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A simple method for detecting phenological change from time series of vegetation index / Jin Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)
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Titre : A simple method for detecting phenological change from time series of vegetation index Type de document : Article/Communication Auteurs : Jin Chen, Auteur ; Yuhan Rao, Auteur ; Miaogen Shen, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 3436 - 3449 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] Chine
[Termes IGN] Enhanced vegetation index
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] phénologie
[Termes IGN] série temporelleRésumé : (Auteur) Remote sensing is a valuable way to retrieve spatially continuous information on vegetation phenological changes, which are widely used as an indicator of climate change. We propose a simple method called weighted cross-correlogram spectral matching-phenology (CCSM-P), which combines CCSM and a weighted correlation system, for detecting vegetation phenological changes by using multiyear vegetation index (VI) time series. In experiments with simulated enhanced VI (EVI) for various scenarios, CCSM-P exhibited high accuracy and robustness to noise and the potential to capture long-term phenological change trends. For a temperate grassland in northern China, CCSM-P retrieved more reasonable vegetation spring phenology from Moderate Resolution Imaging Spectroradiometer (MODIS) EVI images than the MODIS phenology product (MCD12Q2). When validated against field phenological observations in five of the AmeriFlux Network sites in the U.S. (four deciduous broadleaf forest sites and a closed shrublands site), and a cropland site in China, CCSM-P exhibited mean absolute differences (MADs) ranging from 2 to 10 days (median: 4.2 days), whereas MAD of non-CCSM methods showed larger variations, ranging from 5 to 58 days (median: 21.3 days). This is because CCSM-P integrates field phenological observations. Compared with non-CCSM methods, which are widely used to identify phenological events, CCSM-P is more accurate and less dependent on prior knowledge (thresholds or predefined functions), which indicates its effectiveness and applicability for detecting year-to-year variations and long-term change trends in phenology, and should facilitate more reliable assessments of phenological changes in climate change studies. Numéro de notice : A2016-854 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2518167 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2518167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82992
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 6 (June 2016) . - pp 3436 - 3449[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)
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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]Assessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning data / Guang Zheng in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)
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Titre : Assessing the contribution of woody materials to forest angular gap fraction and effective leaf area index using terrestrial laser scanning data Type de document : Article/Communication Auteurs : Guang Zheng, Auteur ; Lixia Ma, Auteur ; Wei He, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1475 - 1487 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] bois sur pied
[Termes IGN] classification automatique
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] photosynthèse
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (Auteur) The spatial distribution of the photosynthetic components of a forest canopy plays a key role in ecological related processes such as gas exchange, photosynthesis, and evapotranspiration through affecting radiation regimes of the forest canopy. However, quantitative evaluation of woody materials' contribution to effective leaf area index (LAIe) using 3-D terrestrial laser scanning (TLS) is a challenging work. In this paper, we first identified the differences between directional gap fraction (DGF) and angular gap fraction (AGF) and then developed a local geometric feature-based approach to automatically classify a TLS forest point cloud data (PCD) into three different classes, including nonphotosynthetic canopy components (i.e., stem and branch points), photosynthetic canopy components (i.e., leaf and grass points), and bare ground. In addition, we proposed a new approach named “radial hemispherical point cloud slicing” algorithm to investigate the 3-D spatial distribution of foliage elements and retrieve LAIe from a given forest PCD. Our results showed that nonphotosynthetic canopy components contributed from 19% to 54% to LAIe depending on various forest densities. Moreover, TLS-based LAIe estimates can explain 74.27% variations of digital-hemispherical-photography-based LAIe values with a linear regression statistical model. This paper provides a theoretical foundation for LAI estimation based on the PCD generated using the TLS system and facilitates the application of TLS on retrieving 3-D forest canopy structural biophysical parameters. Numéro de notice : A2016-132 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2481492 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2481492 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80019
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1475 - 1487[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2016031 SL Revue Centre de documentation Revues en salle Disponible Comparison of three Landsat TM compositing methods: A case study using modeled tree canopy cover / Bonnie Ruefenacht in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 3 (March 2016)
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Titre : Comparison of three Landsat TM compositing methods: A case study using modeled tree canopy cover Type de document : Article/Communication Auteurs : Bonnie Ruefenacht, Auteur Année de publication : 2016 Article en page(s) : pp 199 - 211 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] canopée
[Termes IGN] image Landsat-TM
[Termes IGN] modèle de régression
[Termes IGN] mosaïquage d'images
[Termes IGN] Normalized Difference Vegetation IndexRésumé : (auteur) Landsat imagery mosaics developed using model II regression have been shown to successfully model percent tree-canopy cover (PTCC). Creating model II regression mosaics, however, is a time-consuming, manual process. The objective of this study is to evaluate the effectiveness of using more easily automated image composites techniques, such as median Landsat-5 image composites or maximum NDVI Landsat-5 image composites, as alternatives to model II regression mosaics for the modeling of PTCC. This study found all composite types were effective in modeling PTCC, but the maximum NDVI composites included anomalies, clouds, shadows, and tended to be pixelated, whereas the median composites and the model II regression mosaics had none of these issues. The median composite procedure is automated and was found to be an effective approach to statistically reduce a much larger ensemble of images on a pixel basis to create images suitable for vegetation modeling. Numéro de notice : A2016-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.3.189 En ligne : https://doi.org/10.14358/PERS.82.3.189 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80515
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 3 (March 2016) . - pp 199 - 211[article]Temporal MODIS data for identification of wheat crop using noise clustering soft classification approach / Priyadarshi Upadhyay in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)
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Titre : Temporal MODIS data for identification of wheat crop using noise clustering soft classification approach Type de document : Article/Communication Auteurs : Priyadarshi Upadhyay, Auteur ; Sanjay Kumar Ghosh, Auteur ; Anil Kumar, Auteur Année de publication : 2016 Article en page(s) : pp 278 - 295 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] blé (céréale)
[Termes IGN] bruit rose
[Termes IGN] classification automatique
[Termes IGN] croissance végétale
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] surveillance agricoleRésumé : (Auteur) In this study, temporal MODIS-Terra MOD13Q1 data have been used for identification of wheat crop uniquely, using the noise clustering (NC) soft classification approach. This research also optimises the selection of date combination and vegetation index for classification of wheat crop. First, a separability analysis is used to optimise the date combination for each case of number of dates and vegetation index. Then, these scenes have undergone for NC soft classification. The resolution parameter (δ) was optimised for the NC classifier and found to be a value of 1.6 × 104 for wheat crop identification. Classified outputs were analysed by receiver operating characteristics (ROC) analysis for sub-pixel detection. Highest area under the ROC curve was found for soil-adjusted vegetation index corresponding to the three different phenological stages data sets. From this study, the data sets corresponding to the Sowing, Flowering and Maturity phenological stages of wheat crop were found more suitable to identify it uniquely. Numéro de notice : A2016-159 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1047415 Date de publication en ligne : 26/05/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1047415 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80381
in Geocarto international > vol 31 n° 3 - 4 (March - April 2016) . - pp 278 - 295[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2016021 RAB Revue Centre de documentation En réserve L003 Disponible Improved salient feature-based approach for automatically separating photosynthetic and nonphotosynthetic components within terrestrial Lidar point cloud data of forest canopies / Lixia Ma in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)
PermalinkMangrove forest characterization in Southeast Côte d’Ivoire / Isimemen Osemwegie in Open journal of forestry, vol 6 n° 3 (February 2016)
PermalinkOptimising the spatial resolution of WorldView-2 pan-sharpened imagery for predicting levels of Gonipterus scutellatus defoliation in KwaZulu-Natal, South Africa / Romano Lottering in ISPRS Journal of photogrammetry and remote sensing, vol 112 (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)
PermalinkEffects of water and heat on growth of winter wheat in the North China Plain / Hongyan Wang in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)
PermalinkA Bayesian network-based method to alleviate the ill-posed inverse problem: A case study on leaf area index and canopy water content retrieval / Xingwen Quan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)
PermalinkA moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data / Gang Yang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)
PermalinkMonitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia / Loïc Paul Dutrieux in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
PermalinkBRDF-corrected vegetation indices confirm seasonal pattern in greening of French Guiana's forests / Emil A. Cherrington in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)
PermalinkIn situ calibration of light sensors for long-term monitoring of vegetation / Hongxiao Jin in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)
PermalinkUtilisation des données des capteurs MODIS et SPOT-VGT pour l'analyse de la dynamique des feux dans deux territoires (réserve protégée et unités pastorales) au Ferlo (Sénégal) / Mamadou Adama Sarr in Photo interprétation, European journal of applied remote sensing, vol 51 n° 2 (juin 2015)
PermalinkValidation of canopy height profile methodology for small-footprint full-waveform airborne LiDAR data in a discontinuous canopy environment / Karolina D. Fieber in ISPRS Journal of photogrammetry and remote sensing, vol 104 (June 2015)
PermalinkAn improved species distribution model for Scots pine and downy oak under future climate change in the NW Italian Alps / Giorgio Vacchiano in Annals of Forest Science, vol 72 n° 3 (May 2015)
PermalinkDo competition-density rule and self-thinning rule agree? / Sonja Vospernik in Annals of Forest Science, vol 72 n° 3 (May 2015)
PermalinkMultispectral sensor spectral resolution simulations for generation of hyperspectral vegetation indices from Hyperion data / Prabir Das in Geocarto international, vol 30 n° 5 - 6 (May - July 2015)
PermalinkEvaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework / H. Croft in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
PermalinkImproving forest aboveground biomass estimation using seasonal Landsat NDVI time-series / Xiaolin Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
PermalinkLidar 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)
PermalinkEvaluating 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)
PermalinkMODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests / Tomáš Hlásny in Annals of Forest Science, vol 72 n° 1 (January 2015)
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