A Regularization Method for Landslide Thickness Estimation

Lisa Borgatti, Davide Donati, Liwei Hu, Germana Landi, Fabiana Zama, Giuseppe Amato · 2024

Read A Regularization Method for Landslide Thickness Estimation by Lisa Borgatti, Davide Donati, Liwei Hu, Germana Landi, Fabiana Zama, Giuseppe Amato (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11678178.txt.

Description

Lisa Borgatti and co-authors give in 2024 a math method to gauge how thick a landslide is from height data shot from space. True depth is a core need for hazard calls and safety work. Mass balance turns the depth task into a reverse math task with many fits.

Their fix picks smooth fits and tunes the trade off with a balance rule. Fake data sets with known depth test the method at split noise loads. It held up well as noise rose. On a real slide in Alaska, the depth map matched past geology reads, which backs its field worth.

Catalog record

CREATORLisa Borgatti, Davide Donati, Liwei Hu, Germana Landi, Fabiana Zama, Giuseppe Amato
YEAR2024
COLLECTIONPAPERS
FORMATTXT
FILE SIZE41 KB
VERSION1.0
LICENSECC BY 4.0
RIGHTSCC BY
SOURCEEurope PMC

Source: https://europepmc.org/articles/PMC11678178

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