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Auteur Sassan Saatchi |
Documents disponibles écrits par cet auteur (5)
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A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT / Shengli Tao in Earth System Science Data, vol 15 n° 4 (2023)
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Titre : A global long-term, high-resolution satellite radar backscatter data record (1992–2022+): merging C-band ERS/ASCAT and Ku-band QSCAT Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Zurui Ao, Auteur ; Jean-Pierre Wigneron, Auteur ; Sassan Saatchi, Auteur ; Philippe Ciais, Auteur ; Jérôme Chave, Auteur ; Thuy Le Toan, Auteur ; Pierre-Louis Frison , Auteur ; et al., Auteur
Année de publication : 2023 Article en page(s) : pp 1577 - 1596 Note générale : bibliographie
Data description paperLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande C
[Termes IGN] bande Ku
[Termes IGN] fusion de données
[Termes IGN] image radar moirée
[Termes IGN] régression
[Termes IGN] série temporelleRésumé : (auteur) Satellite radar backscatter contains unique information on land surface moisture, vegetation features, and surface roughness and has thus been used in a range of Earth science disciplines. However, there is no single global radar data set that has a relatively long wavelength and a decades-long time span. We here provide the first long-term (since 1992), high-resolution (∼8.9 km instead of the commonly used ∼25 km resolution) monthly satellite radar backscatter data set over global land areas, called the long-term, high-resolution scatterometer (LHScat) data set, by fusing signals from the European Remote Sensing satellite (ERS; 1992–2001; C-band; 5.3 GHz), Quick Scatterometer (QSCAT, 1999–2009; Ku-band; 13.4 GHz), and the Advanced SCATterometer (ASCAT; since 2007; C-band; 5.255 GHz). The 6-year data gap between C-band ERS and ASCAT was filled by modelling a substitute C-band signal during 1999–2009 from Ku-band QSCAT signals and climatic information. To this end, we first rescaled the signals from different sensors, pixel by pixel. We then corrected the monthly signal differences between the C-band and the scaled Ku-band signals by modelling the signal differences from climatic variables (i.e. monthly precipitation, skin temperature, and snow depth) using decision tree regression. The quality of the merged radar signal was assessed by computing the Pearson r, root mean square error (RMSE), and relative RMSE (rRMSE) between the C-band and the corrected Ku-band signals in the overlapping years (1999–2001 and 2007–2009). We obtained high Pearson r values and low RMSE values at both the regional (r≥0.92, RMSE ≤ 0.11 dB, and rRMSE ≤ 0.38) and pixel levels (median r across pixels ≥ 0.64, median RMSE ≤ 0.34 dB, and median rRMSE ≤ 0.88), suggesting high accuracy for the data-merging procedure. The merged radar signals were then validated against the European Space Agency (ESA) ERS-2 data, which provide observations for a subset of global pixels until 2011, even after the failure of on-board gyroscopes in 2001. We found highly concordant monthly dynamics between the merged radar signals and the ESA ERS-2 signals, with regional Pearson r values ranging from 0.79 to 0.98. These results showed that our merged radar data have a consistent C-band signal dynamic. The LHScat data set (https://doi.org/10.6084/m9.figshare.20407857; Tao et al., 2023) is expected to advance our understanding of the long-term changes in, e.g., global vegetation and soil moisture with a high spatial resolution. The data set will be updated on a regular basis to include the latest images acquired by ASCAT and to include even higher spatial and temporal resolutions. Numéro de notice : A2023-097 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-15-1577-2023 Date de publication en ligne : 12/04/2023 En ligne : https://doi.org/10.5194/essd-15-1577-2023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103215
in Earth System Science Data > vol 15 n° 4 (2023) . - pp 1577 - 1596[article]Forest degradation and biomass loss along the Chocó region of Colombia / Victoria Meyer in Carbon Balance and Management, vol 14 (March 2019)
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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]Lidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)
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Titre : Lidar detection of individual tree size in tropical forests Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet
, Auteur ; Victoria Meyer, Auteur
Année de publication : 2016 Projets : 1-Pas de projet / Article en page(s) : pp 318 - 333 Note générale : Bibliographie
António Ferraz's research was supported by an appointment to the NASA Postdoctoral Program at the Jet Propulsion Laboratory, administrated by Oak Ridge Associated Universities under contract with NASA(grant number NNH15CO48B).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Panama
[Termes IGN] semis de points
[Termes IGN] télédétection aérienneRésumé : (Auteur) Characterization of tropical forest trees has been limited to field-based techniques focused on measurement of diameter of the cylindrical part of the bole, with large uncertainty in measuring large trees with irregular shapes, and other size attributes such as total tree height and the crown size. Here, we introduce a methodology to decompose lidar point cloud data into 3D clusters corresponding to individual tree crowns (ITC) that enables the estimation of many biophysical variables of tropical forests such as tree height, crown area, crown volume, and tree number density. The ITC-based approach was tested using airborne high-resolution lidar data collected over the 50-ha Center for Tropical Forest Science (CTFS) plot in the Barro Colorado Island, Panama. The lack of tree height and crown size measurements in the field prohibits the direct validation of the ITC metrics. We assess the reliability of our method by comparing the aboveground biomass (AGB) estimated using ground and lidar individual tree measurements at multiple spatial scales, namely 1ha, 2.25 ha, 4ha, and 6.25 ha. We examined four different lidar-derived AGB models, with three based on individual tree height, crown volume, and crown area, and one with mean top canopy height (TCH) calculated at the plot level using the lidar canopy height model. Results show that the predictive power of all models based on ITC size and TCH increases with decreasing spatial resolution from16.9% at 1ha for the worst model to 5.0% at 6.25ha for the best model. The TCH-based model performed slightly better than ITC-based models except at higher spatial scales (~4 ha) and when errors due to edge effects associated with tree crowns were reduced. Unlike the TCH models that change regionally depending on forest type and structure allometry, the ITC-based models are derived as a function of individual tree allometry and can be extended globally to all tropical forests. The method for lidar detection of individual crown size overcome some limitations of ground-based inventories such as 1) it is able to access crowns of large trees and 2) it enables the assessment of directional changes in tree density, canopy architecture and forest dynamics over large and inaccessible areas to support robust tropical ecological studies. Numéro de notice : A2016--103 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2016.05.028 Date de publication en ligne : 21/06/2016 En ligne : http://doi.org/10.1016/j.rse.2016.05.028 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84669
in Remote sensing of environment > vol 183 (15 September 2016) . - pp 318 - 333[article]Airborne lidar estimation of aboveground forest biomass in the absence of field inventory / António Ferraz in Remote sensing, vol 8 n° 8 (August 2016)
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Titre : Airborne lidar estimation of aboveground forest biomass in the absence of field inventory Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet
, Auteur ; Stéphane Jacquemoud, Auteur ; Gil Rito-Gonçalves
, Auteur ; Carlos Alberto Silva, Auteur ; Paola Soares, Auteur ; Margarida Tomé, Auteur ; Luisa Pereira, Auteur
Année de publication : 2016 Projets : 3-projet - voir note / Article en page(s) : pp 1 - 18 Note générale : Bibliographie
This work was supported in part by the Portuguese Foundation for Science and Technology under Grant PTDC/AGR-CFL/72380/2006, co-financed by the European Fund of Regional Development (FEDER) through COMPETE—Operational Factors of Competitiveness Program (POFC) and the Grant Pest-OE/EEI/UI308/2014Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] analyse de groupement
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification automatique d'objets
[Termes IGN] couvert végétal
[Termes IGN] dendrométrie
[Termes IGN] données lidar
[Termes IGN] extraction d'arbres
[Termes IGN] fiabilité des données
[Termes IGN] houppier
[Termes IGN] Portugal
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) The scientific community involved in the UN-REDD program is still reporting large uncertainties about the amount and spatial variability of CO2 stored in forests. The main limitation has been the lack of field samplings over space and time needed to calibrate and convert remote sensing measurements into aboveground biomass (AGB). As an alternative to costly field inventories, we examine the reliability of state-of-the-art lidar methods to provide direct retrieval of many forest metrics that are commonly collected through field sampling techniques (e.g., tree density, individual tree height, crown cover). AGB is estimated using existing allometric equations that are fed by lidar-derived metrics at either the individual tree- or forest layer-level (for the overstory or underneath layers, respectively). Results over 40 plots of a multilayered forest located in northwest Portugal show that the lidar method provides AGB estimates with a relatively small random error (RMSE = of 17.1%) and bias (of 4.6%). It provides local AGB baselines that meet the requirements in terms of accuracy to calibrate satellite remote sensing measurements (e.g., the upcoming lidar GEDI (Global Ecosystem Dynamics Investigation), and the Synthetic Aperture Radar (SAR) missions NISAR (National Aeronautics and Space Administration and Indian Space Research Organization SAR) and BIOMASS from the European Space Agency, ESA) for AGB mapping purposes. The development of similar techniques over a variety of forest types would be a significant improvement in quantifying CO2 stocks and changes to comply with the UN-REDD policies. Numéro de notice : A2016--104 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs8080653 Date de publication en ligne : 12/08/2016 En ligne : https://doi.org/10.3390/rs8080653 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84675
in Remote sensing > vol 8 n° 8 (August 2016) . - pp 1 - 18[article]Documents numériques
en open access
A2016--104_Airborne_lidar_estimation_of_aboveground_forest_biomassAdobe Acrobat PDFTropical forest structure characterization using airborne lidar data: an individual tree level approach / António Ferraz (dec 2015)
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Titre : Tropical forest structure characterization using airborne lidar data: an individual tree level approach Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet
, Auteur ; Victoria Meyer, Auteur
Editeur : Washington DC [Maryland - Etats-Unis] : American Geophysical Union AGU Année de publication : dec 2015 Conférence : AGU 2015 Fall Meeting 14/10/2015 18/12/2015 San Francisco Californie - Etats-Unis Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] biomasse aérienne
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] Panama
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (auteur) Fine scale tropical forest structure characterization has been performed by means of field measurements techniques that record both the specie and the diameter at the breast height (dbh) for every tree within a given area. Due to dense and complex vegetation, additional important ecological variables (e.g. the tree height and crown size) are usually not measured because they are hardly recognized from the ground. The poor knowledge on the 3D tropical forest structure has been a major limitation for the understanding of different ecological issues such as the spatial distribution of carbon stocks, regeneration and competition dynamics and light penetration gradient assessments. Airborne laser scanning (ALS) is an active remote sensing technique that provides georeferenced distance measurements between the aircraft and the surface. It provides an unstructured 3D point cloud that is a high-resolution model of the forest. This study presents the first approach for tropical forest characterization at a fine scale using remote sensing data. The multi-modal lidar point cloud is decomposed into 3D clusters that correspond to single trees by means of a technique called Adaptive Mean Shift Segmentation (AMS3D). The ability of the corresponding individual tree metrics (tree height, crown area and crown volume) for the estimation of above ground biomass (agb) over the 50 ha CTFS plot in Barro Colorado Island is here assessed. We conclude that our approach is able to map the agb spatial distribution with an error of nearly 12% (RMSE=28 Mg ha-1) compared with field-based estimates over 1ha plots. Numéro de notice : C2015-033 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://agu.confex.com/agu/fm15/meetingapp.cgi/Paper/75802 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83298