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Quantifying intra-annual dynamics of carbon sequestration in the forming wood: a novel histologic approach / Anjy Andrianantenaina in Annals of Forest Science, Vol 76 n° 3 (September 2019)
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Titre : Quantifying intra-annual dynamics of carbon sequestration in the forming wood: a novel histologic approach Type de document : Article/Communication Auteurs : Anjy Andrianantenaina, Auteur ; Cyrille B.K. Rathgeber, Auteur ; Gonzalo Péres-de-Lis, Auteur ; Henri E. Cuny , Auteur ; Julien Ruelle, Auteur
Année de publication : 2019 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : n° 62 Note générale : bibliographie
This work was supported by a grant overseen by the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE), and by the National Institute of Agricultural Research (INRA Grand-Est Nancy) with a doctoral fellowship granted to the first author (CJS, “Contrat Jeune Scientifique”).Langues : Anglais (eng) Descripteur : [Termes IGN] analyse d'image numérique
[Termes IGN] Angiosperme
[Termes IGN] biomasse aérienne
[Termes IGN] croissance végétale
[Termes IGN] densité du bois
[Termes IGN] Hesse, forêt de (Meuse)
[Termes IGN] microscope électronique
[Termes IGN] Picea abies
[Termes IGN] puits de carbone
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) This study presents a novel histologic approach to quantify the intra-annual dynamics of carbon sequestration in forming wood. This innovative approach, based on repeated measurements of xylem apparent density, is more direct, and more accurate than the previously published cellular-based approach. Moreover, this new approach, which was tested here on softwoods, is also applicable to hardwoods without any modification.
Context : Forest ecosystems are key players of the terrestrial carbon cycle. Indeed, wood represents the principal carbon pool of terrestrial biomass, accumulated in trees through cambial activity.
Aims : Here, we present a novel, simple, and fast approach to accurately estimate the intra-annual dynamics of aboveground woody biomass production based on image analysis of forming xylem sections.
Methods : During the 2015 growing season, we weekly collected wood samples (microcores) containing the forming xylem on seven Norway spruces (Picea abies (L.) Karst), grown in Hesse forest (North-East France). The microcores were prepared to allow the observation of the forming tissues with an optical microscope. Xylem apparent density and radial increment were then measured directly on images of the histological sections. In order to compare our “histologic approach” with the previously published “cellular approach,” we also counted the number of tracheids in each differentiation zones, and measured the tracheid dimensions all along the last-formed tree ring.
Results : The two approaches yielded comparable meaningful results, describing xylem size increase and aboveground woody biomass production as bell-shaped curves culminating in May and June respectively. However, the histologic approach provided a shorter time lag between xylem size increase and biomass production than the cellular one.
Conclusion : Better quantification of the shift between stem growth in size and in biomass will require addressing the knowledge gap regarding lignin deposition kinetics. Nevertheless, our novel histologic approach is simpler and more direct than the cellular one, and may open the way to a first quantification of intra-annual dynamics of woody biomass production in angiosperms, where the cellular approach is hardly applicable.Numéro de notice : A2019-650 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0846-7 En ligne : https://doi.org/10.1007/s13595-019-0846-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97454
in Annals of Forest Science > Vol 76 n° 3 (September 2019) . - n° 62[article]Validating the use of object-based image analysis to map commonly recognized landform features in the United States / Samantha T. Arundel in Cartography and Geographic Information Science, Vol 46 n° 5 (September 2019)
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Titre : Validating the use of object-based image analysis to map commonly recognized landform features in the United States Type de document : Article/Communication Auteurs : Samantha T. Arundel, Auteur ; Gaurav Sinha, Auteur Année de publication : 2019 Article en page(s) : pp 441 - 455 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] accident géographique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] base de données localisées
[Termes IGN] chaîne de traitement
[Termes IGN] données localisées 3D
[Termes IGN] Etats-Unis
[Termes IGN] relation spatiale
[Termes IGN] relief
[Termes IGN] toponymie localeRésumé : (Auteur) The U.S. Geological Survey (USGS) National Geospatial Program (NGP) seeks to i) create semantically accessible terrain features from the pixel-based 3D Elevation Program (3DEP) data, and ii) enhance the usability of the USGS Geographic Names Information System (GNIS) by associating boundaries with GNIS features whose spatial representation is currently limited to 2D point locations. Geographic object-based image analysis (GEOBIA) was determined to be a promising method to approach both goals. An existing GEOBIA workflow was modified and the resulting segmented objects and terrain categories tested for a strategically chosen physiographic province in the mid-western US, the Ozark Plateaus. The chi-squared test of independence confirmed that there is significant overall spatial association between terrain categories of the GEOBIA and GNIS feature classes. Contingency table analysis also suggests strong category-specific associations between select GNIS and GEOBIA classes. However, 3D visual analysis revealed that GEOBIA objects resembled segmented regions more than they did individual landform objects, with their boundaries often failing to correspond to match what people would likely perceive as landforms. Still, objects derived through GEOBIA can provide initial baseline landscape divisions that can improve the efficiency of more specialized feature extraction methods. Numéro de notice : A2019-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1526652 Date de publication en ligne : 07/11/2018 En ligne : https://doi.org/10.1080/15230406.2018.1526652 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93173
in Cartography and Geographic Information Science > Vol 46 n° 5 (September 2019) . - pp 441 - 455[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2019051 RAB Revue Centre de documentation En réserve L003 Disponible Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data / Sitinor Atikah Nordin in Geocarto international, vol 34 n° 11 ([15/08/2019])
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Titre : Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data Type de document : Article/Communication Auteurs : Sitinor Atikah Nordin, Auteur ; Zulkiflee Abd Latif, Auteur ; Hamdan Omar, Auteur Année de publication : 2019 Article en page(s) : pp 1218 - 1236 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] analyse multibande
[Termes IGN] Asie du sud-est
[Termes IGN] bande rouge
[Termes IGN] canopée
[Termes IGN] capteur hyperspectral
[Termes IGN] carte forestière
[Termes IGN] forêt tropicale
[Termes IGN] image hyperspectrale
[Termes IGN] image proche infrarouge
[Termes IGN] image satellite
[Termes IGN] niveau de gris (image)
[Termes IGN] réflectance végétale
[Termes IGN] segmentation d'image
[Termes IGN] teneur en chlorophylle des feuilles
[Termes IGN] tourbièreRésumé : (Auteur) Individual tree crown segmentation is important step for deriving various information for fine-scale analysis of ecological process. However, only several studies have applied tree crown segmentation in tropical forest ecosystems, especially in mixed peat swamp forests. In this study, hyperspectral data were used to detect changes in the biochemical and biophysical characteristics, which are important factors for tree crown segmentation. Principal Component Analysis method was performed to investigate its influence on crown segmentation. Visually Selected PCs, 160 PCs and 160 Spectral Bands image were used and two segmentation techniques; Watershed Transformation and Region Growing segmentation were applied on those images. The highest accuracy was achieved for the crown segmentation is using Region Growing segmentation, based on 1:1 measurement, D value and RMSE value. The results obtained from 160 PCs image using region growing algorithm shows better accuracy with D value of 0.2 (80% accuracy, 20% error) and RMSE of 9.9 m2. Numéro de notice : A2019-463 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1475511 Date de publication en ligne : 24/05/2018 En ligne : https://doi.org/10.1080/10106049.2018.1475511 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93605
in Geocarto international > vol 34 n° 11 [15/08/2019] . - pp 1218 - 1236[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2019111 RAB Revue Centre de documentation En réserve L003 Disponible Land-cover change in the Wulagai grassland, Inner Mongolia of China between 1986 and 2014 analysed using multi-temporal Landsat images / Temulun Tangud in Geocarto international, vol 34 n° 11 ([15/08/2019])
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Titre : Land-cover change in the Wulagai grassland, Inner Mongolia of China between 1986 and 2014 analysed using multi-temporal Landsat images Type de document : Article/Communication Auteurs : Temulun Tangud, Auteur ; Kenlo Nasahara, Auteur ; Habura Borjigin, Auteur ; Hasi Bagan, Auteur Année de publication : 2019 Article en page(s) : pp 1237 - 1251 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] carte d'occupation du sol
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] image Landsat
[Termes IGN] maillage
[Termes IGN] Mongolie intérieure (Chine)
[Termes IGN] prairie
[Termes IGN] série temporelle
[Termes IGN] steppe
[Termes IGN] zone arideRésumé : (Auteur) The Inner Mongolian steppe is a vast grassland ecosystem that has long been home to nomadic pastoralists. However, this steppe is experiencing grassland degradation as well as more frequent sand storms. The objective of this study was to detect land-cover changes in the Wulagai grassland of Inner Mongolia using multi-temporal Landsat images from 1986 to 2014, and to determine the factors driving these changes and their impacts. Land-cover maps for 1986, 1995, 2000, 2006 and 2014 were produced using the Support Vector Machine method. Subsequently, 300 m × 300 m grid-cell vector map which covered Wulagai grassland was made to detect land-cover changes and correlations between land-cover classes. The results show degradation trend from 1986 to 2014. Grid-cell-based spatial correlation analysis confirmed a strong negative correlation between grassland and barren, indicating that grassland degradation in this region is due to the regional modernization over the past 28 years. Numéro de notice : A2019-464 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1478457 Date de publication en ligne : 01/06/2018 En ligne : https://doi.org/10.1080/10106049.2018.1478457 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93607
in Geocarto international > vol 34 n° 11 [15/08/2019] . - pp 1237 - 1251[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2019111 RAB Revue Centre de documentation En réserve L003 Disponible A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm / Ana Claudia Dos Santos Luciano in International journal of applied Earth observation and geoinformation, vol 80 (August 2019)
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Titre : A generalized space-time OBIA classification scheme to map sugarcane areas at regional scale, using Landsat images time-series and the random forest algorithm Type de document : Article/Communication Auteurs : Ana Claudia Dos Santos Luciano, Auteur ; Michelle Cristina Araújo Picoli, Auteur ; Jansle Vieira Rocha, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 127-136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] apprentissage automatique
[Termes IGN] Brésil
[Termes IGN] carte agricole
[Termes IGN] classification dirigée
[Termes IGN] classification orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] extraction de données
[Termes IGN] image à haute résolution
[Termes IGN] image Landsat
[Termes IGN] production agricole
[Termes IGN] Saccharum officinarum
[Termes IGN] série temporelle
[Termes IGN] surface cultivée
[Termes IGN] zone d'intérêtRésumé : (auteur) The monitoring of sugarcane areas is important for sustainable planning and management of the sugarcane industry in Brazil. We developed an operational Object-Based Image Analysis (OBIA) classification scheme, with generalized space-time classifier, for mapping sugarcane areas at the regional scale in São Paulo State (SP). Binary random forest (RF) classification models were calibrated using multi-temporal data from Landsat images, at 10 sites located across SP. Space and time generalization were tested and compared for three approaches: a local calibration and application; a cross-site spatial generalization test with the RF model calibrated on a site and applied on other sites; and a unique space–time classifier calibrated with all sites together on years 2009–2014 and applied to the entire SP region on 2015. The local RF models Dice Coefficient (DC) accuracies at sites 1 to 8 were between 0.83 and 0.92 with an average of 0.89. The cross-site classification accuracy showed an average DC of 0.85, and the unique RF model had a DC of 0.89 when compared with a reference map of 2015. The results demonstrated a good relationship between sugarcane prediction and the reference map for each municipality in SP, with R² = 0.99 and only 5.8% error for the total sugarcane area in SP, and compared with the area inventory from the Brazilian Institute of Geography and Statistics, with R² = 0.95 and –1% error for the total sugarcane area in SP. The final unique RF model allowed monitoring sugarcane plantations at the regional scale on independent year, with efficiency, low-cost, limited resources and a precision approximating that of a photointerpretation. Numéro de notice : A2019-470 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2019.04.013 Date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.1016/j.jag.2019.04.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93612
in International journal of applied Earth observation and geoinformation > vol 80 (August 2019) . - pp 127-136[article]Improving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours / David Griffiths in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)
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