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Forest degradation and biomass loss along the Chocó region of Colombia / Victoria Meyer in Carbon Balance and Management, vol 14 (March 2019)
[article]
Titre : Forest degradation and biomass loss along the Chocó region of Colombia Type de document : Article/Communication Auteurs : Victoria Meyer, Auteur ; Sassan Saatchi, Auteur ; António Ferraz , Auteur ; Liang Xu, Auteur ; Duque Alvaro, Auteur ; Mariano Garcia, Auteur ; Mariano Chave, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Colombie
[Termes IGN] densité du bois
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] dynamique de la végétation
[Termes IGN] dynamique spatiale
[Termes IGN] forêt tropicale
[Termes IGN] hauteur de la végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] semis de pointsRésumé : (auteur) Background: Wet tropical forests of Chocó, along the Pacific Coast of Colombia, are known for their high plant diversity and endemic species. With increasing pressure of degradation and deforestation, these forests have been prioritized for conservation and carbon offset through Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanisms. We provide the first regional assessment of forest structure and aboveground biomass using measurements from a combination of ground tree inventories and airborne Light Detection and Ranging (Lidar). More than 80,000 ha of lidar samples were collected based on a stratified random sampling to provide a regionally unbiased quantification of forest structure of Chocó across gradients of vegetation structure, disturbance and elevation. We developed a model to convert measurements of vertical structure of forests into aboveground biomass (AGB) for terra firme, wetlands, and mangrove forests. We used the Random Forest machine learning model and a formal uncertainty analysis to map forest height and AGB at 1-ha spatial resolution for the entire pacific coastal region using spaceborne data, extending from the coast to higher elevation of Andean forests.
Results: Upland Chocó forests have a mean canopy height of 21.8 m and AGB of 233.0 Mg/ha, while wetland forests are characterized by a lower height and AGB (13.5 m and 117.5 Mg/a). Mangroves have a lower mean height than upland forests (16.5 m), but have a similar AGB as upland forests (229.9 Mg/ha) due to their high wood density. Within the terra firme forest class, intact forests have the highest AGB (244.3 ± 34.8 Mg/ha) followed by degraded and secondary forests with 212.57 ± 62.40 Mg/ha of biomass. Forest degradation varies in biomass loss from small-scale selective logging and firewood harvesting to large-scale tree removals for gold mining, settlements, and illegal logging. Our findings suggest that the forest degradation has already caused the loss of more than 115 million tons of dry biomass, or 58 million tons of carbon.
Conclusions: Our assessment of carbon stocks and forest degradation can be used as a reference for reporting on the state of the Chocó forests to REDD+ projects and to encourage restoration efforts through conservation and climate mitigation policies.Numéro de notice : A2019-625 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s13021-019-0117-9 Date de publication en ligne : 23/03/2019 En ligne : https://doi.org/10.1186/s13021-019-0117-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95368
in Carbon Balance and Management > vol 14 (March 2019)[article]Quantifying spatiotemporal post‐disturbance recovery using field inventory, tree growth, and remote sensing / Shengli Huang in Earth and space science, vol 6 n° 3 (March 2019)
[article]
Titre : Quantifying spatiotemporal post‐disturbance recovery using field inventory, tree growth, and remote sensing Type de document : Article/Communication Auteurs : Shengli Huang, Auteur ; C. Ramirez, Auteur ; M. McElhaney, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 489 - 504 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne
[Termes IGN] croissance végétale
[Termes IGN] Etats-Unis
[Termes IGN] indice de végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Forest recovery following a disturbance lasts decades to centuries, and the rate depends on pre‐ and post‐disturbance condition and local environmental factors. Existing approaches of field observations, remote sensing, statistical chronosequence, and ecological modeling have one or more drawbacks, including short time frames, generalized details, indirect indicators, hard parameterization, and defective assumptions. Using aboveground live biomass (AGLB) as an example, we developed an approach called “Disturbance and Recovery Assessment across Space and Time (DRAST).” For a specific post‐disturbance year, DRAST utilizes Field Inventory and Analysis data sets and the Forest Vegetation Simulator, as well as pre‐ and post‐disturbance remote sensing to create two rasters: (1) what the AGLB would look like over the disturbed area had the disturbance not occurred and (2) what the AGLB would look like over the disturbed area in the actual presence of the disturbance. These two rasters are compared annually to examine the spatiotemporal recovery pattern. We demonstrated DRAST with the 2013 Rim fire in California, United States, by creating two sets of AGLB for 100 years. Our results showed that (1) the AGLB consumed by Rim fire was 3.52 Tg and (2) 45.9% of the burned area needs 95 years), 5.9% (10–15 years), 5.4% (15–20 years), 4.8% (20–25 years), and 4.3% (25–30 years). In conclusion, DRAST can provide spatially explicit and highly detailed ecological indicators for decades under the two scenarios of “no disturbance” and “actual disturbance occurrence” for recovery analysis. Numéro de notice : A2019-402 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1029/2018EA000489 Date de publication en ligne : 25/03/2019 En ligne : https://doi.org/10.1029/2018EA000489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93504
in Earth and space science > vol 6 n° 3 (March 2019) . - pp 489 - 504[article]Generation of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar / Yang Lei in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)
[article]
Titre : Generation of large-scale moderate-resolution forest height mosaic with spaceborne repeat-pass SAR interferometry and lidar Type de document : Article/Communication Auteurs : Yang Lei, Auteur ; Paul Siqueira, Auteur ; Nathan Torbick, Auteur ; Mark J. Ducey, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 770 - 787 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bande L
[Termes IGN] biomasse aérienne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] image ALOS-PALSAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] Maine (Etats-Unis)
[Termes IGN] New Hampshire (Etats-Unis)Résumé : (Auteur) This paper provides an overview of the scattering model, inversion approach, and validation of the application results for creating large-scale moderate-resolution (hectare-level) mosaics of forest height through using spaceborne repeat-pass SAR interferometry and lidar. By incorporating several improvements to the forest height inversion and mosaicking approach, the height estimation accuracy along with the robustness of this approach have been considerably enhanced from its originally reported accuracy of RMSE of 3-4 m at a 20-hectare aggregated pixel size to RMSE of 3-4 m on the order of 3-6 hectares. Furthermore, practical data processing schemes are provided in detail. Extensive validation results are demonstrated which include: 1) a forest height mosaic (total area of 11.6 million hectares) is generated for the U.S. states of Maine and New Hampshire using Japanese Aerospace Exploration Agency's (JAXA) ALOS-1 InSAR correlation data and a small airborne lidar strip (44 000 hectares); 2) the mosaic height estimates are further compared with the available airborne lidar data and field measurements over both flat and mountainous areas; and 3) feasibility of using modern repeat-pass InSAR satellites with short repeat interval is also examined by using JAXA's ALOS-2 data. This simple and efficient approach is a potential observational prototype with much smaller error budget for the future spaceborne repeat-pass L-band InSAR systems with small spatial baseline and moderate/large temporal baseline (such as NISAR) in combination with lidar (such as GEDI) on the application of large-scale forest height/biomass mapping. It also serves as a complementary tool to the spaceborne single-pass InSAR systems using InSAR/PolInSAR methods when full-pol data are not available and/or when the underlying topography slope causes problems for these approaches. Numéro de notice : A2019-109 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2860590 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2860590 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92427
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 2 (February 2019) . - pp 770 - 787[article]TanDEM-X digital surface models in boreal forest above-ground biomass change detection / Kirsi Karila in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)
[article]
Titre : TanDEM-X digital surface models in boreal forest above-ground biomass change detection Type de document : Article/Communication Auteurs : Kirsi Karila, Auteur ; Xiaowei Yu, Auteur ; Mikko Vastaranta, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 174 - 183 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] densité de la végétation
[Termes IGN] détection de changement
[Termes IGN] données localisées 3D
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] hauteur des arbres
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] MNS TerraSAR & TanDEM-X
[Termes IGN] modèle numérique de surfaceRésumé : (Auteur) Satellite images provide spatially explicit information on forest change covering wide areas. In this study, bistatic TanDEM-X (TDX) synthetic aperture radar (SAR) satellite data were used to derive digital surface models (DSMs) of forest areas using SAR interferometry (InSAR). The capability of change features derived from bi-temporal InSAR DSMs to detect forest height (90th percentile of canopy height distribution, H90) and density variations was investigated. Moreover, changes in the forest above-ground biomass (AGB) were estimated from height changes between two InSAR DSMs. Bi-temporal airborne laser scanning (ALS) data, aerial orthoimages and an ALS-based AGB change map from a study area in Southern Finland were used as references. The results indicate that the InSAR height change of a forested area correlates more with vegetation density change than with height change. The correlation between the InSAR mean height change and the height change feature from ALS was 0.76 at stand level. Correspondingly, the correlation between the InSAR mean height change and the ALS penetration rate change was 0.89. The AGB changes predicted based on InSAR height change agreed well with the reference data; the root-mean-square error (RMSE) was 20.7 Mg/ha (18.5% of the mean biomass in 2012) at stand level and 27.4 Mg/ha (27.0%) for 16 × 16 m grid cells. The results show that TDX DSMs can be used to detect biomass changes of different orders of magnitude, e.g. due to logging and thinning. Numéro de notice : A2019-073 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.01.002 Date de publication en ligne : 11/01/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.01.002 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92160
in ISPRS Journal of photogrammetry and remote sensing > vol 148 (February 2019) . - pp 174 - 183[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2019021 RAB Revue Centre de documentation En réserve L003 Disponible 081-2019023 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2019022 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt CarDen: A software for fast measurement of wood density on increment cores by CT scanning / Philippe Jacquin in Computers and Electronics in Agriculture, vol 156 (January 2019)
[article]
Titre : CarDen: A software for fast measurement of wood density on increment cores by CT scanning Type de document : Article/Communication Auteurs : Philippe Jacquin, Auteur ; Frédéric Mothe, Auteur ; Fleur Longuetaud, Auteur ; Antoine Billard, Auteur ; Baptiste Kerfriden , Auteur ; Jean-Michel Leban , Auteur Année de publication : 2019 Article en page(s) : pp 606 - 617 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] anatomie du bois
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] densité du bois
[Termes IGN] forêt tempérée
[Termes IGN] tomographie
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Increment cores are often used in wood science for measuring wood density of trees non destructively and at large scale, for instance with the objective to assess the available biomass in a forest resource. This paper presents a software allowing to measure by X-ray computed tomography (CT) the wood density of thousands increment cores. The software is able to process 3000 cores per hour semi-automatically. Manual intervention may be required to control and eventually adjust the positioning of the cores. The software was tested on 30 trees from 13 temperate species. Two increment cores were taken from each tree: one 5 mm diameter core and one 4 mm diameter core. The obtained CT density of the cores was compared to reference data obtained by volume and mass measurement on the 5 mm cores. The reference data were used for tuning the software settings by leave-one-out cross validation method. The obtained root mean square error was below 10 kg/m3 (1.7%) for the 5 mm cores. For the 4 mm cores, the root mean square difference with the reference density of the 5 mm cores was 25 kg/m3 (4.2%). Numéro de notice : A2019-665 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compag.2018.12.008 Date de publication en ligne : 14/12/2018 En ligne : https://doi.org/10.1016/j.compag.2018.12.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99929
in Computers and Electronics in Agriculture > vol 156 (January 2019) . - pp 606 - 617[article]Evaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest / Aline Bernarda Debastiani in Annals of forest research, vol 62 n° 1 (January - June 2019)PermalinkPermalinkEstimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations / Kun Liu in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkEstimation of forest above-ground biomass by geographically weighted regression and machine learning with Sentinel imagery / Lin Chen in Forests, vol 9 n° 10 (October 2018)PermalinkStrategies for climate-smart forest management in Austria / Robert Jandl in Forests, vol 9 n° 10 (October 2018)PermalinkUnmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil / Sébastien Giordano in IEEE Transactions on geoscience and remote sensing, vol 56 n° 10 (October 2018)PermalinkDeveloping allometric equations for estimating shrub biomass in a Boreal Fen / Annie He in Forests, vol 9 n° 9 (September 2018)PermalinkUsing terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: A comparison with traditional destructive approach / Stéphane Momo Takoudjou in Methods in ecology and evolution, vol 9 n° 4 (April 2018)PermalinkSeasonal time-course of the above ground biomass production efficiency in beech trees (Fagus sylvatica L.) / Laura Heid in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkEstimating forest standing biomass in savanna woodlands as an indicator of forest productivity using the new generation WorldView-2 sensor / Timothy Dube in Geocarto international, vol 33 n° 2 (February 2018)Permalink