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Thermal infrared reveals vegetation stress / Thomas A. Groen in GIM international [en ligne], vol 30 n° 6 (June 2016)

Public [article]  inGIM international [en ligne] > vol 30 n° 6 (June 2016) . - pp 29 - 31 Titre : Thermal infrared reveals vegetation stress Type de document : Article/Communication Auteurs : Thomas A. Groen, Auteur ; Christoph A. Hecker, Auteur ; Maria Buitrago, Auteur Année de publication : 2016 Article en page(s) : pp 29 - 31 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes descripteurs IGN] image infrarouge [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] indice de stress [Termes descripteurs IGN] photo-interprétation Résumé : (éditeur) Climate change or other environmental changes may affect the health of plants. Conventional methods for determining how vegetation responds to changes in temperature and humidity measure the reflectance of the visible and near-infrared part of the electromagnetic (EM) spectrum on the leaves. By using a non-destructive thermal infrared spectrometer, the authors demonstrate that persistent stress also affects the thermal infrared emissivity of plants. This finding paves the way for using thermal spectroscopy to monitor responses of vegetation to climate change. Numéro de notice : A2016-315 Thématique : FORET/IMAGERIE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80933 [article]

Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM / Nitika Dangwal in Geocarto international, vol 31 n° 5 - 6 (May - June 2016)  

Public [article]  inGeocarto international > vol 31 n° 5 - 6 (May - June 2016) . - pp 682 - 693 Titre : Monitoring of water stress in wheat using multispectral indices derived from Landsat-TM Type de document : Article/Communication Auteurs : Nitika Dangwal, Auteur ; N.R. Patel, Auteur ; Mamta Kumari, Auteur ; S.K. Saha, Auteur Année de publication : 2016 Article en page(s) : pp 682 - 693 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] indice d'humidité [Termes descripteurs IGN] indice de stress [Termes descripteurs IGN] irrigation [Termes descripteurs IGN] surveillance agricole [Termes descripteurs IGN] teneur en eau de la végétation Résumé : (Auteur) Detection of crop water stress is crucial for efficient irrigation water management. Potential of Satellite data to provide spatial and temporal dynamics of crop growth conditions makes it possible to monitor crop water stress at regional level. This study was conducted in parts of western Uttar Pradesh and Haryana. Multi-temporal Landsat data were used for detecting wheat crop water stress using vegetation indices (VIs), viz. vegetation water stress index (VWSI) and land surface wetness index water stress factor (Ws_LSWI). The estimated water stress from satellite data-based VIs was validated by water stress factor (Ws) derived from flux-tower data. The study observed Ws_LSWI to be better index for water stress detection. The results indicated that Ws_LSWI was superior over other index showing RMSE = 0.12, R2 = 0.65, whereas VWSI showed overestimated values with mean RD 4%. Numéro de notice : A2016-174 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1073369 date de publication en ligne : 01/09/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1073369 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80518 [article]

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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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 85 - 95 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 descripteurs IGN] acer saccharum [Termes descripteurs IGN] aiguille [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] indice de stress [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] picea mariana [Termes descripteurs IGN] Pinus banksiana [Termes descripteurs IGN] populus tremuloides [Termes descripteurs IGN] réflectance végétale [Termes descripteurs IGN] surveillance forestière [Termes descripteurs IGN] teneur en chlorophylle des feuilles Résumé : (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 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://www.sciencedirect.com/science/article/pii/S0924271615000258 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78326 [article]

MODIS-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 [en ligne], vol 72 n° 1 (January 2015)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 72 n° 1 (January 2015) . - pp 109 - 125 Titre : MODIS-based vegetation index has sufficient sensitivity to indicate stand-level intra-seasonal climatic stress in oak and beech forests Type de document : Article/Communication Auteurs : Tomáš Hlásny, Auteur ; Ivan Barka, Auteur ; Zuzana Sitková, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 109 - 125 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] chaleur [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] Fagus (genre) [Termes descripteurs IGN] forêt tempérée [Termes descripteurs IGN] image Aqua-MODIS [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] indice de stress [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] prévision météorologique [Termes descripteurs IGN] quercus (genre) [Termes descripteurs IGN] sécheresse Résumé : (auteur) Context : Variation in photosynthetic activity of trees induced by climatic stress can be effectively evaluated using remote sensing data. Although adverse effects of climate on temperate forests have been subjected to increased scrutiny, the suitability of remote sensing imagery for identification of drought stress in such forests has not been explored fully. Aim : The study seeks to evaluate the sensitivity of MODIS-based vegetation index to heat and drought stress in temperate forests, and to explore the differences in stress response of oaks and beech. Methods : We identified 8 oak and 13 beech pure and mature stands, each covering between 4 and 13 MODIS pixels. For each pixel, we extracted a time series of MODIS NDVI from 2000 to 2010. We identified all sequences of continuous unseasonal NDVI decline to be used as the response variable indicative of environmental stress. Neural network-based regression modelling was then applied to identify the climatic variables that best explain observed NDVI declines. Results : Tested variables explained 84–97 % of the variation in NDVI, whilst air temperature-related climate extremes were found to be the most influential. Beech showed a linear response to the most influential climatic predictors, while oak responded in a unimodal pattern suggesting a better coping mechanism. Conclusions : MODIS NDVI has proved sufficiently sensitive as a stand-level indicator of climatic stress acting upon temperate broadleaf forests, leading to its potential use in predicting drought stress from meteorological observations and improving parameterisation of forest stress indices. Numéro de notice : A2015-382 Thématique : FORET/IMAGERIE Nature : Article En ligne : http://link.springer.com/article/10.1007/s13595-014-0404-2/fulltext.html Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76874 [article]