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Effects of radiometric correction on cover type and spatial resolution for modeling plot level forest attributes using multispectral airborne LiDAR data / Wai Yeung Yan in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 169 (November 2020) . - pp 152 - 165 Titre : Effects of radiometric correction on cover type and spatial resolution for modeling plot level forest attributes using multispectral airborne LiDAR data Type de document : Article/Communication Auteurs : Wai Yeung Yan, Auteur ; Karin Y. Van Ewijk, Auteur ; Paul M. Treitz, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 152 - 165 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] artefact [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] correction d'image [Termes descripteurs IGN] correction radiométrique [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] délignage [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] Ontario [Termes descripteurs IGN] restauration d'image [Termes descripteurs IGN] semis de points Résumé : (auteur) In order to use the airborne LiDAR intensity in conjunction with the height-derived information for forest modeling and classification purposes, radiometric correction is deemed to be a critical pre-processing requirement. In this study, we implemented a LiDAR scan line correction (LSLC) and an overlap-driven intensity correction (OIC) to remove the stripe artifacts that appeared within the individual flight lines and overlapping regions of adjacent flight lines of a multispectral LiDAR dataset. We tested the effectiveness of these corrections in various land/forest cover types in a temperate mixed mature forest in Ontario, Canada. Subsequently, we predicted three plot level forest attributes, i.e., basal area (BA), quadratic mean diameter (QMD), and trees per hectare (TPH), using different combinations of height and intensity metrics derived from the multispectral LiDAR data to determine if LiDAR intensity data (corrected and uncorrected) improved predictions over models that utilize LiDAR height-derived information only. The results show that LSLC can reduce the intensity banding effect by 0.19–23.06% in channel 1 (1550 nm) and 4.79–66.87% in channel 2 (1064 nm) at the close-to-nadir region. The combined effect of LSLC and OIC is notable particularly at the swath edges. After implementing both methods, the intensity homogeneity is improved by 5.51–12% in channel 1, 6.37–42.93% in channel 2, and 6.48–33.77% in channel 3 (532 nm). Our results further demonstrate that BA and QMD predictions in our study area gained little from additional LiDAR intensity metrics. Intensity metrics from multiple LiDAR channels and intensity normalized difference vegetation index (NDVI) metrics did improve TPH predictions up to 7.2% in RMSE and 1.8% in Bias. However, our lowest TPH prediction errors (%RMSE) were still approximately 10% larger than for BA and QMD. We observed only minimal differences in plot level BA, QMD, and TPH predictions between models using original and corrected intensity. We attribute this to: (i) the lower effectiveness of radiometric correction in forest versus grassland, bare soil and road land cover types, and (ii) the effect of spatial resolution on intensity noise. Numéro de notice : A2020-640 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.09.001 date de publication en ligne : 22/09/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.09.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96063 [article]

What influences the long-term development of mixtures in British forests? / William L. Mason in Forestry, an international journal of forest research, vol 93 n° 4 (July 2020)  

Public [article]  inForestry, an international journal of forest research > vol 93 n° 4 (July 2020) . - pp 545 - 556 Titre : What influences the long-term development of mixtures in British forests? Type de document : Article/Communication Auteurs : William L. Mason, Auteur ; T. Connolly, Auteur Année de publication : 2020 Article en page(s) : pp 545 - 556 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse comparative [Termes descripteurs IGN] Betula pendula [Termes descripteurs IGN] composition d'un peuplement forestier [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] foresterie [Termes descripteurs IGN] Grande-Bretagne [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] Larix kaempferi [Termes descripteurs IGN] ombre [Termes descripteurs IGN] peuplement mélangé [Termes descripteurs IGN] peuplement pur [Termes descripteurs IGN] picea sitchensis [Termes descripteurs IGN] Pinus contorta [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] surface terrière [Termes descripteurs IGN] tsuga heterophylla [Vedettes matières IGN] Sylviculture Résumé : (auteur) Six experiments were established between 1955 and 1962 in different parts of northern and western Britain which used replicated randomized block designs to compare the performance of two species 50:50 mixtures with pure stands of the component species. The species involved were variously lodgepole pine (Pinus contorta Dougl.), Japanese larch (Larix kaempferi Lamb. Carr.), Scots pine (Pinus sylvestris L.), silver birch (Betula pendula Roth.), Sitka spruce (Picea sitchensis Bong. Carr.) and western hemlock (Tsuga heterophylla Raf. Sarg.). The first four species are light demanding, while Sitka spruce is of intermediate shade tolerance and western hemlock is very shade tolerant: only Scots pine and silver birch are native to Great Britain. In three experiments (Bickley, Ceannacroc, Hambleton), the mixtures were of two light-demanding species, while at the other three sites, the mixture tested contained species of different shade tolerance. The experiments were followed for around 50 years, similar to a full rotation of even-aged conifer stands in Britain. Five experiments showed a tendency for one species to dominate in mixture, possibly reflecting differences in the shade tolerance or other functional traits of the component species. In the three experiments, the basal area of the mixtures at the last assessment was significantly higher than predicted based on the performance of the pure stands (i.e. the mixture ‘overyielded’). In two of these cases, the mixture had had a higher basal area than found in the more productive pure stand indicating ‘transgressive overyielding’. Significant basal area differences were generally more evident at the later assessment date. The exception was in a Scots pine: western hemlock mixture where greater overyielding at the earlier date indicated a nursing (‘facilitation’) effect. In the remaining experiments, the performance of the mixture conformed to predictions from the growth of the component species in pure stands. Taken overall, the results suggest that functional traits can be used to interpret the performance of mixtures but prediction of the outcome will require better understanding of the interplay between species and site characteristics plus the influence of silvicultural interventions. Numéro de notice : A2020-580 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1093/forestry/cpaa003 date de publication en ligne : 11/02/2020 En ligne : https://doi.org/10.1093/forestry/cpaa003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95899 [article]

An Illumination Insensitive descriptor combining the CSLBP features for street view images in augmented reality: experimental studies / Zejun Xiang in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 6 (June 2020) . - 33 p. Titre : An Illumination Insensitive descriptor combining the CSLBP features for street view images in augmented reality: experimental studies Type de document : Article/Communication Auteurs : Zejun Xiang, Auteur ; Ronghua Yang, Auteur ; Chang Deng, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 33 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algorithme d'appariement [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] DAISY [Termes descripteurs IGN] éclairage [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] motif binaire local [Termes descripteurs IGN] réalité augmentée [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] SIFT (algorithme) [Termes descripteurs IGN] SURF (algorithme) Résumé : (auteur) Numéro de notice : A2020-312 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9060362 date de publication en ligne : 01/06/2020 En ligne : https://doi.org/10.3390/ijgi9060362 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95166 [article]

Multiscale Intensity Propagation to Remove Multiplicative Stripe Noise From Remote Sensing Images / Hao Cui in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 4 (April 2020) . - pp 2308 - 2323 Titre : Multiscale Intensity Propagation to Remove Multiplicative Stripe Noise From Remote Sensing Images Type de document : Article/Communication Auteurs : Hao Cui, Auteur ; Peng Jia, Auteur ; Guo Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2308 - 2323 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse des correspondances [Termes descripteurs IGN] bande spectrale [Termes descripteurs IGN] capteur à balayage [Termes descripteurs IGN] correction d'image [Termes descripteurs IGN] dégradation d'image [Termes descripteurs IGN] délignage [Termes descripteurs IGN] filtrage du bruit [Termes descripteurs IGN] filtrage du rayonnement [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] itération [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] pollution acoustique Résumé : (auteur) Sensor instability, dark currents, and other factors often cause stripe noise corruption in hyperspectral remote sensing images and severely limit their application in practical purposes. Previous studies have proposed numerous destriping algorithms that have yielded impressive results. Although most destriping algorithms are based on the premise of additive noise, a few studies have focused directly on multiplicative stripe noise. This article fully analyzes the characteristics of the stripe noise of OHS-01 images and proposes a multiplicative stripe noise removal method. Specifically, stripe noise is tackled by performing radiometric normalization of different columns in the image. First, the relative gain coefficients of adjacent columns are separated based on prior knowledge. Second, the local relative intensity correspondence of the image columns are established by means of intensity propagation, intensity connection, and so on. Finally, the above-mentioned process is iterated in multiscale space, and the accumulated gain correction coefficient maps were used to correct the radiation of the original image. The results of extensive experiments on simulated and real remote sensing image data demonstrate that the proposed method can, in most cases, yield desirable results. In certain cases, the results are even better, visually, and quantitatively, than those obtained using classical algorithms. Moreover, the proposed method has high robustness and efficiency. Thus, it can conform to the requirements of engineering applications. Numéro de notice : A2020-194 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2947599 date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2947599 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94861 [article]

Reducing shadow effects on the co-registration of aerial image pairs / Matthew Plummer in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 3 (March 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 3 (March 2020) . - pp 177 - 186 Titre : Reducing shadow effects on the co-registration of aerial image pairs Type de document : Article/Communication Auteurs : Matthew Plummer, Auteur ; Douglas A. Stow, Auteur ; Emmanuel Storey, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 177 - 186 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse de données [Termes descripteurs IGN] correction des ombres [Termes descripteurs IGN] détection automatique [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] effet d'ombre [Termes descripteurs IGN] enregistrement de données [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] intensité lumineuse [Termes descripteurs IGN] masque [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] SIFT (algorithme) Résumé : (auteur) Image registration is an important preprocessing step prior to detecting changes using multi-temporal image data, which is increasingly accomplished using automated methods. In high spatial resolution imagery, shadows represent a major source of illumination variation, which can reduce the performance of automated registration routines. This study evaluates the statistical relationship between shadow presence and image registration accuracy, and whether masking and normalizing shadows leads to improved automatic registration results. Eighty-eight bitemporal aerial image pairs were co-registered using software called Scale Invariant Features Transform (SIFT) and Random Sample Consensus (RANSAC) Alignment (SARA). Co-registration accuracy was assessed at different levels of shadow coverage and shadow movement within the images. The primary outcomes of this study are (1) the amount of shadow in a multi-temporal image pair is correlated with the accuracy/success of automatic co-registration; (2) masking out shadows prior to match point select does not improve the success of image-to-image co-registration; and (3) normalizing or brightening shadows can help match point routines find more match points and therefore improve performance of automatic co-registration. Normalizing shadows via a standard linear correction provided the most reliable co-registration results in image pairs containing substantial amounts of relative shadow movement, but had minimal effect for pairs with stationary shadows. Numéro de notice : A2020-147 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.4.177 date de publication en ligne : 01/03/2020 En ligne : https://doi.org/10.14358/PERS.86.4.177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94776 [article]

Simultaneous intensity bias estimation and stripe noise removal in infrared images using the global and local sparsity constraints / Li Liu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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Automatic illumination-invariant image-to-geometry registration in outdoor environments / Christian Kehl in Photogrammetric record, vol 32 n° 158 (June - july 2017)  

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Hyperspectral and lidar intensity data fusion : A framework for the rigorous correction of illumination, anisotropic effects, and cross calibration / Maximilian Brell in IEEE Transactions on geoscience and remote sensing, vol 55 n° 5 (May 2017)  

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An inquiry on contrast enhancement methods for satellite images / Jose-Luis Lisani in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

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Automated co-registration of satellite images through luminance transformation / Deniz Gerçek in Photogrammetric record, vol 31 n° 156 (December 2016 - February 2017)  

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An intensity recovery algorithm (IRA) for minimizing the edge effect of LIDAR data / Fabiane Bordin in European journal of remote sensing, vol 49 (2016)  

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Efficient terrestrial laser scan segmentation exploiting data structure / Hamid Mahmoudabadi in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

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Satellite images analysis for shadow detection and building height estimation / Gregoris Liasis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)  

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3D leaf water content mapping using terrestrial laser scanner backscatter intensity with radiometric correction / Xi Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 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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