrammetry Remote Sensing, Bethesda, Maryland.Search in Google Scholar

Rupnik, B., Mongus, D., Žalik, B. 2015. Point Density Evaluation of Airborne LiDAR Datasets. Journal of Universal Computer Science, 21(4), 587-603. DOI: 10.3217/jucs-021-04-0587Search in Google Scholar

Rusu, R.B. 2010. Semantic 3d object maps for everyday manipulation in human living environments. KIKünstlicheIntelligenz, 24(4), 345-348.Search in Google Scholar

Stereńczak, K., Ciesielski, M., Bałazy, R., Zawiła-Niedźwiecki, T. 2016. Comparison of various algorithms for DTM interpolation from LIDAR data in dense mountain forests. European Journal of Remote Sensing, 49, 599–621.Search in Google Scholar

Tran, G., Nguyen, D., Milenkovic, M., Pfeifer, N. 2015. Potential of Full Waveform Airborne Laser Scanning Data for Urban Area Classification-Transfer of Classification Approaches Between Missions. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40 (7), 1317-1323.Search in Google Scholar

Vierling, K.T., Vierling, L.A., Gould, W.A., Martinuzzi, S., Clawges, R.M. 2008. Lidar: shedding new light on habitat characterization and modeling. Frontiers in Ecology and the Environment, 6(2), 90-98. DOI: 10.1890/07000110.1890/070001Search in Google Scholar

URS Corporation. 2012. Independent LiDAR Quality Control Report – Calvert Country Area of Interest. Available at http://webmaps.esrgc.org/LiDAR/portal/client/download/Metadata/Calvert/Final%20Calvert%20LiDAR%20QA%20Report.pdfSearch in Google Scholar

Wechsler, N., Rockwell, T.K., Ben-Zion, Y. 2009. Application of high resolution DEM data to detect rock damage from geomorphic signals along the central San Jacinto Fault. Geomorphology, 113 (1), 82-96.Search in Google Scholar

Wężyk, P. 2014. Podręcznik dla uczestników szkoleń z wykorzystaniem produktów LiDAR. Głowny Urząd Geodezji i Kartografii, Warszawa.Search in Google Scholar

Wu, J., Yao, W., Chi, W., Zhao, X. 2011. Comprehensive quality evaluation of airborne lidar data. International Symposium on Lidar and Radar Mapping Technologies, 828604-828604. International Society for Optics and Photonics.10.1117/12.912588Search in Google Scholar

Xiong, X., Adan, A., Akinci, B., Huber, D. 2013. Automatic creation of semantically rich 3D building models from laser scanner data. Automation in Construction, 31, 325-337. DOI: 10.1016/j.autcon.2012.10.00610.1016/j.autcon.2012.10.006Search in Google Scholar

Yan, W.Y., Shaker, A., Habib, A., Kersting, A.P. 2012. Improving classification accuracy of airborne Li-DAR intensity data by geometric calibration and radiometric correction. ISPRS Journal of Photo-grammetry and Remote Sensing, 67, 35-44. DOI: http://dx.doi.org/10.1016/j.isprsjprs.2011.10.00510.1016/j.isprsjprs.2011.10.005Search in Google Scholar

Zhang, Y.J., Xiong, X.D., Hu, X.Y. 2013. Rigorous Li-DAR Strip Adjustment with Triangulated Aerial Imagery. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, II-5/W2, 361–366. DOI: 10.5194/isprsannals-II-5-W2-361-201310.5194/isprsannals-II-5-W2-361-2013Search in Google Scholar

eISSN:
2199-5907
ISSN:
0071-6677
Langue:
Anglais
Périodicité:
4 fois par an
Sujets de la revue:
Life Sciences, Plant Science, Medicine, Veterinary Medicine