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ERS INSAR data for remote sensing hilly forested areas

Castel Thierry, Martinez Jean-Michel, Beaudoin André, Wegmüller Urs, Strozzi Tazio. 2000. ERS INSAR data for remote sensing hilly forested areas. Remote Sensing of Environment, 73 : pp. 73-86.

Journal article ; Article de revue à facteur d'impact
Full text not available from this repository.

Autre titre : L'utilisation de données INSAR ERS pour la télédétection dans des zones forestières montagneuses

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Géographie-Aménagement-Urbanisme-Architecture

Abstract : ERS INSAR data have proved to be of interest for forest applications. The interferometric coherence was found to be related to various land uses and forest types, while in some special cases (e.g., flat terrain) the interferometric phase has been linked to the forest height. This paper reports an investigation on the information content of the interferometric coherence over a hilly terrain supporting various land use types and large pine plantations. The approach includes the use of a Geographic Information System and multitemporal data to analyze the coherence behavior as a function of forest-type forest parameters and environmental factors such as meteorological and topographic effects. Coherence appears to be efficient to discriminate between forest types. However, topography and environmental conditions strongly affect the coherence and its estimation, pointing out the need for rejection of strong slopes areas (>15°) and the sensitivity to local mteorological/seasonal effects. Based on these observations, forest classification results are presented. Forest/nonforest discrimination is very efficient (accuracy >90%) using one-day interval acquisition. More detailed classification with discrimination between forest themes gives also good results. Then, we investigate the indirect link between coherence and forest parameters. The coherence is sensitive to the forest growth stage, making forest parameter retrieval possible using a simple straight-line model. Finally, the importance of wind upon temporal decorrelation is addressed, and a semiempirical correction is proposed. (Résumé d'auteur)

Mots-clés Agrovoc : Télédétection, Radar, Système d'information géographique, Forêt, Pâturages, Terre en pente, Utilisation des terres, Modèle mathématique, Vent, Biomasse

Mots-clés géographiques Agrovoc : France

Classification Agris : U30 - Research methods
K10 - Forestry production
E11 - Land economics and policies

Auteurs et affiliations

  • Castel Thierry, CIRAD-AMIS-AMAP (FRA)
  • Martinez Jean-Michel, LCT (FRA)
  • Beaudoin André, LCT (FRA)
  • Wegmüller Urs, Gamma Remote Sensing (CHE)
  • Strozzi Tazio, Gamma Remote Sensing (CHE)

Autres liens de la publication

Source : Cirad - Agritrop (https://agritrop.cirad.fr/475946/)

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