Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 583-588, 2015
https://doi.org/10.5194/isprsarchives-XL-3-W3-583-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
20 Aug 2015
IQPC 2015 TRACK: WATER DETECTION AND CLASSIFICATION ON MULTISOURCE REMOTE SENSING AND TERRAIN DATA
A. Olasz1, D. Kristóf1, M. Belényesi1, K. Bakos1, Z. Kovács2, B. Balázs2, and Sz. Szabó2 1FÖMI, Institute of Geodesy, Cartography and Remote Sensing, 1149 Budapest, Hungary
2Department of Physical Geography and Geoinformation Systems, University of Debrecen, Hungary
Keywords: IQmulus Processing Contest, Remote Sensing, Water detection and classification, Multi-source remote sensing data processing, Resource optimization, R programming Abstract. Since 2013, the EU FP7 research project “IQmulus” encourages the participation of the whole scientific community as well as specific user groups in the IQmulus Processing Contest (IQPC). This year, IQPC 2015 consists of three processing tasks (tracks), from which “Water detection and classification on multi-source remote sensing and terrain data” is introduced in the present paper. This processing track addresses a particular problem in the field of big data processing and management with the objective of simulating a realistic remote sensing application scenario. The main focus is on the detection of water surfaces (natural waters, flood, inland excess water, other water-affected categories) using remotely sensed data. Multiple independent data sources are available and different tools could be used for data processing and evaluation. The main challenge is to identify the right combination of data and methods to solve the problem in the most efficient way. Although the first deadline for submitting track solutions has passed and the track has been successfully concluded, the track organizers decided to keep the possibility of result submission open to enable collecting a variety of approaches and solutions for this interesting problem.
Conference paper (PDF, 1233 KB)


Citation: Olasz, A., Kristóf, D., Belényesi, M., Bakos, K., Kovács, Z., Balázs, B., and Szabó, Sz.: IQPC 2015 TRACK: WATER DETECTION AND CLASSIFICATION ON MULTISOURCE REMOTE SENSING AND TERRAIN DATA, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-3/W3, 583-588, https://doi.org/10.5194/isprsarchives-XL-3-W3-583-2015, 2015.

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