Geoinformatics Unit

Preliminary Flood Mapping Following Torrential Rain in Iran on March 21, 2019

March 24, 2019

Torrential rain on 21 March 2019 hits the northern part of Iran, leaving local people homeless in the Golestan province. Although the capital of the Golestan province (Gorgan city) is situated too far from the inundated area, Aqqala town has been seriously affected. Most of the agricultural lands in this region have been drowned and according to the authorities at least two people have killed due to the triggered landslides (reference: https://www.presstv.com/Detail/2019/03/23/591706/Iran-floods-Mazandaran-Golestan)

We detected the flooded areas using two Sentinel-1 images in IW mode before (2019.03.11) and after (2019.03.23) the event and the land use map of Iran. Figure 1 shows the RGB color map and the inundated areas (yellowish areas) in the northern part of Iran.

In Figure 2, RGB InSAR coherence map shows the urban changes in the northern part of Iran (especially Aqqala town) using multitemporal InSAR analysis. A normalized difference in InSAR coherence (pre-event - post-event) is considered in red band to reflect building changes as "forward change" and a normalized difference in InSAR coherence (post-event - pre-event) in green band might reflect some characteristics of vegetation growth or post-event human changes (reverse change). The average value of two InSAR coherence products in blue band means "no change". Urban areas were illuminated by Global Urban Footprint (GUF).

Reference: Karimzadeh, S., Matsuoka, M., 2018. Building Damage Characterization for the 2016 Amatrice Earthquake Using Ascending-Descending COSMO SkyMed Data and Topographic Position Index. Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 11 (8), 2668-2682 , doi: 10.1109/JSTARS.2018.2825399

Figure 1. The RGB color map and the inundated areas (yellowish areas) in the northern part of Iran.

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Figure 2. RGB InSAR coherence map shows the urban changes in the northern part of Iran (especially Aqqala town) using multitemporal InSAR analysis.