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Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass / Le Li in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
[article]
Titre : Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass Type de document : Article/Communication Auteurs : Le Li, Auteur ; Qinghua Guo, Auteur ; Shengli Tao, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 198 - 208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse forestière
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] régression linéaireRésumé : (auteur) Forests play a key role in the global carbon cycle, and forest above ground biomass (AGB) is an important indictor to the carbon storage capacity and the potential carbon pool size of a forest ecosystem. Accurate estimation of forest AGB has become increasingly important for a wide range of end-users. Although satellite remote sensing provides abundant observations to monitor forest coverage, validation of coarse-resolution AGB derived from satellite observations is difficult because of the scale mismatch between the footprints of satellite observations and field measurements. In this study, we use airborne Lidar to bridge the scale gaps between satellite-based and field-based studies, and evaluate satellite-derived indices to estimate regional forest AGB. We found that: (1) Lidar data can be used to accurately estimate forest AGB using tree height and tree quadratic height, (2) linear regression, among four tested models, achieve the best performance (R2 = 0.74; RMSE = 183.57 Mg/ha); (3) for MODIS-derived vegetation indices at varied spatial resolution (250–1000 m), accumulated NDVI, accumulated LAI, and accumulated FPAR could explain 53–74% variances of forest AGB, whereas accumulated NDVI derived from 1 km MODIS products gives higher R2 (74%) and lower RMSE (13.4 Mg/ha) than others. We conclude that Lidar data can be used to bridge the scale gap between satellite and field studies. Our results indicate that combining MODIS and Lidar data has the potential to estimate regional forest AGB. Numéro de notice : A2015-694 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.02.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78328
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 198 - 208[article]Mapping aboveground biomass in northern japanese forests using the ALOS PRISM digital surface model / Takeshi Motohka in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)
[article]
Titre : Mapping aboveground biomass in northern japanese forests using the ALOS PRISM digital surface model Type de document : Article/Communication Auteurs : Takeshi Motohka, Auteur ; Toshiya Yoshida, Auteur ; Hideaki Shibata, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1683 - 1691 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse
[Termes IGN] évaluation des données
[Termes IGN] forêt
[Termes IGN] hauteur des arbres
[Termes IGN] image ALOS-PRISM
[Termes IGN] Japon
[Termes IGN] modèle numérique de sursolRésumé : (Auteur) We tested the performance of the stereo observations of the Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) onboard the Advanced Land Observing Satellite (ALOS) in the mapping of forest aboveground biomass (AGB) in Japan. Digital canopy height models (DCHMs), which are differences between PRISM digital surface models and surveying-based digital terrain models (DTMs), were compared to in situ AGB measurements of several forest types (number of stands: 28; average stand size: 0.54 ha; stand size range: 0.25-3.00 ha). DCHM values exhibited a significant correlation with AGB (r = 0.66-0.87; five different DCHMs), and the root-mean-square error and bias of the regression model evaluated by the leave-one-out cross-validation were 37.2-57.8t/ha(22.1%-32.6%) and-0.11-1.89 t/ha, respectively. There was no saturation in the relationship between DCHM and AGB (AGB range: 19-332 t/ha). The correlations between DCHM and mean canopy height (r = 0.17-0.52) and between DCHM and Lorey's height (r = 0.26-0.66) were weaker than the correlation between DCHM and AGB. The PRISM AGB distribution estimated by the regression model was consistent with a tree density map produced from aerial photos. Comparison to Phased Array-type L-band Synthetic Aperture Radar (PALSAR) data showed that the PRISM DCHMs can estimate high AGB over the saturation level of PALSAR backscattering coefficient, i.e., 100-200 t/ha. The results described here demonstrate that the PRISM DCHMs are capable of wall-to-wall AGB estimation at 50-m resolution. This approach will be useful for improving the performance of satellite-based AGB estimation when an accurate DTM is available. Numéro de notice : A2015-169 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2346531 En ligne : https://doi.org/10.1109/TGRS.2014.2346531 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75884
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1683 - 1691[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia / Adelia M.O. Sousa in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
[article]
Titre : Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia Type de document : Article/Communication Auteurs : Adelia M.O. Sousa, Auteur ; Ana Cristina Goncalves, Auteur ; Paulo Mesquita, Auteur ; José R. Marques da Silva, Auteur Année de publication : 2015 Article en page(s) : pp 69 - 79 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse
[Termes IGN] image à très haute résolution
[Termes IGN] image Quickbird
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Portugal
[Termes IGN] Quercus ilexRésumé : (auteur) Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands. Numéro de notice : A2015-469 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.12.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.12.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77171
in ISPRS Journal of photogrammetry and remote sensing > vol 101 (March 2015) . - pp 69 - 79[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Effects of LiDAR point density and landscape context on estimates of urban forest biomass / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
[article]
Titre : Effects of LiDAR point density and landscape context on estimates of urban forest biomass Type de document : Article/Communication Auteurs : Kunwar K. Singh, Auteur ; Gang Chen, Auteur ; James B. McCarter, Auteur ; Ross K. Meentemeyer, Auteur Année de publication : 2015 Article en page(s) : pp 310 - 322 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] composition d'un peuplement forestier
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] forêt urbaine
[Termes IGN] régression multipleRésumé : (auteur) Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density. Numéro de notice : A2015-471 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.12.021 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.12.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77173
in ISPRS Journal of photogrammetry and remote sensing > vol 101 (March 2015) . - pp 310 - 322[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
[article]
Titre : Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa Type de document : Article/Communication Auteurs : Timothy Dube, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2015 Article en page(s) : pp 36 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique subsaharienne
[Termes IGN] analyse comparative
[Termes IGN] biomasse
[Termes IGN] estimation statistique
[Termes IGN] Eucalyptus (genre)
[Termes IGN] image à moyenne résolution
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] indice de végétation
[Termes IGN] Pinus taedaRésumé : (auteur) Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge. Numéro de notice : A2015-468 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.11.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.11.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77170
in ISPRS Journal of photogrammetry and remote sensing > vol 101 (March 2015) . - pp 36 - 46[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2015031 RAB Revue Centre de documentation En réserve L003 Disponible Temporal stability of X-band single-pass InSAR heights in a spruce forest: effects of acquisition properties and season / Svein Solberg in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)PermalinkTree species biomass and carbon stock measurement using ground based-LiDAR / Gurveek Singh Maan in Geocarto international, vol 30 n° 3 - 4 (March - April 2015)PermalinkEstimating forest biomass from TerraSAR-X stripmap radargrammetry / Svein Solberg in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)PermalinkPinastéréo, estimation de la hauteur dominante et de la biomasse forestière dans le massif des Landes de Gascogne à partir d'images stéréoscopiques Pléiades / Thierry Bélouard in Revue Française de Photogrammétrie et de Télédétection, n° 209 (Janvier 2015)PermalinkSatellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest / Romà Ogaya in Annals of Forest Science, vol 72 n° 1 (January 2015)PermalinkThe land use and cover change in Miombo woodlands under community based forest management and its implication to climate change mitigation: A case of Southern Highlands of Tanzania / J.Z. Lupala in International journal of forestry research, vol 2015 ([01/01/2015])PermalinkTropical forest structure characterization using airborne lidar data: an individual tree level approach / António Ferraz (dec 2015)PermalinkDeriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies / Jari Vauhkonen in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)PermalinkImpact of local slope and aspect assessed from LiDAR records on tree diameter in radiata pine (Pinus radiata D. Don) plantations / Hanieh Saremi in Annals of Forest Science, vol 71 n° 7 (October 2014)PermalinkMeasurements of forest biomass change using P-Band synthetic aperture radar backscatter / Gustaf Sandberg in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)Permalink