Abstract:
Among all natural disasters, flood is identified as the most frequent natural hazard in Sri
Lanka, proved by its history as well. The climate of Sri Lanka is known as tropical
monsoon climate with mainly two monsoons periods: southwest and northwest. We have
witnessed during the period of last July 17-22, 2016 a strengthening of the upward trend,
with an average rate was increased in aspect of flood disasters, such as it had a
tremendously high human impact and caused high economic damages. The rapid response
mapping using satellite remote sensing technology is widely used where increasingly
preferred alternative option for emergency assessment and operation flood disaster
management efforts.
The research is to have an accurate and reliable flood area extraction for a large urban
area and extract flood area in Colombo during May 2016, using sentinel-1 C band single
polarization (VV) SAR data and to characterized the performance and the ability of the C
band VV polarization on flood effects. Urban flooding results in serious damages and stay
as a complex phenomenon to map due to the land use heterogeneity it associates. Here
the flood water is considered to be only calm water. Many flood mapping SAR algorithms
model open water as a perfect smooth surface which reflects most radiance away from
side-looking SAR sensors. Especially in urban areas SAR inevitably requires an oblique
scene illumination resulting in undesired occlusion and layover. The sentinel-1 mission is
expected to deliver a wealth of data and imagery.
In the context of floods to understand the backscatter behavior of various semantic
classes a series of histograms representing the class backscatter coefficients were
generated. These histograms were used to determine the backscatter threshold values
between water and the non-water regions. The change detection was performed between
the two images by using a contextual Mean Ratio Detector considering second order pixel
neighboring system. The results were compared with the reference map generated by
using field data, and the correlation coefficients for the sample area were in the range of
0.7 to 0.8 with high agreement. Further the visual interpretation suggests the level of
details using the C band SAR data is significantly higher than the ground based
interpretation.
