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Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)  

Public [article]  inForestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 686 - 696 Titre : Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds Type de document : Article/Communication Auteurs : Paweł Hawryło, Auteur ; Piotr Tompalski, Auteur ; Piotr Wezyk, Auteur Année de publication : 2017 Article en page(s) : pp 686 - 696 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image infrarouge couleur [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] régression linéaire [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Recent research has shown that image-derived point clouds (IPCs) are a highly competitive alternative to airborne laser scanning (ALS) data in the context of selected forest inventory activities. However, there is still a need for investigating different kinds of aerial images used for point cloud generation. This study compares the effectiveness of IPCs derived from true colour (RGB) and colour infrared (CIR) aerial images with ALS data for growing stock volume estimation of single canopy layer Scots pine stands. A multiple linear regression method was used to create predictive models. All models predicted growing stock volume with low root mean square errors – ALS: 15.2%, IPC-CIR: 17.0% and IPC-RGB: 17.5%. The following variables for each data type were found to be the most robust: ALS – mean height of points, percentage of all returns above mean height of points, interquartile range of point heights; IPC-CIR – mean height of points, percentage of all returns above mode height of points, canopy relief ratio; IPC-RGB – mean height of points and canopy relief ratio. Our results show that for single canopy layer Scots pine dominated stands it is possible to predict growing stock volume using IPCs with a comparable accuracy as using ALS data. The comparable performance of IPC-RGB and IPC-CIR based models suggests that a mixed usage of RGB and CIR data in retrospective studies could be possible. Numéro de notice : A2017-904 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx026 En ligne : https://doi.org/10.1093/forestry/cpx026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93205 [article]

Statistical atmospheric parameter retrieval largely benefits from spatial–spectral image compression / Joaquín García-Sobrino in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 4 (April 2017) . - pp. 2213 - 2224 Titre : Statistical atmospheric parameter retrieval largely benefits from spatial–spectral image compression Type de document : Article/Communication Auteurs : Joaquín García-Sobrino, Auteur ; Joan Serra-Sagristà, Auteur ; Valero Laparra, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp. 2213 - 2224 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] compression d'image [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] humidité de l'air [Termes descripteurs IGN] image infrarouge couleur [Termes descripteurs IGN] image MetOp-IASI [Termes descripteurs IGN] interférométrie [Termes descripteurs IGN] température de l'air Résumé : (Auteur) The infrared atmospheric sounding interferometer (IASI) is flying on board of the Metop satellite series, which is part of the EUMETSAT Polar System. Products obtained from IASI data represent a significant improvement in the accuracy and quality of the measurements used for meteorological models. Notably, the IASI collects rich spectral information to derive temperature and moisture profiles, among other relevant trace gases, essential for atmospheric forecasts and for the understanding of weather. Here, we investigate the impact of near-lossless and lossy compression on IASI L1C data when statistical retrieval algorithms are later applied. We search for those compression ratios that yield a positive impact on the accuracy of the statistical retrievals. The compression techniques help reduce certain amount of noise on the original data and, at the same time, incorporate spatial-spectral feature relations in an indirect way without increasing the computational complexity. We observed that compressing images, at relatively low bit rates, improves results in predicting temperature and dew point temperature, and we advocate that some amount of compression prior to model inversion is beneficial. This research can benefit the development of current and upcoming retrieval chains in infrared sounding and hyperspectral sensors. Numéro de notice : A2017-173 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1109/TGRS.2016.2639099 Format de la ressource électronique : URL bulletin Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84722 [article]

An operational high-resolution forest inventory / Julianno Sambatti in GIM international [en ligne], vol 30 n° 10 (October 2016)

Public [article]  inGIM international [en ligne] > vol 30 n° 10 (October 2016) . - pp 42 - 45 Titre : An operational high-resolution forest inventory Type de document : Article/Communication Auteurs : Julianno Sambatti, Auteur ; Dwight P. Crouse, Auteur ; Bruce MacArthur, Auteur ; Ian Moss, Auteur Année de publication : 2016 Article en page(s) : pp 42 - 45 Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image infrarouge couleur [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] traitement d'image [Vedettes matières IGN] Inventaire forestier Résumé : (éditeur) Forestry operations currently rely heavely on forest inventories that employ field plot data as a basis for estimating forest attributes. This labour-intensive approach provides limited information and has become a costly bottleneck in completing operating. Remote sensing can be used to obtain more accurate and comprehensive forest inventories with less effort. This article discusses high resolution forest inventory services (HIRISs) which combine state-of-the-art remote sensing technologies and computer analytics to produce operational forest inventories that help to improve the efficiency of various forest management activities. Numéro de notice : A2016-737 Thématique : FORET/IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82270 [article]

Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing / Jerome O’Connell in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)    

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 109 (November 2015) . - pp 165 - 177 Titre : Wide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing Type de document : Article/Communication Auteurs : Jerome O’Connell, Auteur ; Ute Bradter, Auteur ; Tim G. Benton, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 165 - 177 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] algorithme d'apprentissage [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] Angleterre [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] habitat d'espèce [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image infrarouge couleur [Termes descripteurs IGN] oiseau Résumé : (auteur) Natural and semi-natural habitats in agricultural landscapes are likely to come under increasing pressure with the global population set to exceed 9 billion by 2050. These non-cropped habitats are primarily made up of trees, hedgerows and grassy margins and their amount, quality and spatial configuration can have strong implications for the delivery and sustainability of various ecosystem services. In this study high spatial resolution (0.5 m) colour infrared aerial photography (CIR) was used in object based image analysis for the classification of non-cropped habitat in a 10,029 ha area of southeast England. Three classification scenarios were devised using 4 and 9 class scenarios. The machine learning algorithm Random Forest (RF) was used to reduce the number of variables used for each classification scenario by 25.5 % ± 2.7%. Proportion of votes from the 4 class hierarchy was made available to the 9 class scenarios and where the highest ranked variables in all cases. This approach allowed for misclassified parent objects to be correctly classified at a lower level. A single object hierarchy with 4 class proportion of votes produced the best result (kappa 0.909). Validation of the optimum training sample size in RF showed no significant difference between mean internal out-of-bag error and external validation. As an example of the utility of this data, we assessed habitat suitability for a declining farmland bird, the yellowhammer (Emberiza citronella), which requires hedgerows associated with grassy margins. We found that ∼22% of hedgerows were within 200 m of margins with an area >183.31 m2. The results from this analysis can form a key information source at the environmental and policy level in landscape optimisation for food production and ecosystem service sustainability. Numéro de notice : A2015-862 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.09.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79243 [article]

Documents numériques

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Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution / Ivan Balenović in Annals of forest research, vol 58 n° 1 (January 2015)  

Public [article]  inAnnals of forest research > vol 58 n° 1 (January 2015) . - pp 125 - 143 Titre : Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution Type de document : Article/Communication Auteurs : Ivan Balenović, Auteur ; Ante Seletković, Auteur ; Renata Pernar, Auteur ; Anamarija Jazbec, Auteur Année de publication : 2015 Article en page(s) : pp 125 - 143 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes descripteurs IGN] estimation quantitative [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image infrarouge couleur [Termes descripteurs IGN] pas d'échantillonnage au sol [Termes descripteurs IGN] placette d'échantillonnage Résumé : (auteur) Tree height is one of the more fundamental measurements in forest inventories. In addition to classical field measurements, tree height may be estimated by remote sensing methods, such as by photogrammetric measurements of aerial images. Since it has been found and generally accepted that the extraction of forest and tree data from classical analogue aerial photographs has certain limitations, especially in the densely canopied forests, the usefulness of photogrammetric-based forest inventory in many countries remains a controversial issue. Therefore, this paper focuses on investigating the possibility of applying digital photogrammetric method to estimate mean stand height. Photogrammetric stereo-measurements of tree height were conducted on colour infrared images of high spatial resolution (ground sample distance – GSD – of 30 cm and 10 cm) using a digital photogrammetric workstation. The height of each tree within 183 sample plots (14 subcompartments) were calculated as the difference between the tree top elevations determined with the aerial images and the corresponding tree bottom elevations determined from the digital terrain model. To compare the photogrammetric- and field-estimated mean stand heights, the mean plot heights were calculated for both photogrammetric and field estimates of tree heights. Repeated measurements using ANOVA testing did not reveal a statistically significant difference (p > 0.05) between the field-estimated and photogrammetric-estimated mean stand heights using the 30 cm and 10 cm GSD digital aerial images. Deviations of the mean stand heights estimated using the images of both spatial resolutions were similar to the field-estimated heights. Using the 30 cm images the deviations of the photogrammetrically estimated mean stand height amounted to 0.35 m (1.59%) on average, whereas using the 10 cm images the deviations amounted to 0.31 m (1.41%) compared to the field estimation. Therefore, it can be concluded that the 30 cm GSD aerial images allow for the photogrammetric measurement of mean stand heights with accuracy similar to 10 cm GSD aerial images. In addition, 30 cm GSD aerial images are more favourable financially since the same area of interest could be covered with a considerably smaller number of images than of the 10 cm GSD aerial images. Numéro de notice : A2015-715 Thématique : FORET/IMAGERIE Nature : Article En ligne : http://www.afrjournal.org/index.php/afr/article/view/300 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78358 [article]

Etude expérimentale en cartographie de la végétation par télédétection / Vanessa Sellin in Cybergeo, European journal of geography, n° 2015 (2015)  

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Orthophotographie nocturne à haute résolution : la nuit, vue du ciel / Eva Frangiamone in Géomatique suisse, vol 112 n° 12 (décembre 2014)

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Use of handheld thermal imager data for airborne mapping of fire radiative power and energy and flame front rate of spread / Ronan Paugam in IEEE Transactions on geoscience and remote sensing, vol 51 n° 6 Tome 1 (June 2013)

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Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery / Ujjwal Maulik in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)

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Road network extraction in suburban areas / A. Grote in Photogrammetric record, vol 27 n° 137 (March - May 2012)

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Classification orientée-objet supervisée d'une forêt avec une sélection guidée d'attributs personnalisés / Olivier de Joinville in Revue Française de Photogrammétrie et de Télédétection, n° 195 (Novembre 2011)

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La carte forestière version 2 à l'IFN : de la réalisation à la diffusion / Thierry Touzet in Rendez-vous techniques, n° 32 (printemps 2011) 

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La carte forestière sans papier / Thierry Touzet in Le monde des cartes, n° 206 (décembre 2010)

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Riparian buffer evaluation, remote sensing for environmental protection at CFB Gagetow / J. Leclerc in GIM international, vol 23 n° 9 (September 2009)

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Combined object-based classification and manual interpretation-synergies for a quantitative assessment of parcels and biotopes / S. Lang in Geocarto international, vol 24 n° 2 (April - May 2009)  

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