Descripteur
Termes IGN > télédétection > télédétection électromagnétique
télédétection électromagnétique |
Documents disponibles dans cette catégorie (898)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
L'approche détection des changements pour estimer l'humidité du sol en milieu semi-aride à partir d'images ASAR, cas des hautes plaines de l'Est de l'Algérie / Mokhtar Guerfi in Revue Française de Photogrammétrie et de Télédétection, n° 210 (Avril 2015)
![]()
[article]
Titre : L'approche détection des changements pour estimer l'humidité du sol en milieu semi-aride à partir d'images ASAR, cas des hautes plaines de l'Est de l'Algérie Type de document : Article/Communication Auteurs : Mokhtar Guerfi, Auteur ; Atef Alaadine Amriche, Auteur Année de publication : 2015 Article en page(s) : pp 39 - 49 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Algérie
[Termes IGN] carte thématique
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] détection de changement
[Termes IGN] humidité du sol
[Termes IGN] image Envisat-ASAR
[Termes IGN] plaine
[Termes IGN] régression linéaire
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] zone semi-arideRésumé : (Auteur) C’est avec la télédétection radar que les résultats les plus prometteurs pour estimer et cartographier l’humidité du sol ont été obtenus. Les travaux de ces dernières années ont donné lieu à de nombreuses approches et algorithmes. Dans ce papier, nous évaluons l’approche détection des changements, qui offre le potentiel d’une utilisation opérationnelle, qui est moins complexe, minimise le rôle de la rugosité de surface et de la végétation. Quatre images du capteur ASAR/ENVISAT avec la même configuration ont été acquises, sur un secteur des hautes plaines semi-arides de l’Est de l’Algérie ; 67 échantillons sont prélevés à chaque passage du satellite sur cinq parcelles test et l’humidité mesurée. L’étude des régressions linéaires associée à l’approche détection du changement a permis l’expression du coefficient de rétrodiffusion comme fonction de l’humidité volumique du sol (σ0 = a*θ + b). Les coefficients “a” et “b” de l’équation diffèrent d’un site à l’autre et d’une saison à l’autre. Cette différence est due aux variations saisonnières de la rugosité et du couvert végétal. La comparaison entre l’humidité de surface mesurée et celle estimée montre la pertinence des modèles d’inversion utilisés, avec une erreur moyenne de plus ou moins 4%. Finalement, une carte de la distribution de l’humidité de surface de la région a été obtenue à partir des images acquises. Numéro de notice : A2015-432 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.52638/rfpt.2015.271 En ligne : https://doi.org/10.52638/rfpt.2015.271 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77024
in Revue Française de Photogrammétrie et de Télédétection > n° 210 (Avril 2015) . - pp 39 - 49[article]Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework / H. Croft in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
![]()
[article]
Titre : Evaluating leaf chlorophyll content prediction from multispectral remote sensing data within a physically-based modelling framework Type de document : Article/Communication Auteurs : H. Croft, Auteur ; Jing M. Chen, Auteur ; Y. Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 85 - 95 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Acer saccharum
[Termes IGN] aiguille
[Termes IGN] image Landsat-TM
[Termes IGN] indice de stress
[Termes IGN] Leaf Area Index
[Termes IGN] modèle de transfert radiatif
[Termes IGN] Picea mariana
[Termes IGN] Pinus banksiana
[Termes IGN] Populus tremuloides
[Termes IGN] réflectance végétale
[Termes IGN] surveillance forestière
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (auteur) Accurate modelling of leaf chlorophyll content over a range of spatial and temporal scales is central to monitoring vegetation stress and physiological condition, and vegetation response to different ecological, climatic and anthropogenic drivers. A process-based modelling approach can account for variation in other factors affecting canopy reflectance, providing a more accurate estimate of chlorophyll content across different vegetation species, time-frames, and broader spatial extents. However, physically-based modelling studies usually use hyperspectral data, neglecting a wealth of data from broadband and multispectral sources. In this study, we assessed the potential for using canopy (4-Scale) and leaf radiative transfer (PROSPECT4/5) models to estimate leaf chlorophyll content using canopy Landsat satellite data and simulated Landsat bands from leaf level hyperspectral reflectance data. Over 600 leaf samples were used to test the performance of PROSPECT for different vegetation species, including black spruce (Picea mariana), sugar maple (Acer saccharum), trembling aspen (Populus tremuloides) and jack pine (Pinus banksiana). At the leaf level, hyperspectral and simulated Landsat bands showed very similar results to laboratory measured chlorophyll (R2 = 0.77 and R2 = 0.75, respectively). Comparisons between PROSPECT4 modelled chlorophyll from simulated Landsat and hyperspectral spectra showed a very close correspondence (R2 = 0.97, root mean square error (RMSE) = 3.01 μg/cm2), as did simulated reflectance bands from other broadband and narrowband sensors (MODIS: R2 = 0.99, RMSE = 1.80 μg/cm2; MERIS: R2 = 0.97, RMSE = 2.50 μg/cm2 and SPOT5 HRG: R2 = 0.96, RMSE = 5.38 μg/cm2). Modelled leaf chlorophyll content from Landsat 5 TM canopy reflectance data, acquired from over 40 ground validation sites, demonstrated a strong relationship with measured leaf chlorophyll content (R2 = 0.78, RMSE = 8.73 μg/cm2, p Numéro de notice : A2015-691 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78326
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 85 - 95[article]Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series / Xiaolin Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
![]()
[article]
Titre : Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series Type de document : Article/Communication Auteurs : Xiaolin Zhu, Auteur ; Desheng Liu, Auteur Année de publication : 2015 Article en page(s) : pp 222 - 231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] biomasse forestière
[Termes IGN] image Landsat
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] puits de carbone
[Termes IGN] série temporelle
[Termes IGN] variation saisonnièreRésumé : (auteur) Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting. Landsat data have been widely used to provide efficient and timely estimates of forest AGB because of their long archive and relatively high spatial resolution. Previous studies have explored different empirical modeling approaches to estimate AGB, but most of them only used a single Landsat image in the peak season, which may cause a saturation problem and low accuracy. To improve the accuracy of AGB estimation using Landsat images, this study explored the use of NDVI seasonal time-series derived from Landsat images across different seasons to estimate AGB in southeast Ohio by six empirical modeling approaches. Results clearly show that NDVI in the fall season has a stronger correlation to AGB than in the peak season, and using seasonal NDVI time-series can result in a more accurate AGB estimation and less saturation than using a single NDVI. In comparing these different empirical approaches, it is difficult to decide which one is superior to the other because they have different strengths and their accuracy is generally similar, indicating that modeling methods may not be the key issue for improving the accuracy of AGB estimation from Landsat data. This study suggests that future research should pay more attention to seasonal time-series data, and especially the data from the fall season. Numéro de notice : A2015-695 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78329
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 222 - 231[article]Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass / Le Li in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
![]()
[article]
Titre : Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass Type de document : Article/Communication Auteurs : Le Li, Auteur ; Qinghua Guo, Auteur ; Shengli Tao, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 198 - 208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse forestière
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] régression linéaireRésumé : (auteur) Forests play a key role in the global carbon cycle, and forest above ground biomass (AGB) is an important indictor to the carbon storage capacity and the potential carbon pool size of a forest ecosystem. Accurate estimation of forest AGB has become increasingly important for a wide range of end-users. Although satellite remote sensing provides abundant observations to monitor forest coverage, validation of coarse-resolution AGB derived from satellite observations is difficult because of the scale mismatch between the footprints of satellite observations and field measurements. In this study, we use airborne Lidar to bridge the scale gaps between satellite-based and field-based studies, and evaluate satellite-derived indices to estimate regional forest AGB. We found that: (1) Lidar data can be used to accurately estimate forest AGB using tree height and tree quadratic height, (2) linear regression, among four tested models, achieve the best performance (R2 = 0.74; RMSE = 183.57 Mg/ha); (3) for MODIS-derived vegetation indices at varied spatial resolution (250–1000 m), accumulated NDVI, accumulated LAI, and accumulated FPAR could explain 53–74% variances of forest AGB, whereas accumulated NDVI derived from 1 km MODIS products gives higher R2 (74%) and lower RMSE (13.4 Mg/ha) than others. We conclude that Lidar data can be used to bridge the scale gap between satellite and field studies. Our results indicate that combining MODIS and Lidar data has the potential to estimate regional forest AGB. Numéro de notice : A2015-694 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.02.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78328
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 198 - 208[article]Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs) / Gonzalo Pajares in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 4 (April 2015)
![]()
[article]
Titre : Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs) Type de document : Article/Communication Auteurs : Gonzalo Pajares, Auteur Année de publication : 2015 Article en page(s) : pp 281- 330 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] acquisition d'images
[Termes IGN] capteur aérien
[Termes IGN] drone
[Termes IGN] instrument aéroporté
[Termes IGN] télédétection aérienneRésumé : (auteur) Remotely Piloted Aircraft (RPA) is presently in continuous development at a rapid pace. Unmanned Aerial Vehicles (UAVs) or more extensively Unmanned Aerial Systems (UAS) are platforms considered under the RPAs paradigm. Simultaneously, the development of sensors and instruments to be installed onboard such platforms is growing exponentially. These two factors together have led to the increasing use of these platforms and sensors for remote sensing applications with new potential. Thus, the overall goal of this paper is to provide a panoramic overview about the current status of remote sensing applications based on unmanned aerial platforms equipped with a set of specific sensors and instruments. First, some examples of typical platforms used in remote sensing are provided. Second, a description of sensors and technologies is explored which are onboard instruments specifically intended to capture data for remote sensing applications. Third, multi-UAVs in collaboration, coordination, and cooperation in remote sensing are considered. Finally, a collection of applications in several areas are proposed, where the combination of unmanned platforms and sensors, together with methods, algorithms, and procedures provide the overview in very different remote sensing applications. This paper presents an overview of different areas, each independent from the others, so that the reader does not need to read the full paper when a specific application is of interest. Numéro de notice : A2015-964 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.4.281 En ligne : https://doi.org/10.14358/PERS.81.4.281 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80022
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 4 (April 2015) . - pp 281- 330[article]Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
PermalinkNon-invasive forest litter characterization using full-wave inversion of microwave radar data / Frédéric André in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)
PermalinkStable mean-shift algorithm and its application to the segmentation of arbitrarily large remote sensing images / Julien Michel in IEEE Transactions on geoscience and remote sensing, vol 53 n° 2 (February 2015)
PermalinkMODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests / Tomáš Hlásny in Annals of Forest Science, vol 72 n° 1 (January 2015)
Permalinkn° 209 - Janvier 2015 - Pléiades days 2014 (2ème partie) (Bulletin de Revue Française de Photogrammétrie et de Télédétection)
PermalinkPôle thématique surfaces continentales THEIA : infrastructure de données pour les scientifiques et les acteurs publics / Nicolas Baghdadi (2015)
PermalinkPermalinkRetrieving surface variables by integrating ground measurements and earth observation data in forest canopies : a case study in Speuldersbos forest / Kitsiri Weligepolage (2015)
![]()
PermalinkSatellite data as indicators of tree biomass growth and forest dieback in a Mediterranean holm oak forest / Romà Ogaya in Annals of Forest Science, vol 72 n° 1 (January 2015)
PermalinkSemisupervised manifold alignment of multimodal remote sensing images / Devis Tuia in IEEE Transactions on geoscience and remote sensing, vol 52 n° 12 (December 2014)
Permalink