1 / 8

Revised RNL floodmap

This study presents a refined flood mapping approach utilizing 25m x 25m pixels, with significant speckle reduction and user-defined endmembers through Spectral Angle Mapper (SAM). The analysis results in the merging of 17 SAM classes into five distinct categories, applying varied thresholds to characterize flood states accurately. The methodology includes a flood duration maximum span map and distinguishes between always-flooded, sometimes-flooded, and never-flooded areas. A histogram illustrates the distribution of maximum flooded dates, capturing both wild variability and consistent patterns in flooding dynamics.

masako
Download Presentation

Revised RNL floodmap

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Revised RNL floodmap • Pixels 25m x 25m binned 4:1 • Speckle reduced significantly. No other filter applied. • SAM has 10 endmembers user-defined • Plus 7 statistically derived from n-D • Grown but less unclass to start with • No unclassified pixels once grown • 17 SAM classes merged into 5 classes • Threshold applied to two classes • Threshold varied (0.20 and 0.18 sigma0) • Flood total dates map • Flood duration maximum span map

  2. Mixed, not-well-characterized varfl Nf or impenetrable forest Always flooded, sometimes emergent. Varfl Always flooded, always emergent Grown 5-class combination made from 17-class SAM. Only varfl vary their flood state.

  3. never sometimes always always The transition from never flooded thru sometimes flooded space and into always-flooded space is arranged in a believable way. In this example, some always-flooded submergable class is surrounded by always-flooded emergent class which is bordering on sometimes-flooded emergent which borders on never-flooded or impenetrable. Mixed, not-well-characterized varfl Nf or impenetrable forest Always flooded, sometimes emergent. Varfl Always flooded, always emergent

  4. Flood maximum span of dates Flood dates total in 2 years

  5. Max span of dates flooded, for each pixel. Histogram for the varfl class: distribution of max span of dates flooded.

  6. This small class “wildly-varying varfl” is a mixture. This class is 1/3 of 1 percent of the regular varfl class. It contains sometimes-flooded areas and also always-flooded areas.

More Related