Toward a general tropical forest biomass prediction model from very high resolution optical satellite images

Ploton Pierre, Barbier Nicolas, Couteron Pierre, Antin Cécile, Ayyappan Narayanan, Balachandran N., Barathan N., Bastin Jean-François, Chuyong George B., Dauby Gilles, Droissart Vincent, Gastellu Etchegorry Jean-Philippe, Kamdem Narcisse Guy, Kenfack David, Libalah Moses, Mofack Gislain II, Momo S.T., Pargal S., Petronelli Pascal, Proisy Christophe, Rejou-Mechain Maxime, Sonké Bonaventure, Texier Nicolas, Thomas Duncan, Verley Philippe, Zebaze Dongmo D., Berger Uta, Pélissier Raphaël. 2017. Toward a general tropical forest biomass prediction model from very high resolution optical satellite images. Remote Sensing of Environment, 200 : 140-153.

Quartile : Q1, Sujet : REMOTE SENSING / Quartile : Outlier, Sujet : IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY / Quartile : Q1, Sujet : ENVIRONMENTAL SCIENCES

Liste HCERES des revues (en SHS) : oui

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

Résumé : Very high spatial resolution (VHSR) optical satellite imagery has shown good potential to provide non-saturating proxies of tropical forest aboveground biomass (AGB) from the analysis of canopy texture, for instance through the Fourier Transform Textural Ordination method. Empirical case studies however showed that the relationship between Fourier texture features and forest AGB varies across forest types and regions of the world, limiting model transferability. A better understanding of the biophysical mechanisms on which canopy texture – forest AGB relation relies is a prerequisite to move toward broad scale applications. Here we simulated VHSR optical canopy scenes in identical sun-sensor geometry for 279 1-ha tropical forest inventory plots distributed across the tropics. Our aim was to assess the respective merits and complementarity of two types of texture analysis techniques (i.e. Fourier and lacunarity) on a set of forests with contrasted structure and geographical origin, and develop a general texture-based approach for tropical forest AGB mapping. Across forests, Fourier texture captured a gradient of stands mean crown size reflecting well the progressive changes in stand structure throughout forest aggradation phase (e.g. Pearson's r = − 0.42 with basal area) while lacunarity texture captured a gradient of canopy openness (, i.e. Pearson's r = − 0.57 with stand gap fraction). Both types of texture indices were highly complementary for predicting forest AGB at the global level (so-called FL-model). The residual error of the FL-model was structured across sites and could be partially captured with a bioclimatic proxy, further improving the performance of the global model (so-called FLE-model) and reducing site-level biases. The FLE model was tested on a set of real Pleiades images covering a mosaic of high-biomass forests in the Congo basin (mean AGB over 49 field plots: 359 ± 98 Mg ha− 1), leading to a significant relationship (R2 = 0.47 on validation data) with reasonable error levels (< 25% rRMSE). The increasing availability of VHSR optical sensors (such as from constellations of small satellite platforms) raises the possibility of routine repeated imaging of the world's tropical forests and suggests that texture-based analyses could become an essential tool in international efforts to monitor carbon emissions from deforestation and forest degradations (REDD +).

Mots-clés Agrovoc : forêt, forêt tropicale, biomasse, télédétection, imagerie par satellite, dynamique des populations, inventaire forestier, modèle de simulation, méthode statistique, ressource forestière

Mots-clés géographiques Agrovoc : Congo

Classification Agris : K01 - Foresterie - Considérations générales
U30 - Méthodes de recherche
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

• Ploton Pierre, IRD (FRA)
• Barbier Nicolas, IRD (FRA)
• Couteron Pierre, IRD (FRA)
• Antin Cécile, IRD (FRA)
• Ayyappan Narayanan, Institut français de Pondichéry (IND)
• Balachandran N., Institut français de Pondichéry (IND)
• Barathan N., Institut français de Pondichéry (IND)
• Bastin Jean-François, ULB (BEL)
• Chuyong George B., Université de Buéa (CMR)
• Dauby Gilles, IRD (FRA)
• Droissart Vincent, IRD (FRA)
• Gastellu Etchegorry Jean-Philippe, CESBIO (FRA)
• Kamdem Narcisse Guy, University of Yaounde 1 (CMR)
• Kenfack David, STRI (USA)
• Libalah Moses, University of Yaounde 1 (CMR)
• Mofack Gislain II, University of Yaounde 1 (CMR)
• Momo S.T., IRD (FRA)
• Pargal S., IRD (FRA)
• Petronelli Pascal, CIRAD-ES-UMR Ecofog (GUF)
• Proisy Christophe, IRD (FRA)
• Rejou-Mechain Maxime, IRD (FRA)
• Sonké Bonaventure, Université de Yaoundé (CMR)
• Texier Nicolas, IRD (FRA)
• Thomas Duncan, Washington State University (USA)
• Verley Philippe, IRD (FRA)
• Zebaze Dongmo D., Université de Yaoundé 1 (CMR)
• Berger Uta, Technische Universität Dresden (DEU)
• Pélissier Raphaël, IRD (FRA)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/585510/)

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