Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 191-195, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-191-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 191-195, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-191-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

POST-HURRICANE DAMAGE ASSESSMENT ON GREENHOUSE FIELDS WITH USE OF SAR DATA

N. Demir1, Y. E. Eryilmaz2, and S. Oy1 N. Demir et al.
  • 1Akdeniz University, Space Science, and Technologies, 07058 Konyaaltı Antalya, Turkey
  • 2Akdeniz University, Remote Sensing and Geographic Information Systems, 07058 Konyaaltı Antalya, Turkey

Keywords: SAR, Tornadoes, Disaster Management, Greenhouses, Remote Sensing, SENTİNEL

Abstract. Hurricanes occur without any control of human-being, and it causes large scale loss of life and properties. They happen in the very short timeline and cannot be stopped by the people after it starts to occur. Therefore, the damage has to be assessed just after the disaster for an effective management. Radar images have advantages since the radar sensor can operate in all weather conditions, not be affected by the clouds, therefore use of SAR imagery is useful to identify the damage and loss of properties. In our study, Antalya-Kumluca region has been selected, because a hurricane has occurred on 13th November 2017 and caused large damages especially in agricultural fields where there are lots of greenhouses. Two Sentinel 1A (S1A) images have been used, one from the pre-disaster period and the other is from the post-disaster period. Backscatter values are analyzed in both images. It is expected that the difference between dB values are expected to be larger than the dB value of the pre-disaster period, in case a large-scale damage happened. The fields which were affected by the disaster were found and compared with the Sentinel 2A (S2A) multispectral images to validate the occurred loss. The results show a high match between the detected damages in SAR image and the identical effected fields on multispectral image from the post-disaster period.