Exploration of the OBIA methods available in SPRING noncommercial software to UAV data processing

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 9245, Issue , 2014, Pages

  Teodoro, A C ^a   Araujo R ^a  

^a UNIVERSITY OF PORTO   (Portugal)

Author keywords

OBIA; SPRING software; UAV

Indexed keywords

ALGORITHMS; DATA HANDLING; DATA MINING; IMAGE PROCESSING; PIXELS; REMOTE SENSING; UNMANNED AERIAL VEHICLES (UAV);

DATA MINING ALGORITHM; IMAGE PROCESSING TECHNIQUE; OBIA; OBJECT-BASED IMAGE CLASSIFICATION; PARAMETER COMBINATION; PIXEL BASED CLASSIFICATIONS; SUPERVISED CLASSIFICATION; UNSUPERVISED CLASSIFICATION;

IMAGE CLASSIFICATION;

EID: 84923074003     PISSN: 0277786X     EISSN: 1996756X     Source Type: Conference Proceeding    
DOI: 10.1117/12.2066468     Document Type: Conference Paper

References (23)

1. Díaz-Pacheco, J., García-Palomares, J. C., "A highly detailed land use vector map for Madrid region based on photo-interpretation", Journal of Maps 10(3), 424-433 (2014).
2. Youying Z., Hongxia, C. "Techniques of UAV system land use changes detection application", Proc. SPIE 7752, PIAGENG 2010: Photonics and Imaging for Agricultural Engineering 77520X (2011).
3. Teodoro, A. C., Pais-Barbosa, J., Gonçalves, H., Veloso-Gomes, F., Taveira-Pinto, F., "Identification of beach features/patterns through image classification techniques applied to remotely sensed data", International Journal of Remote Sensing 32(22), 7399-7422 (2011).
4. Teodoro, A. C. and Gonçalves, H., "A semi-automatic approach for the extraction of sandy bodies (sand spits) from IKONOS-2 data", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5(2), 634-642 (2012).
5. Jin, X., Davis, C. H., "An integrated system for automatic road mapping from high-resolution multispectral satellite imagery by information fusion", Int. J. Inform. Fusion 6, 257-273 (2005).
6. Bryson, M., Reid, A., Ramos, F., Sukkarieh, S., "Airborne vision-based mapping and classification of large farmland environments", J. Field Robot. 27, 632-655 (2010).
7. Ma, L., Cheng, L., Han, W., Zhong, L., Li, M., "Cultivated land information extraction from high-resolution unmanned aerial vehicle imagery data", J. Appl. Remote Sens. 8(1), 083673 (2014).
8. Garcia-Ruiz, F., Sankaran, S., Maja, J. M., Lee, W. S., Rasmussen, J., Ehsani, R., "Comparison of two aerial imaging platforms for identification of Huanglongbing-infected citrus trees", Comput. Electron. Agric. 91, 106-115 (2013).
9. Torres-Sánchez, J., Peña, J. M., De Castro, A. I., López-Granados, F., "Multi-temporal mapping of the vegetation fraction in early-season wheat fields using images from UAV", Computers and Electronics in Agriculture 103, 104-113 (2014).
10. Dong, G., Zhang Y. and Fan Y., "Remote Sensing Image Classification Algorithm Based on Rough Set Theory", B.-Y. Cao (Ed.): Fuzzy Information and Engineering (ICFIE) 40, 846-851 (2007).
11. Hung, C., Yiwen, H., Coleman, T. and Qian, K., "A spatial classification algorithm using peer group pixels", Proceedings of Geoscience and Remote Sensing Symposium (IGARSS) 6, 3405-3407 (2002).
12. Gonzalez, R. C. and Woods, R. E. [Digital Image Processing, 3nd ed.], Prentice Hall, ISBN 978-0131687288, Upper Saddle River, NJ (2008).
13. Oliveira, H. N. B., Bello, O. R. P., Geus, K., "Segmentation and classification of Landsat TM images to monitor the soil use", International Archives of Photogrammetry and Remote Sensing XXXIII (B7), 1065-1072 (2000).
14. Marghany, M. and Hashim, M., "Comparison between Mahalanobis classification and neural network for oil spill detection using RADARSAT-1 SAR data", International Journal of the Physical Sciences 6(3), 566-576 (2011).
15. Smits, P. C., Dellepiane, S. G. and Schowengerdt, R. A., "Quality assessment of image classification algorithms for land-cover mapping: a review and a proposal for a cost-based approach", International Journal of Remote Sensing, 20(8), 1461-1486 (1999).
16. Congalton, R. G., Mead, R. A., "A quantitative method to test for consistency and correctness in photointerpretation", Photogrammetric Engineering and Remote Sensing 49, 69-74 (1983).
17. Ma, Z., Redmond, R L., "Tau coefficients for accuracy assessment of classification of remote sensing data", Photogrammetric Engineering & Remote Sensing 61(4), 435-439 (1995).
18. Næsset, E., "Conditional tau coefficient for assessment of producer's accuracy of classified remotely sensed data", ISPRaS Journal of Photogrammetry & Remote Sensing 51(2), 91-98 (1996).
19. Ventura, S. J., Irvin, B. J., [Automated landform classification methods for soil-landscape studies], In J P Wilson and J Gallant, editors, Terrain analysis: principles and applications 267-294. Wiley & Sons, New York (2000).
20. SPRING, [Spring 5.1.2, passo a passo-aplicações práticas], Santos, A., Peluzio, T., and Saito, N. (Eds), Alegre, ES (2010).
21. Painho, M. and Caetano, M., [Cartografia de ocupação do solo Portugal continental 1985-2000-CORINE Land Cover 2000]. Instituto do Ambiente (Eds), ISBN: 972-8577-27-3 (2005).
22. Corine land cover update 2000, [Technical report]. EEA European Environment Agency (2002).
23. Corine land cover 1994, [Technical report]. EEA European Environment Agency (1994).