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Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging / Bo Li in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 161 -1 72 Titre : Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging Type de document : Article/Communication Auteurs : Bo Li, Auteur ; Xiangming Xu, Auteur ; Li Zhang, Auteur Année de publication : 2020 Article en page(s) : pp 161 -1 72 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] hauteur de la végétation [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] pomme de terre [Termes descripteurs IGN] régression des moindres carrés partiels [Termes descripteurs IGN] rendement agricole Résumé : (auteur) Rapid and accurate biomass and yield estimation facilitates efficient plant phenotyping and site-specific crop management. A low altitude unmanned aerial vehicle (UAV) was used to acquire RGB and hyperspectral imaging data for a potato crop canopy at two growth stages to estimate the above-ground biomass and predict crop yield. Field experiments included six cultivars and multiple treatments of nitrogen, potassium, and mixed compound fertilisers. Crop height was estimated using the difference between digital surface model and digital elevation models derived from RGB imagery. Combining with two narrow-band vegetation indices selected by the RReliefF feature selection algorithm. Random Forest regression models demonstrated high prediction accuracy for both fresh and dry above-ground biomass, with a coefficient of determination (r2) > 0.90. Crop yield was predicted using four narrow-band vegetation indices and crop height (r2 = 0.63) with imagery data obtained 90 days after planting. A Partial Least Squares regression model based on the full wavelength spectra demonstrated improved yield prediction (r2 = 0.81). This study demonstrated the merits of UAV-based RGB and hyperspectral imaging for estimating the above-ground biomass and yield of potato crops, which can be used to assist in site-specific crop management. Numéro de notice : A2020-125 Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.013 date de publication en ligne : 28/02/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.013 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94750 [article]

Artificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of Turkey / Alkan Günlü in Geocarto international, Vol 35 n° 1 ([02/01/2020])  

Public [article]  inGeocarto international > Vol 35 n° 1 [02/01/2020] . - pp 17 - 28 Titre : Artificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of Turkey Type de document : Article/Communication Auteurs : Alkan Günlü, Auteur ; Ilker Erkanli, Auteur Année de publication : 2020 Article en page(s) : pp 17 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] carbone [Termes descripteurs IGN] Fagus (genre) [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] peuplement forestier [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] Turquie Résumé : (auteur) The goal of this study was to estimate aboveground stand carbon (AGSC) of pure beech stands in Turkey with ground measurements as well as topographic information and remote sensing data. For this purpose, 153 sample plots were collected from pure beech stands in study area. The AGSC of each sample plot was computed. Eight texture images (variance, dissimilarity, homogeneity, entropy, contrast, mean, second moment and correlation) with five window sizes (3 × 3, 5 × 5, 7 × 7, 9 × 9 and 11 × 11) generated from ALOS PALSAR L-band satellite image. The AGSC models predicting the relationships between ALOS PALSAR texture values and topographic information, and sample plot AGSC were developed by using multiple linear regressions (MLR). Also, artificial neural networks (ANNs) architectures were trained by comparing various numbers of neurons and activation functions in its network types. Our results revealed the ability of ANNs was better than MLR models to predict AGSC values. Numéro de notice : A2020-017 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1499817 date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1499817 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94410 [article]

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Remote Sensing Technology Applications in Forestry and REDD+ / Kim Calders (2020)  

Public contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB   Titre : Remote Sensing Technology Applications in Forestry and REDD+ Type de document : Monographie Auteurs : Kim Calders, Editeur scientifique ; Inge Jonckheere, Editeur scientifique ; Mikko Vastaranta, Editeur scientifique ; Joanne Nightingale, Editeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 244 p. ISBN/ISSN/EAN : 978-3-03928-471-9 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] canopée [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image Sentinel [Termes descripteurs IGN] Pinus massoniana [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] télémétrie laser aéroporté [Termes descripteurs IGN] télémétrie laser terrestre Résumé : (Editeur) Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion. Numéro de notice : 26296 Thématique : FORET/IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03928-471-9 date de publication en ligne : 07/04/2020 En ligne : https://doi.org/10.3390/books978-3-03928-471-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95009

Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden (2020)    

Public Titre : Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density Type de document : Article/Communication Auteurs : Baptiste Kerfriden, Auteur ; Jean-Daniel Bontemps , Auteur ; Jean-Michel Leban, Auteur Editeur : Research Square Année de publication : 2020 Importance : 20 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] capacité de rétention d'eau du sol [Termes descripteurs IGN] carbone [Termes descripteurs IGN] densité du bois [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] forêt tempérée [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] pinophyta [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Background: Biomass ratio (BR) is a forest state variable allowing the conversion of forest volume of growing stock into biomass. Despite huge intraspecific variation in wood density depending on the biotic and abiotic environments of tree growth, this variable is most often considered a tree species constant in C budgets. The aims were i) to identify variations in BR along decorrelated water, soil nutrition and elevation gradients, ii) to test for differences between broadleaved and conifer tree species in BR variations, and iii) to weight the contribution of interspecific and intraspecific diversity in BR variations. Methods: Analyses were based on massive wood density measurements performed with an X-ray medical scanner on 54,700 tree cores collected in 2016 and 2017 on the spatially systematic plot sampling design of the French national forest inventory (NFI) program. Results: BR variations along the three gradients were found significant. BR hence decreased by 73 kg.m-3 (conifers) and 126 kg.m-3 (broadleaves) along a 180 mm gradient of soil water holding capacity (SWHC). It also increased by 153 kg.m-3 on average along the full gradient of soil basicity Index (SBI). A negative trend along elevation was also identified, with an average decrease by 155 kg.m-3 from 200 to 2000 m of elevation. Species distribution was found to be the main cause of BR variations along these gradients. Conclusions: We report dependences of BR on both water (–), nutrient availability (+) and warmth (+) gradients, more acute in broadleaves than in conifers only for water availability. At the scale of the whole French forests, intraspecific variations in wood density do not affect BR estimations along these gradients. BR variations are mainly driven by the tree stand species composition along them. Numéro de notice : P2020-007 Thématique : FORET Nature : Article nature-HAL : Préprint DOI : 10.21203/rs.3.rs-27539/v1 En ligne : https://doi.org/10.21203/rs.3.rs-27539/v1 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95090

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Phosphorus availability in relation to soil properties and forest productivity in Pinus sylvestris L. plantations / Teresa Bueis in Annals of Forest Science [en ligne], Vol 76 n° 4 (December 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 76 n° 4 (December 2019) Titre : Phosphorus availability in relation to soil properties and forest productivity in Pinus sylvestris L. plantations Type de document : Article/Communication Auteurs : Teresa Bueis, Auteur ; Felipe Bravo, Auteur ; Valentin Pando, Auteur ; et al., Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] écosystème forestier [Termes descripteurs IGN] Espagne [Termes descripteurs IGN] industrie forestière [Termes descripteurs IGN] phosphore [Termes descripteurs IGN] Pinus sylvestris [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Key message : Pinus sylvestris L. productivity in Spanish plantations is driven by P availability, which, in turn, is determined by the activity of soil microorganisms, responsible for inorganic P solubilization; Fe and Al contents, responsible for P retention; and organic matter, which is source of organic P, inhibits its precipitation as insoluble compounds, and reduces P retention. Context : Phosphorus is often a limiting nutrient in forest ecosystems mainly due to the low solubility of P compounds and the sorption processes occurring in soils. Aims : The main aims of this work were to evaluate soil P availability, to assess which soil properties are driving P availability, and to study whether soil P availability is determining forest productivity in Pinus sylvestris L. plantations in Northern Spain. Methods : Soil properties and forest productivity were studied in 34 plots located in monospecific P. sylvestris plantations. Tiessen and Moir (Canadian Society of Soil Science 75–86, 1993) sequential fractionation method was carried out to determine different forms of soil P and to provide a comprehensive assessment of available P in soils. To explore the relationships between these variables, canonical correlation analyses and Pearson’s correlations were studied. Results : Significant correlations were found between P fractions and soil properties related to Fe and Al contents, organic matter, and microbial biomass. Besides, significant correlations were found between site index and the studied P fractions except for P extracted with anion exchange membrane (PAEM) and the recalcitrant P fraction. Conclusion : In the studied soils, P availability is low and the predominant fractions of P are the recalcitrant forms. Aluminum and iron contents in the soils studied play an important role in sorption processes related to the highly and moderately labile P fractions and the organic phosphorus. P availability seems to be regulated by both processes: biochemical mineralization, where phosphatase activity is relevant, and biological mineralization of the soil organic matter. Phosphorus availability affects forest productivity in the Pinus sylvestris plantations studied. Numéro de notice : A2019-531 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0882-3 date de publication en ligne : 18/10/2019 En ligne : https://doi.org/10.1007/s13595-019-0882-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94119 [article]

Mapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece / Maria Kampouri in Geocarto international, vol 34 n° 12 ([15/09/2019])  

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Free and open-source GIS technologies for the management of woody biomass / Michele Mangiameli in Applied geomatics, vol 11 n° 3 (September 2019)  

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Pressures and threats to nature related to human activities in European urban and suburban forests / Ewa Referowska-Chodak in Forests, vol 10 n° 9 (September 2019)  

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Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images / Jie Wang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Occlusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

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Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)  

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Tree and stand level estimations of Abies alba Mill. aboveground biomass / Andrzej M. Jagodzinski in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

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Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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Wood quality of black spruce and balsam fir trees defoliated by spruce budworm: A case study in the boreal forest of Quebec, Canada / Carlos Paixao in Forest ecology and management, vol 437 (1 April 2019)  

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Estimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data / Kalifa Goïta in Geocarto international, vol 34 n° 3 ([01/03/2019])  

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