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Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring / Gopal Krishna in Geocarto international, vol 36 n° 5 ([15/03/2021])
[article]
Titre : Application of thermal imaging and hyperspectral remote sensing for crop water deficit stress monitoring Type de document : Article/Communication Auteurs : Gopal Krishna, Auteur ; Rabi N. Sahoo, Auteur ; Prafull Singh, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 481 - 498 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] image hyperspectrale
[Termes IGN] image thermique
[Termes IGN] indice de stress
[Termes IGN] Oryza (genre)
[Termes IGN] réflectance spectrale
[Termes IGN] régression des moindres carrés partiels
[Termes IGN] rizière
[Termes IGN] sécheresse
[Termes IGN] stress hydrique
[Termes IGN] teneur en eau de la végétationRésumé : (auteur) Water deficit in crops induces a stress that may ultimately result in low production. Identification of response of genotypes towards water deficit stress is very crucial for plant phenotyping. The study was carried out with the objective to identify the response of different rice genotypes to water deficit stress. Ten rice genotypes were grown each under water deficit stress and well watered or nonstress conditions. Thermal images coupled with visible images were recorded to quantify the stress and response of genotypes towards stress, and relative water content (RWC) synchronized with image acquisition was also measured in the lab for rice leaves. Synced with thermal imaging, Canopy reflectance spectra from same genotype fields were also recorded. For quantification of water deficit stress, Crop Water Stress Index (CWSI) was computed and its mode values were extracted from processed thermal imageries. It was ascertained from observations that APO and Pusa Sugandha-5 genotypes exhibited the highest resistance to the water deficit stress or drought whereas CR-143, MTU-1010, and Pusa Basmati-1 genotypes ascertained the highest sensitiveness to the drought. The study reveals that there is an effectual relationship (R2 = 0.63) between RWC and CWSI. The relationship between canopy reflectance spectra and CWSI was also established through partial least square regression technique. A very efficient relationship (calibration R2 = 0.94 and cross-validation R2 = 0.71) was ascertained and 10 most optimal wavebands related to water deficit stress were evoked from hyperspectral data resampled at 5 nm wavelength gap. The identified ten most optimum wavebands can contribute in the quick detection of water deficit stress in crops. This study positively contributes towards the identification of drought tolerant and drought resistant genotypes of rice and may provide valuable input for the development of drought-tolerant rice genotypes in future. Numéro de notice : A2021-250 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1618922 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1618922 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97272
in Geocarto international > vol 36 n° 5 [15/03/2021] . - pp 481 - 498[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2021051 RAB Revue Centre de documentation En réserve L003 Disponible Terrestrial laser scanning intensity captures diurnal variation in leaf water potential / S. Junttila in Remote sensing of environment, Vol 255 (March 2021)
[article]
Titre : Terrestrial laser scanning intensity captures diurnal variation in leaf water potential Type de document : Article/Communication Auteurs : S. Junttila, Auteur ; T. Hölttä, Auteur ; Eetu Puttonen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112274 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Betula (genre)
[Termes IGN] diagnostic foliaire
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] dynamique de la végétation
[Termes IGN] Pinus sylvestris
[Termes IGN] sécheresse
[Termes IGN] semis de points
[Termes IGN] stress hydrique
[Termes IGN] teneur en eau de la végétation
[Termes IGN] variation diurneRésumé : (auteur) During the past decades, extreme events have become more prevalent and last longer, and as a result drought-induced plant mortality has increased globally. Timely information on plant water dynamics is essential for understanding and anticipating drought-induced plant mortality. Leaf water potential (ΨL), which is usually measured destructively, is the most common metric that has been used for decades for measuring water stress. Remote sensing methods have been developed to obtain information on water dynamics from trees and forested landscapes. However, the spatial and temporal resolutions of the existing methods have limited our understanding of the water dynamics and diurnal variation of ΨL within single trees. Thus, we investigated the capability of terrestrial laser scanning (TLS) intensity in observing diurnal variation in ΨL during a 50-h monitoring period. We aimed to improve the understanding on how large a part of the diurnal variation in ΨL can be captured using TLS intensity observations. We found that TLS intensity at the 905 nm wavelength measured from a static position was able to explain 77% of the variation in ΨL for three trees of two tree species with a root mean square error of 0.141 MPa. Based on our experiment with three trees, a time series of TLS intensity measurements can be used in detecting changes in ΨL, and thus it is worthwhile to expand the investigations to cover a wider range of tree species and forests and further increase our understanding of plant water dynamics at wider spatial and temporal scales. Numéro de notice : A2021-192 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2020.112274 Date de publication en ligne : 14/01/2021 En ligne : https://doi.org/10.1016/j.rse.2020.112274 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97113
in Remote sensing of environment > Vol 255 (March 2021) . - n° 112274[article]How to accelerate the germination of Scots pine and Norway spruce seeds? / Kateřina Houšková in Journal of forest science, vol 67 n° 3 (March 2021)
[article]
Titre : How to accelerate the germination of Scots pine and Norway spruce seeds? Type de document : Article/Communication Auteurs : Kateřina Houšková, Auteur ; Jan Klepárník, Auteur ; Oldřich Mauer, Auteur Année de publication : 2021 Article en page(s) : pp 134 - 142 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] croissance des arbres
[Termes IGN] germination
[Termes IGN] phytobiologie
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] semis (sylviculture)
[Termes IGN] teneur en eau de la végétation
[Vedettes matières IGN] BotaniqueRésumé : (auteur) The aim of the study was to confirm and compare efficiency of methods enhancing the vitality of Scots pine and Norway spruce seeds: soaking in water, cold stratification, additional moistening and incubation according to IDS method. The examined parameters included water content in the seeds, germination energy, mean germination time and germination capacity before the seed treatment, after its treatment by the tested methods and after drying. Results show that all the tested methods accelerate germination of seeds; cold stratification is the most efficient and recommended method for Scots pine and soaking of seeds in water is the most efficient and recommended for Norway spruce. The best results in spruce were also obtained with cold stratification (comparable with soaking in water) but the method is complicated, longer-lasting and more costly than soaking in water. Numéro de notice : A2021-273 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.17221/133/2020-JFS Date de publication en ligne : 17/12/2020 En ligne : https://doi.org/10.17221/133/2020-JFS Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97354
in Journal of forest science > vol 67 n° 3 (March 2021) . - pp 134 - 142[article]Coastal 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)
[article]
Titre : Coastal water remote sensing from sentinel-2 satellite data using physical, statistical, and neural network retrieval approach Type de document : Article/Communication Auteurs : Frank S. Marzano, Auteur ; Michele Iacobelli, Auteur ; Massimo Orlandi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 915 - 928 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Adriatique, mer
[Termes IGN] bathymétrie
[Termes IGN] chlorophylle
[Termes IGN] correction atmosphérique
[Termes IGN] couleur de l'océan
[Termes IGN] eaux côtières
[Termes IGN] image Sentinel-MSI
[Termes IGN] incertitude spectrale
[Termes IGN] matière organique
[Termes IGN] Méditerranée, mer
[Termes IGN] réseau neuronal artificielRésumé : (auteur) Recent optical remote sensing satellite missions, such as Sentinel-2 with the MultiSpectral Imager (MSI) onboard, allow the estimation of coastal water key parameters with very high spatial resolutions (down to 10 m). In this article, multiple approaches are proposed for retrieving chlorophyll-a (Chl-a) and total suspended matter (TSM) along the Adriatic and Tyrrhenian coasts in Italy, using both empirical and model-based frameworks to design regressive and neural network (NN) estimation methods. The latter proves to be more accurate on a regional scale, where standard ocean color physical models exhibit high uncertainty in their local parameterization due to the complex spectral characteristics of the observed scene. Retrieval results are encouraging for Chl-a with a coefficient of determination R2 up to 0.72 with a root-mean-square error (RMSE) of 0.33 mg m−3 , using an empirical NN. The TSM algorithms exhibit higher uncertainty, mainly due to scarcity of in situ measurements and model parameterizations, with R2=0.52 and RMSE = 1.95 g/m 3 using NNs. The bio-optical model, used for the development of model-based algorithms, shows some inadequacies in representing the inherent and apparent optical properties for the case study areas, especially considering the different spectral features between the oligotrophic Tyrrhenian Sea and the eutrophic Adriatic Sea. This study confirms the potential of Sentinel-2 MSI products for coastal water monitoring, but it also highlights key issues to be further tackled such as the atmospheric correction impact, the need of reliable in situ measurements, and possible bathymetry effects near the shores. Numéro de notice : A2021-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2980941 Date de publication en ligne : 09/12/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2980941 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96912
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 2 (February 2021) . - pp 915 - 928[article]Assessment 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)
[article]
Titre : Assessment of chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data Type de document : Article/Communication Auteurs : Ioannis Moutzouris-Sidiris, Auteur ; Konstantinos Topouzelis, Auteur Année de publication : 2021 Article en page(s) : pp 85 - 97 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] chlorophylle
[Termes IGN] classification par réseau neuronal
[Termes IGN] couleur de l'océan
[Termes IGN] image Envisat-MERIS
[Termes IGN] image Sentinel-3
[Termes IGN] image Sentinel-OLCI
[Termes IGN] Méditerranée, merRésumé : (auteur) The objective of this study is to evaluate the efficiency of two well-known algorithms (Ocean Colour 4 for MERIS [OC4Me] and neural net [NN]) used in the calculation of chlorophyll-a (Chl-a) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) compared to in situ measurements covering the Mediterranean Sea. In situ data set, obtained from the Copernicus Marine Environmental Monitoring Service (CMEMS) and more specifically from the data set with the title INSITU_MED_NRT_OBSERVATIONS_013_035, and Chl-a values at different depths were extracted. The concentration of Chl-a at a penetration depth was calculated. Then, water was classified into two categories, Case-1 and Case-2. For Case-2 waters, the OC4Me presents a moderate correlation with the in situ data for a time window of 0–2 h. In contrast with the NN algorithm, where very weak correlations were calculated, lower values of the statistical index of Bias for Case-1 waters were calculated for the OC4Me algorithm. Higher values of Pearson correlation were calculated (r > 0.5) for OC4Me algorithm than NN. OC4Me performed better than NN. Numéro de notice : A2021-487 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/geo-2020-0204 Date de publication en ligne : 29/01/2021 En ligne : https://doi.org/10.1515/geo-2020-0204 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97776
in Open geosciences > vol 13 n° 1 (January 2021) . - pp 85 - 97[article]Norway 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)PermalinkMonitoring of wheat crops using the backscattering coefficient and the interferometric coherence derived from Sentinel-1 in semi-arid areas / Nadia Ouaadi in Remote sensing of environment, Vol 251 (15 December 2020)PermalinkBistatic specular scattering measurements for the estimation of rice crop growth variables using fuzzy inference system at X-, C-, and L-bands / Ajeet Kumar Vishwakarma in Geocarto international, vol 35 n° 13 ([01/10/2020])PermalinkBoreal peatland forests: ditch network maintenance effort and water protection in a forest rotation framework / Jenny Miettinen in Canadian Journal of Forest Research, vol 50 n° 10 (October 2020)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)PermalinkUsing spectral indices to estimate water content and GPP in sphagnum moss and other peatland vegetation / Kirsten J. Lees in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkImproved SMAP dual-channel algorithm for the retrieval of soil moisture / Mario Julian Chaubell in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)Permalink