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A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band / Xinjie Liu in Remote sensing of environment, vol 284 (January 2023)
[article]
Titre : A simple approach to enhance the TROPOMI solar-induced chlorophyll fluorescence product by combining with canopy reflected radiation at near-infrared band Type de document : Article/Communication Auteurs : Xinjie Liu, Auteur ; Liangyun Liu, Auteur ; Cédric Bacour, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113341 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] canopée
[Termes IGN] chlorophylle
[Termes IGN] fluorescence
[Termes IGN] image Sentinel-5P-TROPOMI
[Termes IGN] image Terra-MODIS
[Termes IGN] production primaire brute
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] réflectance de surface
[Termes IGN] réflectance végétaleRésumé : (auteur) Satellite-based data of solar-induced chlorophyll fluorescence (SIF) and the near-infrared radiation reflected by vegetation (NIRvP) are being increasingly used for the estimation of vegetation gross primary product (GPP) at the global scale. Although SIF contains more physiological information than NIRvP, NIRvP can have higher data quality and spatio-temporal resolution. Therefore, the two variables can be considered complementary for GPP monitoring. Here, we propose a simple framework to combine SIF and NIRvP data from different data sources to generate an enhanced SIF product (eSIF). The original SIF data comes from the TROPOMI instrument onboard the Sentinel-5P mission, whereas NIRvP data are derived from MODIS spectral reflectance and ERA5 reanalysis data. The resulting eSIF product has a spatial resolution of 0.05° and a temporal resolution of 8 days, as well as a higher signal-to-noise ratio and a lower angular dependency than the original TROPOMI SIF data. Our results demonstrate that eSIF has similar spatial patterns to the original SIF but is more spatially continuous and less noisy. Comparisons with the FLUXCOM global GPP product show that eSIF has a more universal relationship with GPP than NIRvP for different grass/crop plant functional types (the coefficients of variation are 18.9% for slopes of GPP to eSIF and 27.3% for slopes of GPP to NIRvP), but NIRvP outperforms eSIF for tracking GPP for forest PFTs exclude BoENF. Moreover, eSIF is able to better track the seasonal variations in GPP related to environmental stresses. This study highlights that our methodology based on the combination of SIF and NIRvP is a promising approach for better monitoring of GPP. Numéro de notice : A2023-017 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113341 Date de publication en ligne : 07/11/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113341 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102151
in Remote sensing of environment > vol 284 (January 2023) . - n° 113341[article]Alternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation / Toshihiro Sakamoto in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)
[article]
Titre : Alternative procedure to improve the positioning accuracy of orthomosaic images acquired with Agisoft Metashape and DJI P4 multispectral for crop growth observation Type de document : Article/Communication Auteurs : Toshihiro Sakamoto, Auteur ; Daisuke Ogawa, Auteur ; Satoko Hiura, Auteur ; Nobusuke Iwasaki, Auteur Année de publication : 2022 Article en page(s) : pp 323 - 332 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] bande spectrale
[Termes IGN] blé (céréale)
[Termes IGN] chlorophylle
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] indice de végétation
[Termes IGN] orthophotoplan numérique
[Termes IGN] point d'appui
[Termes IGN] précision du positionnement
[Termes IGN] rizière
[Termes IGN] structure-from-motionRésumé : (Auteur) Vegetation indices (VIs), such as the green chlorophyll index and normalized difference vegetation index, are calculated from visible and near-infrared band images for plant diagnosis in crop breeding and field management. The DJI P4 Multispectral drone combined with the Agisoft Metashape Structure from Motion/Multi View Stereo software is some of the most cost-effective equipment for creating high-resolution orthomosaic VI images. However, the manufacturer's procedure results in remarkable location estimation inaccuracy (average error: 3.27–3.45 cm) and alignment errors between spectral bands (average error: 2.80–2.84 cm). We developed alternative processing procedures to overcome these issues, and we achieved a higher positioning accuracy (average error: 1.32–1.38 cm) and better alignment accuracy between spectral bands (average error: 0.26–0.32 cm). The proposed procedure enables precise VI analysis, especially when using the green chlorophyll index for corn, and may help accelerate the application of remote sensing techniques to agriculture. Numéro de notice : A2022-528 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00064R2 Date de publication en ligne : 01/05/2022 En ligne : https://doi.org/10.14358/PERS.21-00064R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101379
in Photogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 5 (May 2022) . - pp 323 - 332[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 105-2022052 SL Revue Centre de documentation Revues en salle Disponible 105-2022051 SL Revue Centre de documentation Revues en salle Disponible A convolution neural network for forest leaf chlorophyll and carotenoid estimation using hyperspectral reflectance / Shuo Shi in International journal of applied Earth observation and geoinformation, vol 108 (April 2022)
[article]
Titre : A convolution neural network for forest leaf chlorophyll and carotenoid estimation using hyperspectral reflectance Type de document : Article/Communication Auteurs : Shuo Shi, Auteur ; Lu Xu, Auteur ; Wei Gong, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102719 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] chlorophylle
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] écosystème forestier
[Termes IGN] feuille (végétation)
[Termes IGN] modèle de transfert radiatif
[Termes IGN] processus gaussien
[Termes IGN] réflectance spectrale
[Termes IGN] régressionRésumé : (auteur) Forest leaf chlorophyll (Cab) and carotenoid (Cxc) are key functional indicators for the state of the forest ecosystem. Current machine learning models based on hyperspectral reflectance are widely applied to estimate leaf Cab and Cxc contents at leaf scale. However, these models have certain accuracy for non-independent datasets but have poor generalization for independent datasets when they are used to estimate leaf Cab and Cxc contents. This fact limits that hyperspectral remote sensing completely replaces destructive measurements for leaf Cab and Cxc contents. Thus, the development of an estimation model with high accuracy and satisfactory generalization is necessary. Convolutional neural networks (CNNs) have certain accuracy and generalization in many domains, and have the potential to solve above-mentioned problem. Therefore, this study developed a CNN using one-dimensional hyperspectral reflectance, which aimed to improve the model's accuracy and generalization in leaf Cab and Cxc content estimation at leaf scale. The proposed CNN was developed by three steps. First, in consideration of the correlation between leaf Cab and Cxc contents in natural leaves, 2500 physical data with leaf reflectance and corresponding Cab and Cxc contents were generated by leaf radiative transfer model and multivariable gaussian distribution function. Then, the proposed CNN was built by five strategies based on the architecture of the AlexNet. Finally, five-fold cross validation was performed with 70% of the physical data to determine the best strategy to develop the proposed CNN. These were executed to ensure the proposed CNN with the maximum accuracy and generalization. In addition, the accuracy and generalization of the proposed CNN were tested using a non-independent dataset and an independent dataset, respectively. The proposed CNN was also compared with back propagation neural network (BPNN), support vector regression (SVR) and gaussian process regression (GPR). Results showed that the best CNN could be developed with one input, five convolutional, three max-pooling and three fully-connected layers. Comprehensively considering the model's accuracy and generalization, the proposed CNN was the best model for leaf Cab and Cxc content estimation compared with BPNN, SVR and GPR. This study provides a development strategy of CNN estimation model using one-dimensional hyperspectral reflectance at leaf scale. The proposed CNN could further promote the practical application of hyperspectral remote sensing in leaf Cab and Cxc content estimation. Numéro de notice : A2022-231 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102719 Date de publication en ligne : 16/02/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102719 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100119
in International journal of applied Earth observation and geoinformation > vol 108 (April 2022) . - n° 102719[article]Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 / Nima Pahlevan in Remote sensing of environment, vol 270 (March 2022)
[article]
Titre : Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 Type de document : Article/Communication Auteurs : Nima Pahlevan, Auteur ; Brandon Smith, Auteur ; Krista Alikas, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] appariement d'images
[Termes IGN] apprentissage automatique
[Termes IGN] chlorophylle
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] correction atmosphérique
[Termes IGN] données multisources
[Termes IGN] eaux côtières
[Termes IGN] image Landsat-OLI
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-OLCI
[Termes IGN] matière organique
[Termes IGN] Oregon (Etats-Unis)
[Termes IGN] qualité des eauxRésumé : (auteur) Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (acdom(440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and acdom(440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and acdom(440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and acdom(440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model. Numéro de notice : A2022-126 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112860 Date de publication en ligne : 04/01/2022 En ligne : https://doi.org/10.1016/j.rse.2021.112860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99705
in Remote sensing of environment > vol 270 (March 2022) . - n° 112860[article]Detection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)
[article]
Titre : Detection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements Type de document : Article/Communication Auteurs : Xue Li, Auteur ; Shaoling Shang, Auteur ; Zhongping Lee, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4200513 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algue
[Termes IGN] biomasse
[Termes IGN] cartographie thématique
[Termes IGN] Chine
[Termes IGN] chlorophylle
[Termes IGN] couleur de l'océan
[Termes IGN] espèce exotique envahissante
[Termes IGN] image captée par drone
[Termes IGN] image hyperspectrale
[Termes IGN] plancton
[Termes IGN] réflectanceRésumé : (auteur) Phaeocystis globosa (P. globosa) is a unique causative species of harmful algal blooms, which can form gelatinous colonies. We, for the first time, used unmanned aerial vehicle (UAV) measurements to identify P. globosa blooms and to quantify the biomass. Based on in situ measured remote sensing reflectance ( Rrs ), it is found that, for P. globosa blooms, the maximum of the second-derivative ( dλ2Rrs ) of Rrs(λ) in the 460–480-nm domain is beyond 466 nm. An analysis of the absorption properties from algal cultures suggested that this feature comes from the absorption of chlorophyll c3 (Chl −/c3 ) around 466 nm, a prominent feature of P. globosa. This position of dλ2Rrs maximum was, thus, selected as the criterion for P. globosa identification. The spatial extent of P. globosa blooms in two bays off southern China was then mapped by applying the criterion to UAV-measured Rrs . Twelve out of 16 UAV and in situ match-up stations were consistently identified as dominated by P. globosa, indicating the accuracy of 75%. Furthermore, using localized empirical models, chlorophyll a (Chl −/a ) concentration and colony numbers of P. globosa were estimated from UAV-derived Rrs , where P. globosa colonies were found in a range of ~3–37 gel matrix/L, indicating the occurrence of weak to moderate P. globosa blooms during the surveys. The promising results suggest a high potential for detection and quantification of P. globosa blooms in near-shore bays or harbors using UAV-based hyperspectral remote sensing, where conventional ocean color satellite remote sensing runs into difficulties. Numéro de notice : A2022-025 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2021.3051466 Date de publication en ligne : 26/01/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3051466 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99254
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 1 (January 2022) . - n° 4200513[article]A deep learning model using satellite ocean color and hydrodynamic model to estimate chlorophyll-a concentration / Daeyong Jin in Remote sensing, vol 13 n°10 (May-2 2021)PermalinkInversion of solar-induced chlorophyll fluorescence using polarization measurements of vegetation / Haiyan Yao in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 5 (May 2021)PermalinkAtmospheric correction of Sentinel-3/OLCI data for mapping of suspended particulate matter and chlorophyll-a concentration in Belgian turbid coastal waters / Quinten Vanhellemont in Remote sensing of environment, Vol 256 (April 2020)PermalinkCoastal water remote sensing from sentinel-2 satellite data using physical, statistical, and neural network retrieval approach / Frank S. Marzano in IEEE Transactions on geoscience and remote sensing, vol 59 n° 2 (February 2021)PermalinkAssessment of chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data / Ioannis Moutzouris-Sidiris in Open geosciences, vol 13 n° 1 (January 2021)PermalinkNorway spruce seedlings from an Eastern Baltic provenance show tolerance to simulated drought / Roberts Matisons in Forests, vol 12 n° 1 (January 2021)PermalinkUsing remote sensing and modeling to monitor and understand harmful algal blooms. Application to Karaoun Reservoir (Lebanon) / Najwa Sharaf (2021)PermalinkAnalysis of chlorophyll concentration in potato crop by coupling continuous wavelet transform and spectral variable optimization / Ning Liu in Remote sensing, vol 12 n° 17 (September-1 2020)PermalinkA novel algorithm to estimate phytoplankton carbon concentration in inland lakes using Sentinel-3 OLCI images / Heng Lyu in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)PermalinkTowards a semi-automated mapping of Australia native invasive alien Acacia trees using Sentinel-2 and radiative transfer models in South Africa / Cecilia Masemola in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)PermalinkFootprint determination of a spectroradiometer mounted on an unmanned aircraft system / Deepak Gautam in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)PermalinkDetection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkPermalinkPermalinkTélédétection multispectrale et hyperspectrale des eaux littorales turbides / Morgane Larnicol (2018)PermalinkImproved atmospheric correction and chlorophyll-a remote sensing models for turbid waters in a dusty environment / Maryam R. Al Shehhi in ISPRS Journal of photogrammetry and remote sensing, vol 133 (November 2017)PermalinkEvaluation de variables limnologiques grâce à des images Landsat / Danielle Teixeira Alves Da Silva in Géomatique expert, n° 118 (septembre - octobre 2017)PermalinkUtilisation des données des capteurs MODIS et SPOT-VGT pour l'analyse de la dynamique des feux dans deux territoires (réserve protégée et unités pastorales) au Ferlo (Sénégal) / Mamadou Adama Sarr in Photo interprétation, European journal of applied remote sensing, vol 51 n° 2 (juin 2015)PermalinkDeriving Predictive relationships of carotenoid content at the canopy level in a conifer forest using hyperspectral imagery and model simulation / Rocío Hernández-Clemente in IEEE Transactions on geoscience and remote sensing, vol 52 n° 8 Tome 2 (August 2014)PermalinkLaboratory measurements of plant drying: Implications to estimate moisture content from radiative transfer models in two temperate species / Sara Jurdao in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 5 (May 2014)PermalinkEstimation of higher chlorophylla concentrations using field spectral measurement and HJ-1A hyperspectral satellite data in Dianshan Lake, China / Liguo Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)PermalinkGaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval / Jochem Verrlest in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)PermalinkActive learning methods for biophysical parameter estimation / Edoardo Pasolli in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 2 (October 2012)PermalinkLandscape controls over major nutrients and primary productivity of Arctic lakes / P. Pathak in Cartography and Geographic Information Science, vol 39 n° 4 (October 2012)PermalinkIn situ estimation of water quality parameters in freshwater aquaculture ponds using hyperspectral imaging system / Amr Abd-Elrahman in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 4 (July - August 2011)Permalinkvol 31 n° 17 - 18 - September 2010 - Pan ocean remote sensing : oceanic manifestation of global changes (Bulletin de International Journal of Remote Sensing IJRS) / G. LevyPermalinkFrost damage in Pinus sylvestris L. stems assessed by chlorophyll fluorescence in cortical bark chlorenchyma / José Javier Peguero-Pina in Annals of Forest Science, Vol 65 n° 8 (December 2008)PermalinkWavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation / G. Blackburn in International Journal of Remote Sensing IJRS, vol 28 n°11-12 (June 2007)PermalinkExtending the MODIS 1 km ocean colour atmospheric correction to the MODIS 500 m bands and 500 m chlorophyll-a estimation towards coastal and estuarine monitoring / J.D. Shutler in Remote sensing of environment, vol 107 n° 4 (30/04/2007)PermalinkA new algorithm for estimating chlorophyll-a concentration from multi-spectral satellite data in case 2 waters: a simulation based on a controlled laboratory experiment / Y. Oyoma in International Journal of Remote Sensing IJRS, vol 28 n°7-8 (April 2007)PermalinkRegional products for the Baltic Sea using MERIS data / H. Krawczyk in International Journal of Remote Sensing IJRS, vol 28 n°3-4 (February 2007)PermalinkNeural network estimation of LAI, fAPAR, fCover and LAI*Cab, from top of canopy MERIS reflectance data: principles and validation / Cédric Bacour in Remote sensing of environment, vol 105 n° 4 (30/12/2006)PermalinkRelationship between herbicide concentration during the 1960s and 1970s and the contemporary MERIS terrestrial chlorophyll index (MTCI) for southern Vietnam / J. Dash in International journal of geographical information science IJGIS, vol 20 n° 8 (september 2006)PermalinkDynamique urbaine et télédétection : le choix de l'indicateur végétal, les cas de Montréal, Paris et Pékin / I. Biraud-Burot in Photo interprétation, vol 41 n° 4 (Novembre 2005)PermalinkMarine GIS: identification of mesoscale oceanic thermal fronts / V.D. Valavanis in International journal of geographical information science IJGIS, vol 19 n° 10 (november 2005)PermalinkAssessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands / G. Dall'olmo in Remote sensing of environment, vol 96 n° 2 (30/05/2005)PermalinkAnalysis of simultaneous chlorophyll measurements by lidar fluorosensor, MODIS and SeaWiFS / R. Bardini in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)PermalinkSeaWIFS validation in European coastal waters using optical and bio-geochemical measurements / S.J. Lavender in International Journal of Remote Sensing IJRS, vol 25 n° 7 (April 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)PermalinkToward universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements / G. Le Maire in Remote sensing of environment, vol 89 n° 1 (15/01/2004)PermalinkAutomated subpixel photobathymetry and water quality mapping / R.L. Huguenin in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 1 (January 2004)PermalinkRemote sensing techniques to assess water quality / J.C. Ritchie in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 6 (June 2003)PermalinkSchätzung von Vegetationsparametern aus multispektralen Fernerkundungsdaten / F. Kurz (2003)PermalinkUtilisation des images et données multisources pour caractériser l'état de palmeraies industrielles au Gabon / Marcellin Nziengui (2000)PermalinkOcean colour analysis in coastal waters by airborne sensors / G. Zibordi in International Journal of Remote Sensing IJRS, vol 11 n° 5 (May 1990)PermalinkChlorophyll-a estimation in New-Jersey's coastal waters using Thematic Mapper data / S. Bagheri in International Journal of Remote Sensing IJRS, vol 11 n° 2 (February 1990)PermalinkMapping of phytoplankton by solar-simulated fluorescence using an imaging spectrometer / J.F.R. Gower in International Journal of Remote Sensing IJRS, vol 11 n° 2 (February 1990)PermalinkA multi-temporal study of chlorophyll-a concentration in the Albufera lagoon of Valencia, Spain, using Thematic Mapper data / M.J. Lopez Garcia in International Journal of Remote Sensing IJRS, vol 11 n° 2 (February 1990)PermalinkPassive and active optical remote sensing of the inland water phytoplankton / K.Y. Kondratyev in ISPRS Journal of photogrammetry and remote sensing, vol 44 n° 5 (February 1990)PermalinkRelative photosynthetic activity of agricultural lands from airborne carbon dioxide and satellite data / A.R. Mack in International Journal of Remote Sensing IJRS, vol 11 n° 2 (February 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)PermalinkAirborne discrimination between ice and water : application to the laser measurement of chlorophyll-in-water in a marginal ice zone / F.E. Hoge in Remote sensing of environment, vol 30 n° 1 (01/10/1989)PermalinkA three-component model of ocean colour and its application to remote sensing of phytoplankton pigments in coastal waters / S. Sathyendranath in International Journal of Remote Sensing IJRS, vol 10 n° 8 (August 1989)PermalinkThe plume of the Yukon river in relation to the oceanography of the Bering sea / K.G. Dean in Remote sensing of environment, vol 28 n° 1 (April - June 1989)PermalinkSatellite detection of bloom and pigment distributions in estuaries / R.P. Stumpf in Remote sensing of environment, vol 24 n° 3 (01/04/1988)PermalinkThe effect of dissolved 'yellow substance' on the quantitative retrieval of chlorophyll and total suspended sediment concentrations from remote measurements of water colour / S. Tassan in International Journal of Remote Sensing IJRS, vol 9 n° 4 (April 1988)PermalinkRelative sensitivity of Normalized Difference Vegetation Index (NDVI) and Microwave Polarization Difference Index (MPDI) for vegetation and desertification monitoring / François Becker in Remote sensing of environment, vol 24 n° 2 (March 1988)PermalinkComparison of 'in-situ' and airborne spectral measurements of the blue shift associated with forest decline / B.N. Rock in Remote sensing of environment, vol 24 n° 1 (February 1988)PermalinkMonitoring water stress in buffelgrass using hand-held radiometers / A.J. Richardson in International Journal of Remote Sensing IJRS, vol 8 n° 12 (December 1987)PermalinkEvaluation of the potential of the Thematic Mapper for marine application / S. Tassan in International Journal of Remote Sensing IJRS, vol 8 n° 10 (October 1987)PermalinkOblique view reflectance for assessing nitrogen status of incomplete canopies / T.H. Demetriades-Shah in International Journal of Remote Sensing IJRS, vol 8 n° 7 (July 1987)PermalinkRemotely-sensed tracers for hydrodynamic surface flow estimation / D.A. Stow in International Journal of Remote Sensing IJRS, vol 8 n° 3 (March 1987)PermalinkA two-look technique for studying atmospheric effects in optical scanner data for the ocean / G. Khosraviani in International Journal of Remote Sensing IJRS, vol 8 n° 3 (March 1987)PermalinkMapping of water quality in coastal waters using airborne Thematic Mapper data / J.C. Rimmer in International Journal of Remote Sensing IJRS, vol 8 n° 1 (January 1987)PermalinkVisualisation par analyse des fronts chlorophylliens à partir du radiomètre Nimbus 7 CZCS / R.W. Austin in Photo interprétation, vol 1982 n° 6 (Novembre 1982)Permalink