1 / 7

Understanding Flood Classification Using Sigma0 Thresholds in Multi-Temporal RADARSAT Imagery

This presentation outlines the results of flood classification based on RADARSAT multi-temporal cube analysis. It discusses the interpretation and application of sigma0 thresholds to differentiate various land classes affected by flooding, illustrating the unique DN (Digital Number) representations for each class compared to previous models. Key insights include the behavior of specific classes such as flooded forests, sandbars, and the significance of color coding in RADARSAT imagery. The discussion addresses the complexity of classifying regions accurately, especially concerning the presence of seasonally flooded areas.

ulani
Download Presentation

Understanding Flood Classification Using Sigma0 Thresholds in Multi-Temporal RADARSAT Imagery

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. Filename: Itu_learn_classes_captions.ppt Directory: LBA24/RADARSAT/neg/neg_w_f450/sig/classif/flood/thresh/ Orig date: 22 Nov 2006 Modified date: 20 Dec 2006 By MGB Description of the classification result and how it is interpreted and used to map flooding.

  2. Ready to apply sigma0 threshold to multi-temporal radarsat cube. • But first, which classes are which? • They are different DN than for RNL. • Before RNL Now Itu • DN color class DN color class • 1Red varfl 1 red always fl river • 2green always fl 2 coral always fl sandbar • 3blue always fl 3 purple always fl unk • 4yellow varfl 4 magenta varfl • 5cyan always fl 5 cyan ____ check this • 6magenta varfl 6 green never fl uplandish for • 7maroon varfl 7 yellow varfl floodable forest • 8grey mask 8 grey mask But wait! Sandbars are not always flooded. The sigma0 threshold does not apply well to sandbars. Start with last version of RNL threshold flood map script, the one that includes a never-flooded class.

  3. The cyan class is NPV in Jan TM and flooded in May TM. It is bright all seasons in Radarsat. So I’d say it is flooded and either sparse trunks or leafless trunks. The cyan class blends with the purple class which darkens as depth increases indicating a submergable class. So I’d venture that the cyan is like the purple only the stalks are taller or the terrain is not as low. Then the magenta is on the bounds of the cyan. Perhaps the magenta is higher ground that is dries at low water.

  4. These side-by-side image segments indicate that the cyan class is always flooded, along with the purple class. In the Jan TM the cyan class is the darkest part of the NPV (orangey) patch. And it is always-bright (white) in the seasonal radarsat image.

More Related