Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 307-312, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-307-2018
© 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, 307-312, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-307-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

FLASH FLOOD MAPPING FOR MOUNTAIN STREAMS USING HIGH-RESOLUTION ALOS-2 DATA

Y-J Kwak Y-J Kwak
  • International Centre for Water Hazard and Risk Management (ICHARM-UNESCO), Public Works Research Institute (PWRI) 1-6 Minamihara, Tsukuba, Japan

Keywords: ALOS-2, Capacity building, Flood detection, Valley floodplain

Abstract. This paper introduces a practical way to improve the risk management capacity and resilience of communities by utilizing a prompt flash flood map produced from very high spatial resolution ALOS-2 data. An improved flood detection algorithm is proposed to achieve a better discrimination capacity to identify flooded areas in the valley floodplain based on cluster analysis by verifying training sites and understanding pixel-based backscattering behaviour focusing on surface roughness changes caused by floodwater and floating debris, i.e., mud flow with gravels, stones and uprooted trees. The results show the possibility of a rapid, straightforward change detection approach to flood mapping, in particular to identify and classify floodwaters, damaged buildings, damaged rice fields, and stacks of driftwood through evidenced-based investigation.