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Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods / X. Tang in Annals of forest research, vol 59 n° 2 (July - December 2016)
[article]
Titre : Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods Type de document : Article/Communication Auteurs : X. Tang, Auteur ; L. Fehrmann, Auteur ; Fengying Guan, Auteur ; David I. Forrester, Auteur ; R. Guisasola, Auteur ; C. Kleinn, Auteur Année de publication : 2016 Article en page(s) : pp 269 - 280 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies (genre)
[Termes IGN] biomasse forestière
[Termes IGN] Chine
[Termes IGN] estimation statistique
[Termes IGN] feuillu
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] puits de carbone
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Several comparative studies have reported that there can be great discrepancies between different methods used to estimate forest biomass. With the development of carbon markets, an accurate estimation at the regional scale (i.e. county level) is becoming increasingly important for local government. In this study, we applied five methodologies [continuous biomass expansion factor (CBEF) approach, mean biomass density (MB) approach, mean biomass expansion factor (MBEF) approach, national continuous biomass expansion factors (NCBEF) proposed by Fang et al (2002), standard IPCC approach] to estimate the total biomass for Shitai County, China. The CBEF is generally considered to provide the most realistic estimates in term of regional biomass because CBEF reflects the change of BEF to stand density, stand age and site conditions. The forests of the whole county were divided into four forest types, namely Chinese fir plantations (CF), hardwood broadleaved forests (HB), softwood–broadleaved forests (SB) and mason pine forests (MP) according to the local forest management inventory of 2004. Generally, the MBEF approach overestimated forest biomass while the IPCC approach underestimated forest biomass for all forest types when CBEF derived biomass was used as a control. The MB approach provided the most similar biomass estimates for all forest types and could be an alternative approach when a CBEF equation is lacking in the study area. The total biomass derived from MBEF was highest at 1.44×107 t, followed by 1.32 ×107 t from CBEF, 1.31 ×107 t from NCBEF, 1.25 ×107 t from MB and 1.16 ×107 t from IPCC. Our results facilitate method selection for regional forest biomass estimation and provide statistical evidence for local government planning to enter the potential carbon market. Numéro de notice : A2016--095 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.15287/afr.2016.574 En ligne : http://doi.org/10.15287/afr.2016.574 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84647
in Annals of forest research > vol 59 n° 2 (July - December 2016) . - pp 269 - 280[article]GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring / Erwan Motte in Sensors, vol 16 n° 5 (May 2016)
[article]
Titre : GLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring Type de document : Article/Communication Auteurs : Erwan Motte, Auteur ; Mehrez Zribi, Auteur ; Pascal Fanise, Auteur ; et al., Auteur ; Pierre-Louis Frison , Auteur Année de publication : 2016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] biomasse forestière
[Termes IGN] capteur aérien
[Termes IGN] caractérisation
[Termes IGN] données polarimétriques
[Termes IGN] humidité du sol
[Termes IGN] réflectométrie par GNSS
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a remote sensing tool, which is complementary to traditional monostatic radars, for the retrieval of geophysical parameters related to surface properties. In the present paper, we describe a new polarimetric GNSS-R system, referred to as the GLObal navigation satellite system Reflectometry Instrument (GLORI), dedicated to the study of land surfaces (soil moisture, vegetation water content, forest biomass) and inland water bodies. This system was installed as a permanent payload on a French ATR42 research aircraft, from which simultaneous measurements can be carried out using other instruments, when required. Following initial laboratory qualifications, two airborne campaigns involving nine flights were performed in 2014 and 2015 in the Southwest of France, over various types of land cover, including agricultural fields and forests. Some of these flights were made concurrently with in situ ground truth campaigns. Various preliminary applications for the characterisation of agricultural and forest areas are presented. Initial analysis of the data shows that the performance of the GLORI instrument is well within specifications, with a cross-polarization isolation better than −15 dB at all elevations above 45°, a relative polarimetric calibration accuracy better than 0.5 dB, and an apparent reflectivity sensitivity better than −30 dB, thus demonstrating its strong potential for the retrieval of land surface characteristics. Numéro de notice : A2016 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/s16050732 Date de publication en ligne : 20/05/2016 En ligne : https://doi.org/10.3390/s16050732 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91793
in Sensors > vol 16 n° 5 (May 2016)[article]ICESat/GLAS canopy height sensitivity inferred from Airborne Lidar / Craig Mahoney in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)
[article]
Titre : ICESat/GLAS canopy height sensitivity inferred from Airborne Lidar Type de document : Article/Communication Auteurs : Craig Mahoney, Auteur ; Christopher Hopkinson, Auteur ; Alex Held, Auteur ; Natascha Kljun, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 351 - 363 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] altimétrie satellitaire par laser
[Termes IGN] analyse comparative
[Termes IGN] biomasse forestière
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] hauteur des arbres
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) Variations in laser properties and data acquisition times introduced inconsistencies in Geoscience Laser Altimeter System (GLAS) data. The effect of data inconsistencies, on two GLAS height retrieval methods, from three study sites, are investigated and validated against airborne laser scanning (ALS) percentile heights, from three data sources: all/first return point clouds, and raster canopy height models. GLAS/ALS controls were established as a basis against which the influence of laser number, transmission energy, and seasonality were assessed through comparison statistics. The favored GLAS height method best compared with ALS 95th percentile heights from an all return point cloud. Optimal GLAS data (R2 = 0.69, RMSE = 8.10 m) were noted when GLAS acquired data during summertime from high energy, laser three transmissions. As GLAS data can be used in global biomass assessments, there is a need to understand and quantify the influence of these data inconsistencies on canopy height estimates. Numéro de notice : A2016-410 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.5.351 En ligne : http://dx.doi.org/10.14358/PERS.82.5.351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81276
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 5 (May 2016) . - pp 351 - 363[article]Estimating forest and woodland aboveground biomass using active and passive remote sensing / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)
[article]
Titre : Estimating forest and woodland aboveground biomass using active and passive remote sensing Type de document : Article/Communication Auteurs : Zhuoting Wu, Auteur ; Dennis Dye, Auteur ; John Vogel, Auteur ; Barry Middleton, Auteur Année de publication : 2016 Article en page(s) : pp 271 - 281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Arizona (Etats-Unis)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] capteur actif
[Termes IGN] capteur passif
[Termes IGN] données lidar
[Termes IGN] écosystème forestier
[Termes IGN] hauteur des arbres
[Termes IGN] image Landsat-8
[Termes IGN] surface forestièreRésumé : (auteur) Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14 Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States. Numéro de notice : A2016-179 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.4.271 En ligne : http://dx.doi.org/10.14358/PERS.82.4.271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80521
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 4 (April 2016) . - pp 271 - 281[article]Forest above ground biomass inversion by fusing GLAS with optical remote sensing data / Xiaohuan Xi in ISPRS International journal of geo-information, vol 5 n° 4 (April 2016)
[article]
Titre : Forest above ground biomass inversion by fusing GLAS with optical remote sensing data Type de document : Article/Communication Auteurs : Xiaohuan Xi, Auteur ; Tingting Han, Auteur ; Cheng Wang, Auteur ; et al., Auteur Année de publication : 2016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] classification par réseau neuronal
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] données ICEsat
[Termes IGN] forêt
[Termes IGN] hauteur de la végétation
[Termes IGN] image Landsat-TM
[Termes IGN] image optique
[Termes IGN] image Terra-MODIS
[Termes IGN] Leaf Area Index
[Termes IGN] MNS ASTER
[Termes IGN] régression
[Termes IGN] Yunnan (Chine)Résumé : (auteur) Forest biomass is an important parameter for quantifying and understanding biological and physical processes on the Earth’s surface. Rapid, reliable, and objective estimations of forest biomass are essential to terrestrial ecosystem research. The Geoscience Laser Altimeter System (GLAS) produced substantial scientific data for detecting the vegetation structure at the footprint level. This study combined GLAS data with MODIS/BRDF (Bidirectional Reflectance Distribution Function) and ASTER GDEM data to estimate forest aboveground biomass (AGB) in Xishuangbanna, Yunnan Province, China. The GLAS waveform characteristic parameters were extracted using the wavelet method. The ASTER DEM was used to compute the terrain index for reducing the topographic influence on the GLAS canopy height estimation. A neural network method was applied to assimilate the MODIS BRDF data with the canopy heights for estimating continuous forest heights. Forest leaf area indices (LAIs) were derived from Landsat TM imagery. A series of biomass estimation models were developed and validated using regression analyses between field-estimated biomass, canopy height, and LAI. The GLAS-derived canopy heights in Xishuangbanna correlated well with the field-estimated AGB (R2 = 0.61, RMSE = 52.79 Mg/ha). Combining the GLAS estimated canopy heights and LAI yielded a stronger correlation with the field-estimated AGB (R2 = 0.73, RMSE = 38.20 Mg/ha), which indicates that the accuracy of the estimated biomass in complex terrains can be improved significantly by integrating GLAS and optical remote sensing data. Numéro de notice : A2016-820 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi5040045 En ligne : https://doi.org/10.3390/ijgi5040045 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82625
in ISPRS International journal of geo-information > vol 5 n° 4 (April 2016)[article]On the interest of penetration depth, canopy area and volume metrics to improve Lidar-based models of forest parameters / Cédric Vega in Remote sensing of environment, vol 175 (15 March 2016)PermalinkMangrove forest characterization in Southeast Côte d’Ivoire / Isimemen Osemwegie in Open journal of forestry, vol 6 n° 3 (February 2016)PermalinkStatistical rigor in LiDAR-assisted estimation of aboveground forest biomass / Timothy G. Gregoire in Remote sensing of environment, vol 173 (February 2016)PermalinkApplication of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania / Mercy Ojoyi in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)PermalinkEstimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)PermalinkMeasurement of the annual biomass increment of the French forests, XYLODENSMAP project [diaporama] / Jean-Michel Leban (2016)PermalinkDe la modélisation du déterminisme environnemental de la productivité forestière / Jean-Daniel Bontemps (2016)PermalinkRadar based classification prior to biomass retrieval from P-Band SAR data / Pierre-Louis Frison (2016)PermalinkExamining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments / Mbulisi Sibanda in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)PermalinkA review of forest and tree plantation biomass equations in Indonesia / Kamalakumari Anitha in Annals of Forest Science, vol 72 n° 8 (December 2015)Permalink