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Predicting biomass dynamics at the national extent from digital aerial photogrammetry / Bronwyn Price in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 90 (August 2020) . - n° 102116 Titre : Predicting biomass dynamics at the national extent from digital aerial photogrammetry Type de document : Article/Communication Auteurs : Bronwyn Price, Auteur ; Lars T. Waser, Auteur ; Zuyuan Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] hauteur de la végétation [Termes IGN] image aérienne [Termes IGN] indicateur de service écosystémique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier étranger (données) [Termes IGN] lasergrammétrie [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] photogrammétrie aérienne [Termes IGN] puits de carbone [Termes IGN] régression linéaire [Termes IGN] série temporelle [Termes IGN] Suisse [Termes IGN] surveillance écologique [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) The demand for precise mapping and monitoring of forest resources, such as above ground biomass (AGB), has increased rapidly. National accounting and monitoring of AGB requires regularly updated information based on consistent methods. While remote sensing technologies such as airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) have been shown to deliver the necessary 3D spatial data for AGB mapping, the capacity of repeat acquisition, remotely sensed, vegetation structure data for AGB monitoring has received less attention. Here, we use vegetation height models (VHMs) derived from repeat acquisition DAP data (with ALS terrain correction) to map and monitor woody AGB dynamics across Switzerland over 35 years (1983-2017 inclusive), using a linear least-squares regression approach. We demonstrate a consistent relationship between canopy height derived from DAP and field-based NFI measures of woody AGB across four inventory periods. Over the environmentally heterogeneous area of Switzerland, our models have a comparable predictive performance (R2 = 0.54) to previous work predicting AGB based on ALS metrics. Pearson correlation coefficients between measured and predicted changes in woody AGB over time increased with shorter time gaps ( Numéro de notice : A2020-717 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102116 Date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102116 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96292 [article]