1. Grimm, N.B., et al., Global change and the ecology of cities. science, 2008. 319(5864): p. 756-760. [DOI:10.1126/science.1150195]

2. Cohen, B., Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability. Technology in society, 2006. 28(1-2): p. 63-80. [DOI:10.1016/j.techsoc.2005.10.005]

3. Dou, Y., et al., Urban land extraction using VIIRS nighttime light data: An evaluation of three popular methods. Remote Sensing, 2017. 9(2): p. 175. [DOI:10.3390/rs9020175]

4. Liu, X., A. de Sherbinin, and Y. Zhan, Mapping urban extent at large spatial scales using machine learning methods with VIIRS Nighttime light and MODIS daytime NDVI data. Remote Sensing, 2019. 11(10): p. 1247. [DOI:10.3390/rs11101247]

5. Fraser, C., Network Design in Close-range Photogrammetry and Machine Vision. Atkinson (Ed.), 1996: p. 256-282.

6. Fraser, C. Design imperatives in digital non-topographic photogrammetry. in Proceedings of 2nd Turkish-German Joint Geodetic Days Conference. 1997. Technical University of Berlin.

7. Olague, G., Automated photogrammetric network design using genetic algorithms. 2002. [DOI:10.1007/3-540-45365-2_37]

8. Mason, S., Expert system-based design of close-range photogrammetric networks. ISPRS Journal of Photogrammetry and Remote Sensing, 1995. 50(5): p. 13-24. [DOI:10.1016/0924-2716(95)90117-W]

9. Saadatseresht, M., et al., Visibility analysis in vision metrology network design. The Photogrammetric Record, 2004. 19(107): p. 219-236. [DOI:10.1111/j.0031-868X.2004.00280.x]

10. Ibrahim, A., et al., Model-driven visual data capture on construction sites: Method and metrics of success, in Computing in Civil Engineering 2017. 2017. p. 109-116. [DOI:10.1061/9780784480847.014]

11. Gašparović, M. and D. Gajski. Two-step camera calibration method developed for micro UAV's. in XXIII ISPRS Congress. 2016. [DOI:10.5194/isprsarchives-XLI-B1-829-2016]

12. Gašparović, M. and L. Jurjević, Gimbal influence on the stability of exterior orientation parameters of UAV acquired images. Sensors, 2017. 17(2): p. 401. [DOI:10.3390/s17020401]

13. Gerke, M., Dense matching in high resolution oblique airborne images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 2009. 38: p. W4.

14. Hohle, J., Photogrammetric measurements in oblique aerial images. Photogrammetrie Fernerkundung Geoinformation, 2008. 2008(1): p. 7.

15. Remondino, F., et al., Oblique aerial imagery for NMA-some best practices. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016. 41: p. 639. [DOI:10.5194/isprs-archives-XLI-B4-639-2016]

16. Rupnik, E., F. Nex, and F. Remondino. Oblique multi-camera systems-orientation and dense matching issues. 2014. [DOI:10.5194/isprsarchives-XL-3-W1-107-2014]

17. Eisenbeiss, H. and M. Sauerbier, Investigation of UAV systems and flight modes for photogrammetric applications. The Photogrammetric Record, 2011. 26(136): p. 400-421. [DOI:10.1111/j.1477-9730.2011.00657.x]

18. Hernandez, D., et al., An Automatic Approach to UAV Flight Planning and Control for Photogrammetric Applications: A Test Case in the Asturias Region (Spain). Vol. Volume 79. 2013. Pages 87-98. [DOI:10.14358/PERS.79.1.87]

19. Wang, H., et al., Three-dimensional path planning for unmanned aerial vehicle based on interfered fluid dynamical system. Chinese Journal of Aeronautics, 2015. 28(1): p. 229-239. [DOI:10.1016/j.cja.2014.12.031]

20. González, V., et al., UAVs mission planning with flight level constraint using Fast Marching Square Method. Robotics and Autonomous Systems, 2017. 94: p. 162-171. [DOI:10.1016/j.robot.2017.04.021]

21. Manconi, A., et al., optimization of unmanned aerial vehicles flight planning in steep terrains. International Journal of Remote Sensing, 2019. 40(7): p. 2483-2492. [DOI:10.1080/01431161.2019.1573334]

22. Aicardi, I., et al., UAV PHOTOGRAMMETRY WITH OBLIQUE IMAGES: FIRST ANALYSIS ON DATA ACQUISITION AND PROCESSING. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 2016. 41. [DOI:10.5194/isprs-archives-XLI-B1-835-2016]

23. Chiabrando, F., et al., The influence of flight planning and camera orientation in UAVs photogrammetry. A test in the area of Rocca San Silvestro (LI), TUSCANY. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017. 42: p. 163. [DOI:10.5194/isprs-archives-XLII-2-W3-163-2017]

24. Poli, D., K. Moe, and R. Gasser, Growing Use of Oblique Imagery by Municipalities. GIM INTERNATIONAL-THE WORLDWIDE MAGAZINE FOR GEOMATICS, 2017. 31(7): p. 20-23.