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Termes IGN > sciences naturelles > sciences de la Terre et de l'univers > géosciences > géographie physique > météorologie > température de surface > température au sol
température au solSynonyme(s)température de surface du sol température à la surface des terres |
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Attribution of the Australian bushfire risk to anthropogenic climate change / Geert Jan Van Oldenborgh in Natural Hazards and Earth System Sciences, vol 21 n° 3 (March 2021)
[article]
Titre : Attribution of the Australian bushfire risk to anthropogenic climate change Type de document : Article/Communication Auteurs : Geert Jan Van Oldenborgh, Auteur ; Folmer Krikken, Auteur ; Sophie Lewis, Auteur Année de publication : 2021 Article en page(s) : pp 941 - 960 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des risques
[Termes IGN] brousse
[Termes IGN] changement climatique
[Termes IGN] incendie
[Termes IGN] modèle météorologique
[Termes IGN] planification
[Termes IGN] prévention des risques
[Termes IGN] série temporelle
[Termes IGN] température au sol
[Termes IGN] utilisation du solRésumé : (auteur) Disastrous bushfires during the last months of 2019 and January 2020 affected Australia, raising the question to what extent the risk of these fires was exacerbated by anthropogenic climate change. To answer the question for southeastern Australia, where fires were particularly severe, affecting people and ecosystems, we use a physically based index of fire weather, the Fire Weather Index; long-term observations of heat and drought; and 11 large ensembles of state-of-the-art climate models. We find large trends in the Fire Weather Index in the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5) since 1979 and a smaller but significant increase by at least 30 % in the models. Therefore, we find that climate change has induced a higher weather-induced risk of such an extreme fire season. This trend is mainly driven by the increase of temperature extremes. In agreement with previous analyses we find that heat extremes have become more likely by at least a factor of 2 due to the long-term warming trend. However, current climate models overestimate variability and tend to underestimate the long-term trend in these extremes, so the true change in the likelihood of extreme heat could be larger, suggesting that the attribution of the increased fire weather risk is a conservative estimate. We do not find an attributable trend in either extreme annual drought or the driest month of the fire season, September–February. The observations, however, show a weak drying trend in the annual mean. For the 2019/20 season more than half of the July–December drought was driven by record excursions of the Indian Ocean Dipole and Southern Annular Mode, factors which are included in the analysis here. The study reveals the complexity of the 2019/20 bushfire event, with some but not all drivers showing an imprint of anthropogenic climate change. Finally, the study concludes with a qualitative review of various vulnerability and exposure factors that each play a role, along with the hazard in increasing or decreasing the overall impact of the bushfires. Numéro de notice : A2021-395 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-21-941-2021 Date de publication en ligne : 11/03/2021 En ligne : https://doi.org/10.5194/nhess-21-941-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97684
in Natural Hazards and Earth System Sciences > vol 21 n° 3 (March 2021) . - pp 941 - 960[article]Impact of atmospheric correction on spatial heterogeneity relations between land surface temperature and biophysical compositions / Xin-Ming Zhu in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)
[article]
Titre : Impact of atmospheric correction on spatial heterogeneity relations between land surface temperature and biophysical compositions Type de document : Article/Communication Auteurs : Xin-Ming Zhu, Auteur ; Xiao-Ning Song, Auteur ; Pei Leng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2680 - 2697 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Chine
[Termes IGN] correction atmosphérique
[Termes IGN] hétérogénéité spatiale
[Termes IGN] image Landsat-8
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression
[Termes IGN] température au sol
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) Investigating the relations between land surface temperature (LST) and biophysical compositions can help the understanding of the surface biophysical process. However, there are still uncertainties in determining the impacts of biophysical compositions on LST due to the atmospheric effects. In this article, four atmospheric correction algorithms were used to correct 12 Landsat 8 images in Xi’an, Beijing, Wuhan, and Guangzhou, China, including the Atmospheric Correction for Flat Terrain (ATCOR2), Quick Atmospheric Correction (QUAC), Fast Line-of-sight Atmospheric Analysis of Spectral Hypercube (FLAASH), and Second Simulation of Satellite Signal in the Solar Spectrum (6S). Then, geodetector was used to investigate the atmospheric correction differences in the spatial heterogeneity relationships between LST and normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), and bare soil index (BSI). Results indicate that the selected composition factors were greatly improved after atmospheric correction, and the relations between LST and three factors were characterized by obvious atmospheric correction differences in four study areas. On the whole, the 6S algorithm performed the best in improving the factor values and impacting the spatial heterogeneity relations between LST and biophysical compositions, followed by FLAASH, QUAC, and ATCOR2 algorithms. Except for Wuhan, 6S, FLAASH, and QUAC algorithms significantly enhanced the correlation between LST and NDVI. However, all algorithms weakened the correlations between LST, NDVI, and BSI, except Guangzhou. These findings have been verified using the regression analysis. In addition, with geodetector, combinations of any two composition factors all had strongly enhanced impacts on LST, and a combination between NDVI and NDBI performed the strongest in most cases. Numéro de notice : A2021-219 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3002821 Date de publication en ligne : 26/06/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3002821 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97211
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 2680 - 2697[article]
Titre : Remote Sensing Type de document : Monographie Auteurs : Andrew Hammond, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2021 Importance : 140 p. ISBN/ISSN/EAN : 978-1-83880-978-2 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes IGN] Amérique du sud
[Termes IGN] analyse d'image orientée objet
[Termes IGN] biomasse
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données spatiotemporelles
[Termes IGN] Enhanced vegetation index
[Termes IGN] géostatistique
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie de forêt
[Termes IGN] Inde
[Termes IGN] mésosphère
[Termes IGN] précision stéréoscopique
[Termes IGN] sciences naturelles
[Termes IGN] segmentation d'image
[Termes IGN] série temporelle
[Termes IGN] stratosphère
[Termes IGN] système d'information géographique
[Termes IGN] température au sol
[Termes IGN] troposphèreIndex. décimale : 35.00 Télédétection - généralités Résumé : (Editeur) This Edited Volume is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Remote Sensing. The book comprises single chapters authored by various researchers and edited by an expert active in this research area. All chapters are complete in themselves but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on this field of study, and open new possible research paths for further novel developments. Note de contenu : 1. Lidar Observations in South America. Part I - Mesosphere and Stratosphere
2. Lidar Observations in South America. Part II - Troposphere
3. Application of Remote Sensing in Natural Sciences
4. Assessment of Ecological Disturbance Caused by Flood and Fire in Assam Forests, India, Using MODIS Time Series Data of 2001-2011
5. Delineation of Open-Pit Mining Boundaries on Multispectral Imagery
6. Stereoscopic Precision of the Large Format Digital Cameras
7. Remote Sensing Applications in Disease MappingNuméro de notice : 26799 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87829 Date de publication en ligne : 08/12/2021 En ligne : https://doi.org/10.5772/intechopen.87829 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100066 Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale / Chen Yang in Geo-spatial Information Science, vol 23 n° 4 (December 2020)
[article]
Titre : Characterizing the spatial and temporal variation of the land surface temperature hotspots in Wuhan from a local scale Type de document : Article/Communication Auteurs : Chen Yang, Auteur ; Qingming Zhan, Auteur ; Sihang Gao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 327 - 340 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] climat urbain
[Termes IGN] géomorphologie locale
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-OLI
[Termes IGN] image Terra-MODIS
[Termes IGN] image thermique
[Termes IGN] morphologie urbaine
[Termes IGN] processus gaussien
[Termes IGN] regroupement de données
[Termes IGN] série temporelle
[Termes IGN] température au sol
[Termes IGN] Wuhan (Chine)
[Termes IGN] zonage (urbanisme)Résumé : (auteur) Land Surface Temperature (LST) derived from space-borne Thermal-infrared (TIR) sensors is a key parameter of urban climate studies. Current studies are inefficient to capture the spatial and temporal variations of LST for only one snapshot adopted at one time. Focusing on the characterization of the spatial and temporal of LST variations at local scales, the latent patterns, and morphological characteristics are extracted in this study. Technically, sixteen MODerate-resolution Imaging Spectroradiometer (MODIS) eight-day synthesized LST products (MYD11A2) in 2002, 2007, 2012, and 2017 are employed. First, the non-parametric Multi-Task Gaussian Process Model (MTGP) is used to extract the smooth and continuous Latent LST (LLST) patterns using one LST subset and its temporally adjacent images. Second, the Multi-Scale Shape Index (MSSI) is then applied to quantify the morphological characteristics at the optimal scale. Then, the LLST patterns and MSSI maps are clustered into multiple spatial categories. The specific clusters with the highest LLST and MSSI values are considered as local LLST hotspots. The Hotspots Weighted Mean Center (HSWMC) and standard deviation ellipse are adopted to further investigate the spatiotemporal change of hotspots orientation, direction, and trajectories. Results revealed that Impervious Surfaces (IS) composition is the most significant external forcing of local LST anomalies. The configuration factors (e.g., shape index, aggregation index) also have a noticeable local warming effect. This study represents a latent pattern and morphology-based framework for LST hotspots spatial and temporal variations characterization, catering to the zoning and grading strategies in urban planning. Numéro de notice : A2020-788 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2020.1834882 Date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.1080/10095020.2020.1834882 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96550
in Geo-spatial Information Science > vol 23 n° 4 (December 2020) . - pp 327 - 340[article]A deep learning approach to improve the retrieval of temperature and humidity profiles from a ground-based microwave radiometer / Xing Yan in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)
[article]
Titre : A deep learning approach to improve the retrieval of temperature and humidity profiles from a ground-based microwave radiometer Type de document : Article/Communication Auteurs : Xing Yan, Auteur ; Chen Liang, Auteur ; Yize Jiang, Auteur Année de publication : 2020 Article en page(s) : pp 8427 - 8437 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] apprentissage profond
[Termes IGN] changement climatique
[Termes IGN] classification par réseau neuronal
[Termes IGN] humidité du sol
[Termes IGN] modèle atmosphérique
[Termes IGN] radiomètre à hyperfréquence
[Termes IGN] température au solRésumé : (auteur) The ground-based microwave radiometer (MWR) retrieves atmospheric profiles with a high temporal resolution for temperature and humidity up to a height of 10 km. Such profiles are critical for understanding the evolution of climate systems. To improve the accuracy of profile retrieval in MWR, we developed a deep learning approach called batch normalization and robust neural network (BRNN). In contrast to the traditional backpropagation neural network (BPNN), which has previously been applied for MWR profile retrieval, BRNN reduces overfitting and has a greater capacity to describe nonlinear relationships between MWR measurements and atmospheric structure information. Validation of BRNN with the radiosonde demonstrates a good retrieval capability, showing a root-mean-square error of 1.70 K for temperature, 11.72% for relative humidity (RH), and 0.256 g/m 3 for water vapor density. A detailed comparison with various inversion methods (BPNN, extreme gradient boosting, support vector machine, ridge regression, and random forest) has also been conducted in this research, using the same training and test data sets. From the comparison, we demonstrated that BRNN significantly improves retrieval accuracy, particularly for the retrieval of temperature and RH near the surface. Numéro de notice : A2020-741 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2987896 Date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2987896 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96371
in IEEE Transactions on geoscience and remote sensing > Vol 58 n° 12 (December 2020) . - pp 8427 - 8437[article]Analysis of the effect of climate warming on paludification processes: Will soil conditions limit the adaptation of Northern boreal forests to climate change? A synthesis / Ahmed Laamrani in Forests, vol 11 n°11 (November 2020)PermalinkA preliminary exploration of the cooling effect of tree shade in urban landscapes / Qiuyan Yu in International journal of applied Earth observation and geoinformation, vol 92 (October 2020)PermalinkSpatio-temporal relationship between land cover and land surface temperature in urban areas: A case study in Geneva and Paris / Xu Ge in ISPRS International journal of geo-information, vol 9 n° 10 (October 2020)PermalinkDeriving a frozen area fraction from Metop ASCAT backscatter based on Sentinel-1 / Helena Bergstedt in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)PermalinkPhotoperiod and temperature as dominant environmental drivers triggering secondary growth resumption in Northern Hemisphere conifers / Jian-Guo Huang in Proceedings of the National Academy of Sciences of the United States of America PNAS, vol 117 n° 34 (August 2020)PermalinkExtraction of urban built-up areas from nighttime lights using artificial neural network / Tingting Xu in Geocarto international, vol 35 n° 10 ([01/08/2020])PermalinkRoles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects / Jike Chen in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)PermalinkDeveloping shopping and dining walking indices using POIs and remote sensing data / Yingbin Deng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkEstimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)PermalinkAssessment of winter season land surface temperature in the Himalayan regions around the Kullu area in India using Landsat-8 data / Divyesh Varade in Geocarto international, vol 35 n° 6 ([01/05/2020])PermalinkTemporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)PermalinkForest gaps retard carbon and nutrient release from twig litter in alpine forest ecosystems / Bo Tan in European Journal of Forest Research, vol 139 n° 1 (February 2020)PermalinkMODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment / Salahuddin M. Jaber in European journal of remote sensing, vol 53 n° 1 (2020)PermalinkObject‐oriented tracking of thematic and spatial behaviors of urban heat islands / Rui Zhu in Transactions in GIS, Vol 24 n° 1 (February 2020)PermalinkCaractérisation du manteau neigeux arctique, suivi climatique et télédétection micro-onde / Céline Vargel (2020)PermalinkUsing remote sensing to assess the effect of time of day on the spatial and temporal variation of LST in urban areas / Akram Abdulla (2020)PermalinkQuantification of the adjacency effect on measurements in the thermal infrared region / Xiaopo Zheng in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)PermalinkMultitemporal Landsat-MODIS fusion for cropland drought monitoring in El Salvador / Nguyen-Thanh Son in Geocarto international, vol 34 n° 12 ([15/09/2019])PermalinkQuantifying the impact of trees on land surface temperature: a downscaling algorithm at city-scale / Elena Barbierato in European journal of remote sensing, vol 52 n° 4 (2019)PermalinkInvestigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data : A case study of Wuhan, Central China / Xin Huang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)Permalink