A-
A
A+

L'information grandeur nature

Centre de documentation
scientifique

Actualité

L'actu ! Horaires du CDOS

Le centre est ouvert en salle de travail du lundi au vendredi, de 08h30 à 19h00. Les prêts physiques sont suspendus pour le moment. Merci d'adr...

Consulter les archives

dernière publication

Dernière publication Consultez les parutions du CDoS

Informations pratiques

Le centre de documentation scientifique
de l'Institut est aussi celui de l'ENSG-Géomatique.

Envoyez un mail au contact ci-dessous pour vos demandes.

Contact : cdos@ign.fr

Comment venir ?
Pour se rendre au centre de documentation, se reporter au 'Plan d'accès au bâtiment' tout en bas de page à droite. Le centre se trouve dans le bâtiment de l'ENSG. On y accède par le hall, entre l'aile Cassini et l'aile Laplace.

Mots RAMEAU représentant le fonds du centre de documentation
géomatique, géodésie, réseaux (géodésie), systèmes de localisation par satellites,
imagerie satellitaire, traitement d'images, photogrammétrie, lasergrammétrie,
systèmes d'information géographique, données géospatiales, cartographie,
géographie - base de données

Nouvelle recherche

Article: Article/Communication

An open science and open data approach for the statistically robust estimation of forest disturbance areas / Saverio Francini in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)

URL article

Public

[article]
inInternational journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102663

Titre :	An open science and open data approach for the statistically robust estimation of forest disturbance areas
Type de document :	Article/Communication
Auteurs :	Saverio Francini, Auteur ; Ronald E. McRoberts, Auteur ; Giovanni d' Amico, Auteur ; et al., Auteur
Année de publication :	2022
Article en page(s) :	n° 102663
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes IGN] changement climatique [Termes IGN] coupe rase (sylviculture) [Termes IGN] détection de changement [Termes IGN] estimation statistique [Termes IGN] Fagus sylvatica [Termes IGN] Google Earth Engine [Termes IGN] image Sentinel-MSI [Termes IGN] Italie [Termes IGN] méthode robuste [Termes IGN] perturbation écologique [Termes IGN] Quercus cerris [Termes IGN] Quercus pedunculata [Termes IGN] Quercus pubescens [Termes IGN] Quercus sessiliflora [Termes IGN] surveillance forestière
Résumé :	(auteur) Forest disturbance monitoring is critical for understanding forest-related greenhouse gas emissions and for determining the role of forest management in mitigating climate change. Multiple algorithms for the automated mapping of forest disturbance using remotely sensed imagery have been developed and applied; however, variability in natural and anthropogenic disturbance phenomena, as well as image acquisition conditions, can result in maps that may be incomplete or that contain inaccuracies that prevent their use for directly estimating areas of disturbance. To reduce errors in reporting disturbance areas, stratified estimators can be applied to obtain statistically robust area estimates, while simultaneously circumventing the need to conduct a complete census or in situations where such a census may not be possible. We present a semi-automated procedure for implementation in Google Earth Engine, 3I3D-GEE, for regional to global mapping of forest disturbance (including clear-cut harvesting, fire, and wind damage) and sample-based estimation of related areas using data from the processing capacity of Google Earth Engine. Documentation for the application is also provided in Appendix A. Using Sentinel-2 (S2) imagery, our procedure was applied and tested for 2018 in Italy for which the approximately 11 million ha of forests (mostly Q. pubescens, Q. robur, Q. cerris, Q. petraea, and Fagus sylvatica) serve as an appropriate case study because national statistics on forest disturbance areas are not available. To decrease the overall standard errors of the area estimates, the sampling intensities in areas where greater variability in the form of greater commission and omission errors are expected can be increased. To this end, we augmented the predicted forest disturbance map with a buffer class consisting of a two-pixel buffer (20 m) on each side of the disturbance class boundary. We selected a reference sample of 19,300 points: a simple random sample of 9,300 points from the buffer and simple random samples of 5000 from each of the undisturbed and disturbed classes. The reference sample was photointerpreted using fine resolution orthophotos (30 cm) and S2 imagery. While the estimate of the disturbed area obtained by adding the areas of pixels classified as disturbed was 41,732 ha, the estimate obtained using the unbiased stratified estimator was 27% greater at 57,717716 ha. Regarding map accuracy, we found several omission errors in the buffer (53.4%) but none (0%) in the undisturbed map class. Similarly, among the 1035 commission errors, the majority (7 4 4) were in the buffer class. The methods presented herein provide a useful tool that can be used to estimate areas of forest disturbance, which many nations must report as part of their commitment to international conventions and treaties. In addition, the information generated can support forest management, enabling the forest sector to monitor stand-replacing forest harvesting over space and time.
Numéro de notice :	A2022-072
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Article
DOI :	10.1016/j.jag.2021.102663
En ligne :	https://doi.org/10.1016/j.jag.2021.102663
Format de la ressource électronique :	URL article
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=99437

vignette

IGN

IGN / ENSG

Centre de documentation
scientifique
6 et 8 Avenue Blaise Pascal
Cité Descartes
Champs-sur-Marne
77455 Marne la Vallée
Cedex 2
L'IGN a pour vocation

de décrire la surface du territoire national et l'occupation de son sol, et d'élaborer et de mettre à jour l'inventaire permanent des ressources forestières nationales.
Accès directs
2014 -2024 IGN