When remote sensing meets topological data analysis

Duponchel, Ludovic

Type de document :

Article dans une revue scientifique: Article original

DOI :

10.1255/jsi.2018.a1

URL permanente :

http://hdl.handle.net/20.500.12210/57824

Titre :

When remote sensing meets topological data analysis

Auteur(s) :

Duponchel, Ludovic [Auteur]

Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516

Titre de la revue :

Journal of Spectral Imaging

Numéro :

Date de publication :

2018-02

Mot(s)-clé(s) en anglais :

remote sensing
hyperspectral imaging
topological data analysis
clustering
data models

Discipline(s) HAL :

Chimie/Chimie théorique et/ou physique

Résumé en anglais : [en]

Hyperspectral remote sensing plays an increasingly important role in many scientific domains and everyday life problems. Indeed, this imaging concept ends up in applications as varied as catching tax-evaders red-handed by ...
Lire la suite >Hyperspectral remote sensing plays an increasingly important role in many scientific domains and everyday life problems. Indeed, this imaging concept ends up in applications as varied as catching tax-evaders red-handed by locating new construction and building alterations, searching for aircraft and saving lives after fatal crashes, detecting oil spills for marine life and environmental preservation, spying on enemies with reconnaissance satellites, watching algae grow as an indicator of environmental health, forecasting weather to warn about natural disasters and much more. From an instrumental point of view, we can say that the actual spectrometers have rather good characteristics, even if we can always increase spatial resolution and spectral range. In order to extract ever more information from such experiments and develop new applications, we must, therefore, propose multivariate data analysis tools able to capture the shape of data sets and their specific features. Nevertheless, actual methods often impose a data model which implicitly defines the geometry of the data set. The aim of the paper is thus to introduce the concept of topological data analysis in the framework of remote sensing, making no assumptions about the global shape of the data set, but also allowing the capture of its local features.Lire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Établissement(s) :

CNRS
ENSCL
Université de Lille

Collections :

Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516

Équipe(s) de recherche :

Propriétés magnéto structurales des matériaux (PMSM)

Date de dépôt :

2021-11-16T08:23:41Z
2024-02-21T08:08:10Z

Numéro de version	Lien	Date de modification
2	20.500.12210/57824*	2024-02-21T08:06:36Z
1	20.500.12210/57824.1	2021-11-16T08:23:41Z

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When remote sensing meets topological data ...

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