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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)
[article]
Titre : On the interest of penetration depth, canopy area and volume metrics to improve Lidar-based models of forest parameters Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Jean-Pierre Renaud , Auteur ; Sylvie Durrieu, Auteur ; Marc Bouvier, Auteur Année de publication : 2016 Projets : FORESEE / Bigot-de-Morogues, Francis Article en page(s) : pp 32 - 42 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse aérienne
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] métrique
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] modèle numérique de terrain
[Termes IGN] semis de points
[Termes IGN] surface terrièreRésumé : (auteur) We proposed a new area-based approach to process Lidar point clouds and develop new sets of metrics to improve models dedicated to predict forest parameters. First, we introduced point normalization based on penetration depth below the outer canopy layer to avoid biases introduced by ground normalization and canopy surface heterogeneity during metric computation. Second, we proposed computation of area and volume metrics from canopy surface models computed from both first and last returns to better characterize the 3D plot heterogeneity. The set of proposed metrics were combined with traditional ones, based on point height above ground level, to measure their contribution to models of basal area (BA) and aboveground volume (AGV). The modeling framework included a wide range of forest types, canopy structures and Lidar characteristics. Models were developed for all sites grouped together or separately. In each case, the set of metrics was submitted to a hierarchical clustering process to select the best variables to be included in the models that were further established using a best-subset method. Overall, the introduction of the proposed metrics allowed a reduction in models root mean squared error from − 0.06% to 19.58% according to forest types and target forest parameters. Best improvements were achieved for broadleaved forests, showing the potential of the proposed metrics to efficiently characterize the structure of such porous forest canopies. Numéro de notice : A2016--089 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2015.12.039 Date de publication en ligne : 07/01/2016 En ligne : http://doi.org/10.1016/j.rse.2015.12.039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84582
in Remote sensing of environment > vol 175 (15 March 2016) . - pp 32 - 42[article]Mangrove forest characterization in Southeast Côte d’Ivoire / Isimemen Osemwegie in Open journal of forestry, vol 6 n° 3 (February 2016)
[article]
Titre : Mangrove forest characterization in Southeast Côte d’Ivoire Type de document : Article/Communication Auteurs : Isimemen Osemwegie, Auteur ; Dibi N'da Hyppolite, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 138 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] caractérisation
[Termes IGN] changement climatique
[Termes IGN] Côte d'Ivoire
[Termes IGN] Leaf Area Index
[Termes IGN] mangrove
[Termes IGN] palétuvier
[Termes IGN] peuplement forestier
[Termes IGN] puits de carbone
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] teneur en carbone
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Mangrove ecosystems are faced with far more existential threats of erosion than their terrestrial counterparts. Consequences of their degradation vary from decline in edible aquatic stocks, coastal erosion and aquatic weeds invasion. Mangrove forest dynamics was assessed from multi-temporal analyses of remotely sensed satellite images (mosaics of 1989/90 and 2014/15) within 233,900 hectares. Ground-truthing was accompanied by field measurements in selected forest stands to characterize structure, estimate biomass and carbon pools. With conservation as overriding goal, a socio-economic survey was conducted to underpin the factors influencing mangrove forests over-exploitation and qualitatively assess the sensitivity of the locals to resources decline. The region recorded fifty percent loss of mangrove area during the 25-year period. Low leaf area index (1.02 - 2.52 m2·m-2) confirms canopy openness. Above-ground root biomass (kg per root) ranged between 110.67 and 382.64. The roots demonstrate capacity to fix up to 176 Mg C ha-1 with average carbon content of 46 percent. Highest carbon pools were in the Eloka-To forest stands, in near natural conditions. Despite harsh environmental conditions, potential for natural regeneration was evidenced by seedlings density (individuals per m2) up to 76. Pilot survey revealed high dependence on mangrove resources for direct income (70 percent) and daily energy needs (60 percent). Despite the heightened awareness of the impending dangers posed by mangrove deforestation and willingness to conserve, riverine communities are incapacitated by lack of viable economic alternatives. External interventions are therefore imperative to achieve conservation goals with long-term implications for climate change adaptation and mitigation. Numéro de notice : A2016-147 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.4236/oje.2016.63014 En ligne : http://dx.doi.org/ 10.4236/oje.2016.63014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80346
in Open journal of forestry > vol 6 n° 3 (February 2016) . - pp 138 - 150[article]Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass / Timothy G. Gregoire in Remote sensing of environment, vol 173 (February 2016)
[article]
Titre : Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass Type de document : Article/Communication Auteurs : Timothy G. Gregoire, Auteur ; Erik Naesset, Auteur ; Ronald E. McRoberts, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 98 - 108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse aérienne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] échantillonnage
[Termes IGN] incertitude géométrique
[Termes IGN] inférence statistique
[Termes IGN] varianceRésumé : (auteur) For many decades remotely sensed data have been used as a source of auxiliary information when conducting regional or national surveys of forest resources. In the past decade, airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool for sample surveys aimed at improving estimation of above-ground forest biomass. This technology is now employed routinely in forest management inventories of some Nordic countries, and there is eager anticipation for its application to assess changes in standing biomass in vast tropical regions of the globe in concert with the UN REDD program to limit C emissions. In the rapidly expanding literature on LiDAR-assisted biomass estimation the assessment of the uncertainty of estimation varies widely, ranging from statistically rigorous to ad hoc. In many instances, too, there appears to be no recognition of different bases of statistical inference which bear importantly on uncertainty estimation. Statistically rigorous assessment of uncertainty for four large LiDAR-assisted surveys is expounded. Numéro de notice : A2016--160 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2015.11. En ligne : https://doi.org/10.1016/j.rse.2015.11.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87012
in Remote sensing of environment > vol 173 (February 2016) . - pp 98 - 108[article]Application 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)
[article]
Titre : Application of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania Type de document : Article/Communication Auteurs : Mercy Ojoyi, Auteur ; Onisimo Mutanga, Auteur ; John Olindi, Auteur ; Elfatih M. Abdel-Rahman, Auteur Année de publication : 2016 Article en page(s) : pp 1 - 21 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse
[Termes IGN] données topographiques
[Termes IGN] estimation statistique
[Termes IGN] facteur édaphique
[Termes IGN] forêt tropicale
[Termes IGN] image RapidEye
[Termes IGN] indice de végétation
[Termes IGN] montagne
[Termes IGN] surveillance écologique
[Termes IGN] TanzanieRésumé : (Auteur) Estimating tropical biomass is critical for establishment of conservation inventories and landscape monitoring. However, monitoring biomass in a complex and dynamic environment using traditional methods is challenging. Recently, biomass estimates based on remotely sensed data and ecological variables have shown great potential. The present study explored the utility of remotely sensed data and topo-edaphic factors to improve biomass estimation in the Eastern Arc Mountains of Tanzania. Twenty-nine vegetation indices were calculated from RapidEye data, while topo-edaphic factors were taken from field measurements. Results showed that using topo-edaphic variables or vegetation indices, biomass could be predicted with an R2 of 0.4. A combination of topo-edaphic variables and vegetation indices improved the prediction accuracy to an R2 of 0.6. Results further showed a decrease in biomass estimates from 1162 ton ha−1 in 1980 to 285.38 ton ha−1 in 2012. This study demonstrates the value of combining remotely sensed data with topo-edaphic variables in biomass estimation. Numéro de notice : A2016-079 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1041557 Date de publication en ligne : 20/05/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1041557 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79865
in Geocarto international > vol 31 n° 1 - 2 (January - February 2016) . - pp 1 - 21[article]Réservation
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