ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) . vol 126Paru le : 01/04/2017 |
[n° ou bulletin]
est un bulletin de ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) (1990 -)
[n° ou bulletin]
|
Exemplaires(3)
Code-barres | Cote | Support | Localisation | Section | Disponibilité |
---|---|---|---|---|---|
081-2017041 | RAB | Revue | Centre de documentation | En réserve L003 | Disponible |
081-2017043 | DEP-EXM | Revue | LASTIG | Dépôt en unité | Exclu du prêt |
081-2017042 | DEP-EAF | Revue | Nancy | Dépôt en unité | Exclu du prêt |
Dépouillements
Ajouter le résultat dans votre panierA comparison of two downscaling procedures to increase the spatial resolution of mapping actual evapotranspiration / Milad Mahour in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : A comparison of two downscaling procedures to increase the spatial resolution of mapping actual evapotranspiration Type de document : Article/Communication Auteurs : Milad Mahour, Auteur ; Valentyn Tolpekin, Auteur ; Alfred Stein, Auteur ; Ali Sharifi, Auteur Année de publication : 2017 Article en page(s) : pp 56 – 67 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] évapotranspiration
[Termes IGN] image à moyenne résolution
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat-8
[Termes IGN] image Terra-MODIS
[Termes IGN] Iran
[Termes IGN] irrigation
[Termes IGN] krigeage
[Termes IGN] mise à l'échelle
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] température au solRésumé : (auteur) This research addressed the effects of downscaling cokriging Land Surface Temperature (LST) on estimation of Actual Evapotranspiration (AET) from remote sensing images. Two procedures were followed. We first applied downscaling cokriging to a coarse resolution LST product of MODIS at 1000 m. With its outcome, daily AET of a medium spatial resolution (250 m) was obtained using the Surface Energy Balance System (SEBS). Second, we downscaled a coarse AET map to medium spatial resolution (250 m). For both procedures, the 250 m resolution MODIS NDVI product was used as a co-variable. Validation was carried out using Landsat 8 images, from which LST was derived from the thermal bands. The two procedures were applied to an agricultural area with a traditional irrigation network in Iran. We obtained an average LST value of 305.8 K as compared to a downscaled LST value of 307.0 K. Reference AET estimated with SEBS using Landsat 8 data was equal to 5.756 mm day−1, as compared with a downscaled AET value of 5.571 mm day−1. The RMSE between reference AET and downscaled AET was equal to 1.26 mm day−1 (r = 0.49) and between reference and downscaled LST to 3.67 K (r = 0.48). The study showed that AET values obtained with the two downscaling procedures were similar to each other, but that AET showed a higher spatial variability if obtained with downscaled LST. We concluded that LST had a large effect on producing AET maps from Remote Sensing (RS) images, and that downscaling cokriging was helpful to provide daily AET maps at medium spatial resolution. Numéro de notice : A2017-113 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.004 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84508
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 56 – 67[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration / Yinghai Ke in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Spatiotemporal downscaling approaches for monitoring 8-day 30 m actual evapotranspiration Type de document : Article/Communication Auteurs : Yinghai Ke, Auteur ; Jungho Im, Auteur ; Seonyoung Park, Auteur ; Huili Gong, Auteur Année de publication : 2017 Article en page(s) : pp 79 – 93 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] évapotranspiration
[Termes IGN] image à haute résolution
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] réflectance de surface
[Termes IGN] ressources en eau
[Termes IGN] température au solRésumé : (auteur) Continuous monitoring of actual evapotranspiration (ET) is critical for water resources management at both regional and local scales. Although the MODIS ET product (MOD16A2) provides viable sources for ET monitoring at 8-day intervals, the spatial resolution (1 km) is too coarse for local scale applications. In this study, we propose a machine learning and spatial temporal fusion (STF)-integrated approach in order to generate 8-day 30 m ET based on both MOD16A2 and Landsat 8 data with three schemes. Random forest machine learning was used to downscale MODIS 1 km ET to 30 m resolution based on nine Landsat-derived indicators including vegetation indices (VIs) and land surface temperature (LST). STF-based models including Spatial and Temporal Adaptive Reflectance Fusion Model and Spatio-Temporal Image Fusion Model were used to derive synthetic Landsat surface reflectance (scheme 1)/VIs (scheme 2)/ET (scheme 3) on Landsat-unavailable dates. The approach was tested over two study sites in the United States. The results showed that fusion of Landsat VIs produced the best accuracy of predicted ET (R2 = 0.52–0.97, RMSE = 0.47–3.0 mm/8 days and rRMSE = 6.4–37%). High density of cloud-clear Landsat image acquisitions and low spatial heterogeneity of Landsat VIs benefit the ET prediction. The downscaled 30 m ET had good agreement with MODIS ET (RMSE = 0.42–3.4 mm/8 days, rRMSE = 3.2–26%). Comparison with the in situ ET measurements showed that the downscaled ET had higher accuracy than MODIS ET. Numéro de notice : A2017-114 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.006 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84509
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 79 – 93[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Transferability of multi- and hyperspectral optical biocrust indices / Emilio Rodríguez-Caballero in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Transferability of multi- and hyperspectral optical biocrust indices Type de document : Article/Communication Auteurs : Emilio Rodríguez-Caballero, Auteur ; P. Escribano, Auteur ; C. Olehowski, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 94 – 107 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse
[Termes IGN] classification dirigée
[Termes IGN] état de surface du sol
[Termes IGN] image hyperspectrale
[Termes IGN] indice de détection
[Termes IGN] surface du solRésumé : (auteur) Biological soil crusts (biocrusts) are communities of cyanobacteria, algae, microfungi, lichens and bryophytes in varying proportions, which live within or immediately on top of the uppermost millimeters of the soil in arid and semiarid regions. As biocrusts are highly relevant for ecosystem processes like carbon, nitrogen, and water cycling, a correct characterization of their spatial distribution is required. Following this objective, considerable efforts have been devoted to the identification and mapping of biocrusts using remote sensing data, and several mapping indices have been developed. However, their transferability to different regions has only rarely been tested. In this study we investigated the transferability of two multispectral indices, i.e. the Crust Index (CI) and the Biological Soil Crust Index (BSCI), and two hyperspectral indices, i.e. the Continuum Removal Crust Identification Algorithm (CRCIA) and the Crust Development Index (CDI), in three sites dominated by biocrusts, but with differences in soil and vegetation composition. Whereas multispectral indices have been important and valuable tools for first approaches to map and classify biological soil crusts, hyperspectral data and indices developed for these allowed to classify biocrusts at much higher accuracy. While multispectral indices showed Kappa (κ) values below 0.6, hyperspectral indices obtained good classification accuracy (κ ∼ 0.8) in both the study area where they had been developed and in the newly tested region. These results highlight the capability of hyperspectral sensors to identify specific absorption features related to photosynthetic pigments as chlorophyll and carotenoids, but also the limitation of multispectral information to discriminate between areas dominated by biocrusts, vegetation or bare soil. Based on these results we conclude that remote sensing offers an important and valid tool to map biocrusts. However, the spectral similarity between the main surface components of drylands and biocrusts demand for mapping indices based on hyperspectral information to correctly map areas dominated by biocrusts at ecosystem scale. Numéro de notice : A2017-115 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84510
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 94 – 107[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery / Clément Dechesne in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery Type de document : Article/Communication Auteurs : Clément Dechesne , Auteur ; Clément Mallet , Auteur ; Arnaud Le Bris , Auteur ; Valérie Gouet-Brunet , Auteur Année de publication : 2017 Projets : HYEP / Weber, Christiane Article en page(s) : pp 129 – 145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification automatique
[Termes IGN] classification dirigée
[Termes IGN] délimitation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction d'arbres
[Termes IGN] fusion d'images
[Termes IGN] image aérienne
[Termes IGN] image multibande
[Termes IGN] peuplement forestier
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (auteur) Forest stands are the basic units for forest inventory and mapping. Stands are defined as large forested areas (e.g., ⩾⩾2 ha) of homogeneous tree species composition and age. Their accurate delineation is usually performed by human operators through visual analysis of very high resolution (VHR) infra-red images. This task is tedious, highly time consuming, and should be automated for scalability and efficient updating purposes. In this paper, a method based on the fusion of airborne lidar data and VHR multispectral images is proposed for the automatic delineation of forest stands containing one dominant species (purity superior to 75%). This is the key preliminary task for forest land-cover database update. The multispectral images give information about the tree species whereas 3D lidar point clouds provide geometric information on the trees and allow their individual extraction. Multi-modal features are computed, both at pixel and object levels: the objects are individual trees extracted from lidar data. A supervised classification is then performed at the object level in order to coarsely discriminate the existing tree species in each area of interest. The classification results are further processed to obtain homogeneous areas with smooth borders by employing an energy minimum framework, where additional constraints are joined to form the energy function. The experimental results show that the proposed method provides very satisfactory results both in terms of stand labeling and delineation (overall accuracy ranges between 84% and 99%). Numéro de notice : A2017-116 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.011 Date de publication en ligne : 27/02/2017 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84511
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 129 – 145[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data / André Dittrich in ISPRS Journal of photogrammetry and remote sensing, vol 126 (April 2017)
[article]
Titre : Analytical and numerical investigations on the accuracy and robustness of geometric features extracted from 3D point cloud data Type de document : Article/Communication Auteurs : André Dittrich, Auteur ; Martin Weinmann, Auteur ; Stefan Hinz, Auteur Année de publication : 2017 Article en page(s) : pp 195 – 208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bruit (théorie du signal)
[Termes IGN] calcul tensoriel
[Termes IGN] discrétisation
[Termes IGN] données localisées 3D
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] lasergrammétrie
[Termes IGN] méthode robuste
[Termes IGN] restitution lasergrammétrique
[Termes IGN] semis de points
[Termes IGN] valeur propreRésumé : (auteur) In photogrammetry, remote sensing, computer vision and robotics, a topic of major interest is represented by the automatic analysis of 3D point cloud data. This task often relies on the use of geometric features amongst which particularly the ones derived from the eigenvalues of the 3D structure tensor (e.g. the three dimensionality features of linearity, planarity and sphericity) have proven to be descriptive and are therefore commonly involved for classification tasks. Although these geometric features are meanwhile considered as standard, very little attention has been paid to their accuracy and robustness. In this paper, we hence focus on the influence of discretization and noise on the most commonly used geometric features. More specifically, we investigate the accuracy and robustness of the eigenvalues of the 3D structure tensor and also of the features derived from these eigenvalues. Thereby, we provide both analytical and numerical considerations which clearly reveal that certain features are more susceptible to discretization and noise whereas others are more robust. Numéro de notice : A2017-117 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.02.012 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2017.02.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84512
in ISPRS Journal of photogrammetry and remote sensing > vol 126 (April 2017) . - pp 195 – 208[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017043 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2017042 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt