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[article]
Titre : Geoglam, l'agriculture par satellite Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2021 Article en page(s) : pp 17 - 17 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] blé (céréale)
[Termes IGN] carte d'occupation du sol
[Termes IGN] Glycine max
[Termes IGN] image à haute résolution
[Termes IGN] Leaf Area Index
[Termes IGN] maïs (céréale)
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] observation de la Terre
[Termes IGN] Oryza (genre)
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (Auteur) Des satellites pour la sécurité alimentaire et la transparence du marché agricole Numéro de notice : A2021-579 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 13/09/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98400
in Géomètre > n° 2194 (septembre 2021) . - pp 17 - 17[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 063-2021081 RAB Revue Centre de documentation En réserve L003 Disponible Extracting leaf area index using viewing geometry effects : A new perspective on high-resolution unmanned aerial system photography / Lukas Roth in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)
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[article]
Titre : Extracting leaf area index using viewing geometry effects : A new perspective on high-resolution unmanned aerial system photography Type de document : Article/Communication Auteurs : Lukas Roth, Auteur ; Helge Aasen, Auteur ; Achim Walter, Auteur ; Frank Liebisch, Auteur Année de publication : 2018 Article en page(s) : pp 161 - 175 Note générale : Bibliography Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] cultures
[Termes IGN] drone
[Termes IGN] Glycine max
[Termes IGN] image aérienne
[Termes IGN] image RVB
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] modélisation géométrique de prise de vue
[Termes IGN] orthoimage géoréférencée
[Termes IGN] segmentation d'image
[Termes IGN] simulation 3D
[Termes IGN] SuisseRésumé : (Editeur) Extraction of leaf area index (LAI) is an important prerequisite in numerous studies related to plant ecology, physiology and breeding. LAI is indicative for the performance of a plant canopy and of its potential for growth and yield. In this study, a novel method to estimate LAI based on RGB images taken by an unmanned aerial system (UAS) is introduced. Soybean was taken as the model crop of investigation. The method integrates viewing geometry information in an approach related to gap fraction theory. A 3-D simulation of virtual canopies helped developing and verifying the underlying model. In addition, the method includes techniques to extract plot based data from individual oblique images using image projection, as well as image segmentation applying an active learning approach. Data from a soybean field experiment were used to validate the method. The thereby measured LAI prediction accuracy was comparable with the one of a gap fraction-based handheld device ( of , RMSE of m 2m−2) and correlated well with destructive LAI measurements ( of , RMSE of m2 m−2). These results indicate that, if respecting the range (LAI ) the method was tested for, extracting LAI from UAS derived RGB images using viewing geometry information represents a valid alternative to destructive and optical handheld device LAI measurements in soybean. Thereby, we open the door for automated, high-throughput assessment of LAI in plant and crop science. Numéro de notice : A2018-287 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.012 Date de publication en ligne : 07/05/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90402
in ISPRS Journal of photogrammetry and remote sensing > vol 141 (July 2018) . - pp 161 - 175[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018071 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018073 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018072 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications / Amanda Veloso in Remote sensing of environment, vol 199 (15 September 2017)
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[article]
Titre : Understanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications Type de document : Article/Communication Auteurs : Amanda Veloso, Auteur ; Stéphane Mermoz, Auteur ; Alexandre Bouvet, Auteur ; Thuy Le Toan, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 415 - 426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] blé (céréale)
[Termes IGN] cultures
[Termes IGN] Glycine max
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] maïs (céréale)
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance agricole
[Termes IGN] tournesol
[Termes IGN] variation saisonnière
[Termes IGN] variation temporelleRésumé : (auteur) Crop monitoring information is essential for food security and to improve our understanding of the role of agriculture on climate change, among others. Remotely sensing optical and radar data can help to map crop types and to estimate biophysical parameters, especially with the availability of an unprecedented amount of free Sentinel data within the Copernicus programme. These datasets, whose continuity is guaranteed up to decades, offer a unique opportunity to monitor crops systematically every 5 to 10 days. Before developing operational monitoring methods, it is important to understand the temporal variations of the remote sensing signal of different crop types in a given region. In this study, we analyse the temporal trajectory of remote sensing data for a variety of winter and summer crops that are widely cultivated in the world (wheat, rapeseed, maize, soybean and sunflower). The test region is in southwest France, where Sentinel-1 data have been acquired since 2014. Because Sentinel-2 data were not available for this study, optical satellites similar to Sentinel-2 are used, mainly to derive NDVI, for a comparison between the temporal behaviors with radar data. The SAR backscatter and NDVI temporal profiles of fields with varied management practices and environmental conditions are interpreted physically. Key findings from this analysis, leading to possible applications of Sentinel-1 data, with or without the conjunction of Sentinel-2, are then described. This study points out the interest of SAR data and particularly the VH/VV ratio, which is poorly documented in previous studies. Numéro de notice : A2017-418 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.07.015 En ligne : https://doi.org/10.1016/j.rse.2017.07.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86311
in Remote sensing of environment > vol 199 (15 September 2017) . - pp 415 - 426[article]Soil moisture mapping and AMSR-E validation using the PSR in SMEX02 / R. Bindlish in Remote sensing of environment, vol 103 n° 2 (30/07/2006)
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[article]
Titre : Soil moisture mapping and AMSR-E validation using the PSR in SMEX02 Type de document : Article/Communication Auteurs : R. Bindlish, Auteur ; Thomas J. Jackson, Auteur ; A.J. Gasiewski, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 127 - 139 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] bande C
[Termes IGN] bande X
[Termes IGN] biomasse
[Termes IGN] carte thématique
[Termes IGN] Glycine max
[Termes IGN] humidité du sol
[Termes IGN] image Aqua-AMSR
[Termes IGN] Iowa (Etats-Unis)
[Termes IGN] maïs (céréale)
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] température de luminanceRésumé : (Auteur) Field experiments (SMEX02) were conducted to evaluate the effects of dense agricultural crop conditions on soil moisture retrieval using passive microwave remote sensing. Aircraft observations were collected using a new version of the Polarimetric Scanning Radiometer (PSR) that provided four C band and four X band frequencies. Observations were also available from the Aqua satellite Advanced Microwave Scanning Radiometer (AMSR-E) at these same frequencies. SMEX02 was conducted over a three-week period during the summer near Ames, Iowa. Corn and soybeans dominate the region. During the study period the corn was approaching its peak water content state and the soybeans were at the mid point of the growth cycle. Aircraft observations are compared to ground observations. Subsequently models are developed to describe the effects of corn and soybeans on soil moisture retrieval. Multiple altitude aircraft brightness temperatures were compared to AMSR-E observations to understand brightness temperature scaling and provide validation. The X-band observations from the two sensors were in reasonable agreement. The AMSR-E C-band observations were contaminated with anthropogenic RFI, which made comparison to the PSR invalid. Aircraft data along with ancillary data were used in a retrieval algorithm to map soil moisture. The PSR estimated soil moisture retrievals on a field-by-field comparison had a standard error of estimate (SEE) of 5.5%. The error reduced when high altitude soil moisture estimates were aggregated to 25 km resolution (same as AMSR-E EASE grid product resolution) (SEE not, vert, similar 2.85%). These soil moisture products provide a validation of the AMSR retrievals. PSR/CX soil moisture images show spatial and temporal patterns consistent with meteorological and soil conditions. The dynamic range of the PSR/CX observations indicates that reasonable soil moisture estimates can be obtained from AMSR, even in areas of high vegetation biomass content (not, vert, similar 4–8 kg/m2). Copyright Elsevier Numéro de notice : A2006-319 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.02.003 En ligne : https://doi.org/10.1016/j.rse.2005.02.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28043
in Remote sensing of environment > vol 103 n° 2 (30/07/2006) . - pp 127 - 139[article]Land cover-based optimal deconvolution of PALS L-band microwave brightness temperatures / A.S. Limaye in Remote sensing of environment, vol 92 n° 4 (30 September 2004)
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[article]
Titre : Land cover-based optimal deconvolution of PALS L-band microwave brightness temperatures Type de document : Article/Communication Auteurs : A.S. Limaye, Auteur ; William L. Crosson, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 497 - 506 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] biomasse
[Termes IGN] capteur actif
[Termes IGN] capteur passif
[Termes IGN] déconvolution
[Termes IGN] Glycine max
[Termes IGN] Iowa (Etats-Unis)
[Termes IGN] luminance lumineuse
[Termes IGN] maïs (céréale)
[Termes IGN] Passive and Active L and S band Sensor
[Termes IGN] Soil Moisture Experiment
[Termes IGN] température de luminanceRésumé : (Auteur) An optimal deconvolution (ODC) technique has been developed to estimate microwave brightness temperatures of agricultural fields using microwave radiometer observations. The technique is applied to airborne measurements taken by the Passive and Active L and S band (PALS) sensor in Iowa during Soil Moisture Experiments in 2002 (SMEX02). Agricultural fields in the study area were predominantly soybeans and corn. The brightness temperatures of corn and soybeans were observed to be significantly different because of large differences in vegetation biomass. PALS observations have significant over-sampling; observations were made about 100 m apart and the sensor footprint extends to about 400 m. Conventionally, observations of this type are averaged to produce smooth spatial data fields of brightness temperatures. However, the conventional approach is in contrast to reality in which the brightness temperatures are in fact strongly dependent on land cover, which is characterized by sharp boundaries. In this study, we mathematically deconvolve the observations into brightness temperature at the field scale (500-800 m) using the sensor antenna response function. The result is more accurate spatial representation of field-scale brightness temperatures, which may in turn lead to more accurate soil moisture retrieval. Numéro de notice : A2004-415 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.02.019 En ligne : https://doi.org/10.1016/j.rse.2004.02.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26942
in Remote sensing of environment > vol 92 n° 4 (30 September 2004) . - pp 497 - 506[article]Retrieval of soil moisture from passive and active L/S band sensor (PALS) observations during the soil moisture experiment in 2002 (SMEX) / U. Narayan in Remote sensing of environment, vol 92 n° 4 (30 September 2004)
PermalinkHyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modelling and validation in the context of precision agriculture / D. Haboudane in Remote sensing of environment, vol 90 n° 3 (15/04/2004)
PermalinkPermalinkPermalinkA multiconstituent and multilayer microwave backscatter model for a vegetative medium / H.T. Chuah in Remote sensing of environment, vol 31 n° 2 (01/02/1990)
PermalinkArsenic-and-selenium-induced changes in spectral reflectance and morphology of soybean plants / N.M. Milton in Remote sensing of environment, vol 30 n° 3 (01/12/1989)
PermalinkThe use of a spectroradiometer to study aerial photographs of ozone-treated soybeans / G.J. Edwards in International Journal of Remote Sensing IJRS, vol 10 n° 12 (December 1989)
PermalinkCorrelations between canopy reflectance and leaf temperature in irrigated and droughted soybeans / W.W. Cure in Remote sensing of environment, vol 29 n° 3 (01/09/1989)
PermalinkLeaf bidirectional reflectance and transmittance in corn and soybean / E.A.W. Shea in Remote sensing of environment, vol 29 n° 2 (01/08/1989)
PermalinkEffect of metal stress on the thermal infrared emission of soybeans : a green-house experiment, possible utility in remote sensing. / R. Suresh in International Journal of Remote Sensing IJRS, vol 10 n° 3 (March 1989)
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