A workflow to minimize shadows in uav-based orthomosaics

Journal of Unmanned Vehicle Systems

Volumn 7, Issue 2, 2019, Pages 107-117

  Rahman, Mir Mustafizur ^a   McDermid, Gregory J ^a   McKeeman, Taylor ^a   Lovitt, Julie ^a  

^a UNIVERSITY OF CALGARY   (Canada)

Author keywords

Multitemporal; Shadow removal; UAV orthophoto

Indexed keywords

GEOMETRICAL OPTICS; IMAGE ACQUISITION; OPTICAL DATA PROCESSING; UNMANNED AERIAL VEHICLES (UAV);

AERIAL VEHICLE; DATA VALUES; DIFFUSE ILLUMINATION; ILLUMINATION CONDITIONS; MULTI-TEMPORAL; OPTICAL IMAGE; ORTHOPHOTOS; SHADOW REMOVAL; UNMANNED AERIAL VEHICLE ORTHOPHOTO; WORK-FLOWS;

ANTENNAS;

EID: 85081935139     PISSN: None     EISSN: 22913467     Source Type: Journal    
DOI: 10.1139/juvs-2018-0012     Document Type: Article

References (22)

1. Colomina, I., and Molina, P. 2014. Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS J. Photogramm. Remote Sens. 92: 79–97. doi: 10.1016/j.isprsjprs.2014.02.013.
2. Dare, P.M. 2005. Shadow analysis in high-resolution satellite imagery of urban areas. Photogramm. Eng. Remote Sens. 71(2): 169–177. doi: 10.14358/PERS.71.2.169.
3. Goetz, S.J., Wright, R.K., Smith, A.J., Zinecker, E., and Schaub, E. 2003. IKONOS imagery for resource management: Tree cover, impervious surfaces, and riparian buffer analyses in the mid-Atlantic region. Remote Sens. Environ. 88(1): 195–208. doi: 10.1016/j.rse.2003.07.010.
4. Li, H., Zhang, L., and Shen, H. 2014. An adaptive nonlocal regularized shadow removal method for aerial remote sensing images. IEEE Trans. Geosci. Remote Sens. 52(1): 106–120. doi: 10.1109/TGRS.2012.2236562.
5. Li, Y., Gong, P., and Sasagawa, T. 2005. Integrated shadow removal based on photogrammetry and image analysis. Int. J. Remote Sens. 26(18): 3911–3929. doi: 10.1080/01431160500159347.
6. Lillesand, T.M., Kiefer, R.W., and Chipman, J.W. 2008. Remote sensing and image interpretation. 6th ed. Wiley, Hoboken, N.J., USA.
7. Liu, W., and Yamazaki, F. 2012. Object-based shadow extraction and correction of high-resolution optical satellite images. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 5(4): 1296–1302. doi: 10.1109/JSTARS.2012.2189558.
8. Lovitt, J., Rahman, M., and McDermid, G. 2017. Assessing the value of UAV photogrammetry for characterizing terrain in complex peatlands. Remote Sens. 9(7): 715. doi: 10.3390/rs9070715.
9. Pajares, G. 2015. Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs). Photogramm. Eng. Remote Sens. 81(4): 281–330. doi: 10.14358/PERS.81.4.281.
10. Rahman, M.M., Hay, G.J., Couloigner, I., Hemachandran, B., Bailin, J., Zhang, Y., and Tam, A. 2013. Geographic object-based mosaicing (OBM) of high-resolution thermal airborne imagery (TABI-1800) to improve the interpretation of urban image objects. IEEE Geosci. Remote Sens. Lett. 10(4): 918–922. doi: 10.1109/LGRS.2013.2243815.
11. Rau, J.-Y., Chen, N.-Y., and Chen, L.-C. 2002. True orthophoto generation of built-up areas using multi-view images. Photogramm. Eng. Remote Sens. 68(6): 581–588.
12. Roy, D.P., Ju, J., Lewis, P., Schaaf, C., Gao, F., Hansen, M., and Lindquist, E. 2008. Multi-temporal MODIS–Landsat data fusion for relative radiometric normalization, gap filling, and prediction of Landsat data. Remote Sens. Environ. 112(6): 3112–3130. doi: 10.1016/j.rse.2008.03.009.
13. Saha, A.K., Arora, M.K., Csaplovics, E., and Gupta, R.P. 2005. Land cover classification using IRS LISS III image and DEM in a rugged terrain: A case study in Himalayas. Geocarto Int. 20(2): 33–40. doi: 10.1080/10106040508542343.
14. Shahtahmassebi, A., Yang, N., Wang, K., Moore, N., and Shen, Z. 2013. Review of shadow detection and de-shadow-ing methods in remote sensing. Chin. Geogr. Sci. 23(4): 403–420. doi: 10.1007/s11769-013-0613-x.
15. Shu, J.S.P., and Freeman, H. 1990. Cloud shadow removal from aerial photographs. Pattern Recognit. 23(6): 647–656. doi: 10.1016/0031-3203(90)90040-R.
16. SunCalc. 2018. Citing online sources: Advice on online citation formats. Available from https://www.suncalc.org/[accessed October 2018].
17. Tong, X.H., Lin, X.F., Feng, T.T., Xie, H., Liu, S.J., Hong, Z.H., and Chen, P. 2013. Use of shadows for detection of earth-quake-induced collapsed buildings in high-resolution satellite imagery. ISPRS J. Photogramm. Remote Sens. 79: 53–67. doi: 10.1016/j.isprsjprs.2013.01.012.
18. Wu, Q., Zhang, W., and Kumar, B.V.2012. Strong shadow removal via patch-based shadow edge detection. In 2012 IEEE International Conference on Robotics and Automation, St. Paul, Minn., USA, 14–18 May 2012. pp. 2177–2182. doi: 10.1109/ICRA.2012.6224561.
19. Zarco-Tejada, P.J., Diaz-Varela, R., Angileri, V., and Loudjani, P. 2014. Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. Eur. J. Agron. 55: 89–99. doi: 10.1016/j.eja.2014.01.004.
20. Zhang, H., Sun, K., and Li, W. 2014. Object-oriented shadow detection and removal from urban high-resolution remote sensing images. IEEE Trans. Geosci. Remote Sens. 52(11): 6972–6982. doi: 10.1109/TGRS.2014.2306233.
21. Zhang, S., Chen, M., and Tang, J.S. 2013. Shadow detecting and shadow interpolation algorithm for InSAS. Adv. Mater. Res. 605–607: 2121–2125. doi: 10.4028/www.scientific.net/AMR.605-607.2121.
22. Zhu, Z., and Woodcock, C.E. 2014. Continuous change detection and classification of land cover using all available Landsat data. Remote Sens. Environ. 144: 152–171. doi: 10.1016/j.rse.2014.01.011.