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Improved topographic correction of forest image data using a 3D canopy reflectance model in multiple forward mode / S.A. Soenen in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)
[article]
Titre : Improved topographic correction of forest image data using a 3D canopy reflectance model in multiple forward mode Type de document : Article/Communication Auteurs : S.A. Soenen, Auteur ; Derek R. Peddle, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 1007 - 1027 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Alberta (Canada)
[Termes IGN] canopée
[Termes IGN] classe d'objets
[Termes IGN] correction du signal
[Termes IGN] forêt tempérée
[Termes IGN] image SPOT
[Termes IGN] modélisation 3D
[Termes IGN] Pinus (genre)
[Termes IGN] précision de la classification
[Termes IGN] réflectance végétale
[Termes IGN] varianceRésumé : (Auteur) In most forestry remote sensing applications in steep terrain, simple photometric and empirical (PE) topographic corrections are confounded as a result of stand structure and species assemblages that vary with terrain and the anisotropic reflective properties of vegetated surfaces. To address these problems, we present MFM-TOPO as a new physically-based modelling (PBM) approach for normalising topographically induced signal variance as a function of forest stand structure and sub-pixel scale components. MFM-TOPO uses the Li-Strahler geometric optical mutual shadowing (GOMS) canopy reflectance model in Multiple Forward Mode (MFM) to account for slope and aspect influences directly. MFM-TOPO has an explicit physical-basis and uses sun-canopy-sensor (SCS) geometry that is more appropriate than strictly terrain-based corrections in forested areas since it preserves the geotropic nature of trees (vertical growth with respect to the geoid) regardless of terrain, view and illumination angles. MFM-TOPO is compared against our recently developed SCS+C correction and a comprehensive set of other existing PE and SCS methods (cosine, C correction, Minnaert, statistical-empirical, SCS, and b correction) for removing topographically induced variance and for improving SPOT image classification accuracy in a Rocky Mountain forest in Kananaskis, Alberta Canada. MFM-TOPO removed the most terrain-based variance and provided the greatest improvement in classification accuracy within a species and stand density based class structure. For example, pine class accuracy was increased by 62% over shaded slopes, and spruce class accuracy was increased by 13% over more moderate slopes. In addition to classification, MFM-TOPO is suitable for retrieving biophysical parameters in mountainous terrain. Numéro de notice : A2008-007 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701311291 En ligne : https://doi.org/10.1080/01431160701311291 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29002
in International Journal of Remote Sensing IJRS > vol 29 n°3-4 (February 2008) . - pp 1007 - 1027[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-08021 RAB Revue Centre de documentation En réserve L003 Disponible Representing forested regions at small scales: automatic derivation from very large scale data / William A Mackaness in Cartographic journal (the), vol 45 n° 1 (February 2008)
[article]
Titre : Representing forested regions at small scales: automatic derivation from very large scale data Type de document : Article/Communication Auteurs : William A Mackaness, Auteur ; S. Perikleous, Auteur ; Omair Chaudhry, Auteur Année de publication : 2008 Article en page(s) : pp 6 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] 1:250.000
[Termes IGN] carte dérivée
[Termes IGN] forêt tempérée
[Termes IGN] généralisation automatique de données
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] grande échelle
[Termes IGN] Ordnance Survey (UK)
[Termes IGN] petite échelle
[Termes IGN] Royaume-Uni
[Termes IGN] service web géographiqueRésumé : (Auteur) As with any class of feature, it is important to be able to view woodland or forest at multiple levels of detail. At the detailed level, a map can show clusters of trees, tree types, tracks and paths; at the small scale, say 1:250 000, we can discern broad patterns of forests and other land use, which can inform planners and act as input to land resource models. Rather than store such information in separate databases (requiring multiple points of maintenance), the vision is that the information has a single point of storage and maintenance, and that from this detailed level, various, more generalised forms can be automatically derived. This paper presents a methodology and algorithm for automatically deriving forest patches suitable for representation at 1:250 000 scale directly from a detailed dataset. In addition to evaluation of the output, the paper demonstrates how such algorithms can be shared and utilised via 'generalisation web services', arguing that the sharing of such algorithms can help accelerate developments in map generalisation, and increase the uptake of research solutions within commercial systems. Copyright British Cartographic Society Numéro de notice : A2008-130 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/000870408X276576 En ligne : https://doi.org/10.1179/000870408X276576 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29125
in Cartographic journal (the) > vol 45 n° 1 (February 2008) . - pp 6 - 17[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-08011 RAB Revue Centre de documentation En réserve L003 Disponible Feature selection by genetic algorithms in object-based classification of Ikonos imagery for forest mapping in Flanders, Belgium / F.M.B. Van Coillie in Remote sensing of environment, vol 110 n° 4 (30/10/2007)
[article]
Titre : Feature selection by genetic algorithms in object-based classification of Ikonos imagery for forest mapping in Flanders, Belgium Type de document : Article/Communication Auteurs : F.M.B. Van Coillie, Auteur ; L.P.C. Verbeke, Auteur ; R.R. DE Wulf, Auteur Année de publication : 2007 Conférence : ForestSat 2007, forests and remote sensing : methods and operational tools 05/11/2007 07/11/2007 Montpellier France Article en page(s) : pp 476 - 487 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme génétique
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection d'objet
[Termes IGN] Flandre (Belgique)
[Termes IGN] forêt tempérée
[Termes IGN] image Ikonos
[Termes IGN] segmentation d'imageRésumé : (Auteur) Obtaining detailed information about the amount of forest cover is an important issue for governmental policy and forest management. This paper presents a new approach to update the Flemish Forest Map using IKONOS imagery. The proposed method is a three-step object-oriented classification routine that involves the integration of 1) image segmentation, 2) feature selection by Genetic Algorithms (GAs) and 3) joint Neural Network (NN) based object-classification. The added value of feature selection and neural network combination is investigated. Results show that, with GA-feature selection, the mean classification accuracy (in terms of Kappa Index of Agreement) is significantly higher (p Numéro de notice : A2007-412 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.03.020 En ligne : https://doi.org/10.1016/j.rse.2007.03.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28775
in Remote sensing of environment > vol 110 n° 4 (30/10/2007) . - pp 476 - 487[article]Repetitive interpolation: A robust algorithm for DTM generation from aerial Laser scanner data in forested terrain / A. Kobler in Remote sensing of environment, vol 108 n° 1 (15/05/2007)
[article]
Titre : Repetitive interpolation: A robust algorithm for DTM generation from aerial Laser scanner data in forested terrain Type de document : Article/Communication Auteurs : A. Kobler, Auteur ; Norbert Pfeifer, Auteur ; P. Ogrine, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 9 - 23 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] forêt tempérée
[Termes IGN] interpolation
[Termes IGN] lasergrammétrie
[Termes IGN] modèle numérique de terrain
[Termes IGN] semis de points
[Termes IGN] télémétrie laser aéroportéRésumé : (Auteur) We present a new algorithm for digital terrain model (DTM) generation from an airborne laser scanning point cloud, called repetitive interpolation (REIN). It is especially applicable in steep, forested areas where other filtering algorithms typically have problems distinguishing between ground returns and off-ground points reflected in the vegetation. REIN can produce a DTM either in a vector grid or in a TIN data structure. REIN is applied after an initial filtering, which involves removal of all negative outliers and removal of many, but not necessarily all, off-ground points by some existing filtering algorithm. REIN makes use of the redundancy in the initially filtered point cloud (FPC) in order to mitigate the effect of the residual off-ground points. Multiple independent random samples are taken from the initial FPC. From each sample, ground elevation estimates are interpolated at individual DTM locations. Because the lower bounds of the distributions of the elevation estimates at each DTM location are almost insensitive to positive outliers, the true ground elevations can be approximated by adding the global mean offset to the lower bounds, which is estimated from the data. The random sampling makes REIN unique among the methods of filtering airborne laser data. While other filters behave deterministically, always generating a filter error in special situations, in REIN, because of its random aspects, these errors do not occur in each sample, and typically cancel out in the final computation of DTM elevations. Reduction of processing time by parallelization of REIN is possible. REIN was tested in a test area of 2 hectares, encompassing steep relief covered by mixed forest. An Optech ALTM 1020 lidar was used, with a flying height of 260–300 m above the ground, the beam divergence was 0.3 mrad, and the obtained point cloud density for the last returns was 8.5 m- 2. A DTM grid was generated with 1 m horizontal resolution. The root mean square elevation error of the DTM ranged between 1 0.16 m and 1 0.37 m, depending on REIN sampling rate and number of samples taken, the lowest value achieved with 4 samples and using a 23% sampling rate. The paper also gives a short overview on existing filtering algorithms. Copyright Elsevier Numéro de notice : A2007-216 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.10.013 En ligne : https://doi.org/10.1016/j.rse.2006.10.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28579
in Remote sensing of environment > vol 108 n° 1 (15/05/2007) . - pp 9 - 23[article]Woody vegetation increase in Alpine areas: a proposal for a classification and validation scheme / M. Maggi in International Journal of Remote Sensing IJRS, vol 28 n° 1-2 (January 2007)
[article]
Titre : Woody vegetation increase in Alpine areas: a proposal for a classification and validation scheme Type de document : Article/Communication Auteurs : M. Maggi, Auteur ; C. Estreguil, Auteur ; P.J. Soille, Auteur Année de publication : 2007 Article en page(s) : pp 143-166 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Alpes-maritimes (06)
[Termes IGN] classification non dirigée
[Termes IGN] détection de changement
[Termes IGN] forêt tempérée
[Termes IGN] image Landsat
[Termes IGN] matrice
[Termes IGN] Mercantour, massif duRésumé : (auteur) This paper presents a change detection analysis based on a region growing segmentation approach which combines both spectral and spatial information. The test site is a French Alpine protected area, which like many other mountain areas is characterised by a general increase of forest and woody vegetation due to the abandonment of traditional land use practices. Two Landsat images of the years 1984 and 2000 were used and a classification scheme nomenclature based on four vegetation change classes, implying a gradual modification of land cover, was adopted. The accuracy of the change map was assessed both during two visits on the field and using a bi-temporal aerial photographic coverage. A sampling scheme specifically conceived for change detection products was adopted. Error matrices and accuracy indices to assess commission and omission errors of the change maps were generated.
The proposed change detection methodology circumvents limitations which are intrinsic to traditional classification procedures based only on spectral information. On the basis of the accuracy assessment, overall accuracy was 90.1% and the increase of woody vegetation turned out to be the vegetation change class better estimated, with user and producer accuracies of, respectively, 62.3% and 70%. However, confusion between the no change and the other vegetation change classes was noticed, due to standard problems encountered in change studies. Advantages and drawbacks of the use of multitemporal aerial photographs as the validation data set are also discussed.Numéro de notice : A2007-649 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600851785 En ligne : https://doi.org/10.1080/01431160600851785 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73801
in International Journal of Remote Sensing IJRS > vol 28 n° 1-2 (January 2007) . - pp 143-166[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07011 RAB Revue Centre de documentation En réserve L003 Disponible A spatial approach to forest-management optimization: linking GIS and multiple objective genetic algorithms / E.I. Ducheyne in International journal of geographical information science IJGIS, vol 20 n° 8 (september 2006)PermalinkTemperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences / Nathalie Bréda in Annals of Forest Science, Vol 63 n° 6 (september 2006)PermalinkAufnahmen flugzeuggetragener Laserscanner als Grundlage zur Erfassung von Strassen und Wegen in bewaldeten Gebieten [Des données par laserscanner aéroporté comme base pour l'extraction de voies et de chemins dans des régions boisées] / M. Attwenger (2006)PermalinkCaractérisation d'un habitat forestier tempéré par télédétection satellitale pour le suivi de populations aviennes : cas des mésanges en forêt de Larivour (Aube, France) / V. Godard in Photo interprétation, vol 41 n° 4 (Novembre 2005)PermalinkEstimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data / Z.J. Bortolot in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 6 (November 2005)PermalinkTypologie des paysages forestiers du sud du massif de Fontainebleau après la tempête de décembre 1999 / V. Godard in Revue internationale de géomatique, vol 15 n° 3 (septembre – novembre 2005)PermalinkCritères et indicateurs de la gestion des ressources forestières : prise en compte de la complexité et de l'approche écosystématique / Rodolphe Schlaepfer in Revue forestière française, Vol 56 n°5 (septembre - octobre 2004)PermalinkEstimation of interannual variation in productivity of global vegetation using NDVI data / Z.M. Chen in International Journal of Remote Sensing IJRS, vol 25 n° 16 (August 2004)PermalinkTwo decades of normalized difference vegetation index changes in South America: identifying the imprint of global change / J.M. Paruelo in International Journal of Remote Sensing IJRS, vol 25 n° 14 (July 2004)PermalinkMise en œuvre d'une solution de cartographie en ligne appliquée au document de gestion de l'espace agricole et forestier de la Savoie / Hélène Buissart (2004)Permalink