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Knowing is not enough: exploring the missing link between climate change knowledge and action of German forest owners and managers / Yvonne Hengst-Ehrhart in Annals of Forest Science [en ligne], Vol 76 n° 4 (December 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 76 n° 4 (December 2019) Titre : Knowing is not enough: exploring the missing link between climate change knowledge and action of German forest owners and managers Type de document : Article/Communication Auteurs : Yvonne Hengst-Ehrhart, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Allemagne [Termes descripteurs IGN] foresterie [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] industrie forestière [Termes descripteurs IGN] politique forestière [Termes descripteurs IGN] propriétaire forestier [Termes descripteurs IGN] régression multiple [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message : Adaptation to climate change is a complex but urgent task in forest management; however, a lack of action is widely reported. This study shows that adaptive action on both stand and business levels is missing in forest management. Beyond the cognitive dimension, affective and conative aspects should be promoted through awareness-raising initiatives specific to different target groups. Context : Adaptation to climate change is a complex but urgent task in forest management. A lack of action is widely reported combined with a call for awareness-raising and better knowledge transfer to bridge the gap between knowledge and action. Aims : Based on an understanding of awareness encompassing cognitive, affective, and conative dimensions, the paper aims to clarify (1) what kind of adaptive measures are missing in forest management and (2) if there is a gap in climate change awareness of forest owners and managers hindering adaptive action. Methods : An online survey among German forest owners and managers was conducted. The theory of planned behavior was selected to examine variables which support the implementation of adaptive measures and to examine different awareness dimensions. Data was analyzed using descriptive statistics and multiple linear regression analysis. Results : Adaptive measures on stand level were more often implemented than those on business level. All awareness dimensions were influential for the intention to implement adaptive measures. Experience and attitude towards adaptive measures were most important while social norm and perceived behavioral control were influential in some groups. Conclusion : The potential of adaptive measures on stand level and particularly on business level is not fully exploited. Based on these findings, awareness-raising initiatives and forest consultancy can be adapted to consider the specific perspectives of target groups as a means of promoting the implementation of adaptive measures. Numéro de notice : A2019-532 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0878-z date de publication en ligne : 16/10/2019 En ligne : https://doi.org/10.1007/s13595-019-0878-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94120 [article]

Sea level variation around Australia and its relation to climate indices / Armin Agha Karimi in Marine geodesy, vol 42 n° 5 (September 2019)  

Public [article]  inMarine geodesy > vol 42 n° 5 (September 2019) . - pp 469 - 489 Titre : Sea level variation around Australia and its relation to climate indices Type de document : Article/Communication Auteurs : Armin Agha Karimi, Auteur ; Xiaoli Deng, Auteur ; Ole Baltazar Andersen, Auteur Année de publication : 2019 Article en page(s) : pp 469 - 489 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] analyse spectrale [Termes descripteurs IGN] Australie [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] changement du niveau de la mer [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] El Niño-Southern oscillation [Termes descripteurs IGN] Indien (océan) [Termes descripteurs IGN] Pacifique (océan) [Termes descripteurs IGN] régression multiple Résumé : (auteur) This study aims at investigating the intradecadal and decadal signals of the sea level using 25 years of altimetry data around Australia. We have used the multivariable spectral analysis to extract six periodic signals at the 95% confidence level from altimetry-derived sea-level time series in the study area. They are signals with periods of 1, 1.5, 3, 4.3, 5.7 and 11.17 years, which can also be detected in the estimated power spectra from climate indices of the Interdecadal Pacific Oscillation, Multivariate ENSO Index, and Pacific Decadal Oscillation. A parametric model including the detected periodic signals is used to estimate sea-level trends. The determined trends in the area are in a good agreement with recent studies that consider effects of climate indices through a multivariate regression model. The advantage of our model is to present more descriptive explanation of the sea level signals around Australia in terms of periodicity and spatial variability. Numéro de notice : A2019-299 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1629131 date de publication en ligne : 26/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1629131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93219 [article]

Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images / Jie Wang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 189 - 201 Titre : Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images Type de document : Article/Communication Auteurs : Jie Wang, Auteur ; Xiangming Xiao, Auteur ; Rajen Bajgain, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 189 - 201 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] Oklahoma (Etats-Unis) [Termes descripteurs IGN] paturage [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] régression multiple Résumé : (Auteur) Grassland degradation has accelerated in recent decades in response to increased climate variability and human activity. Rangeland and grassland conditions directly affect forage quality, livestock production, and regional grassland resources. In this study, we examined the potential of integrating synthetic aperture radar (SAR, Sentinel-1) and optical remote sensing (Landsat-8 and Sentinel-2) data to monitor the conditions of a native pasture and an introduced pasture in Oklahoma, USA. Leaf area index (LAI) and aboveground biomass (AGB) were used as indicators of pasture conditions under varying climate and human activities. We estimated the seasonal dynamics of LAI and AGB using Sentinel-1 (S1), Landsat-8 (LC8), and Sentinel-2 (S2) data, both individually and integrally, applying three widely used algorithms: Multiple Linear Regression (MLR), Support Vector Machine (SVM), and Random Forest (RF). Results indicated that integration of LC8 and S2 data provided sufficient data to capture the seasonal dynamics of grasslands at a 10–30-m spatial resolution and improved assessments of critical phenology stages in both pluvial and dry years. The satellite-based LAI and AGB models developed from ground measurements in 2015 reasonably predicted the seasonal dynamics and spatial heterogeneity of LAI and AGB in 2016. By comparison, the integration of S1, LC8, and S2 has the potential to improve the estimation of LAI and AGB more than 30% relative to the performance of S1 at low vegetation cover (LAI  2 m2/m2, AGB > 500 g/m2). These results demonstrate the potential of combining S1, LC8, and S2 monitoring grazing tallgrass prairie to provide timely and accurate data for grassland management. Numéro de notice : A2019-269 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.06.007 date de publication en ligne : 21/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.06.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93086 [article]

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Investigating 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)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 152 (June 2019) . - pp 119 - 131 Titre : Investigating 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 Type de document : Article/Communication Auteurs : Xin Huang, Auteur ; Ying Wang, Auteur Année de publication : 2019 Article en page(s) : pp 119 - 131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] Chine [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Landsat-TIRS [Termes descripteurs IGN] image ZiYuan-3 [Termes descripteurs IGN] morphologie urbaine [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] Wuhan (Chine) Résumé : (Auteur) The Urban heat island (UHI) effect is an increasingly serious problem in urban areas. Information on the driving forces of intra-urban temperature variation is crucial for ameliorating the urban thermal environment. Although prior studies have suggested that urban morphology (e.g., landscape pattern, land-use type) can significantly affect land surface temperature (LST), few studies have explored the comprehensive effect of 2D and 3D urban morphology on LST in different urban functional zones (UFZs), especially at a fine scale. Therefore, in this research, we investigated the relationship between 2D/3D urban morphology and summer daytime LST in Wuhan, a representative megacity in Central China, which is known for its extremely hot weather in summer, by adopting high-resolution remote sensing data and geographical information data. The “urban morphology” in this study consists of 2D urban morphological parameters, 3D urban morphological parameters, and UFZs. Our results show that: (1) The LST is significantly related to 2D and 3D urban morphological parameters, and the scattered distribution of buildings with high rise can facilitate the mitigation of LST. Although sky view factor (SVF) is an important measure of 3D urban geometry, its influence on LST is complicated and context-dependent. (2) Trees are the most influential factor in reducing LST, and the cooling efficiency mainly depends on their proportions. The fragmented and irregular distribution of grass/shrubs also plays a significant role in alleviating LST. (3) With respect to UFZs, the residential zone is the largest heat source, whereas the highest LST appears in commercial and industrial zones. (4) Results of the multivariate regression and variation partitioning indicate that the relative importance of 2D and 3D urban morphological parameters on LST varies among different UFZs and 2D morphology outperforms 3D morphology in LST modulation. The results are generally consistent in spring, summer and autumn. These findings can provide insights for urban planners and designers on how to mitigate the surface UHI (SUHI) effect via rational landscape design and urban management during summer daytime. Numéro de notice : A2019-456 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.04.010 date de publication en ligne : 22/04/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.04.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92869 [article]

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Including Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data / Abdelhakim Amazirh in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 150 (April 2019) . - pp 11 - 26 Titre : Including Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data Type de document : Article/Communication Auteurs : Abdelhakim Amazirh, Auteur ; Olivier Merlin, Auteur ; Salah Er-Raki, Auteur Année de publication : 2019 Article en page(s) : pp 11 - 26 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] désagrégation [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Maroc [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] régression multiple [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] zone semi-aride Résumé : (Auteur) The use of land surface temperature (LST) for monitoring the consumption and water status of crops requires data at fine spatial and temporal resolutions. Unfortunately, the current spaceborne thermal sensors provide data at either high temporal (e.g. MODIS: Moderate Resolution Imaging Spectro-radiometer) or high spatial (e.g. Landsat) resolution separately. Disaggregating low spatial resolution (LR) LST data using ancillary data available at high spatio-temporal resolution could compensate for the lack of high spatial resolution (HR) LST observations. Existing LST downscaling approaches generally rely on the fractional green vegetation cover (fgv) derived from HR reflectances but they do not take into account the soil water availability to explain the spatial variability in LST at HR. In this context, a new method is developed to disaggregate kilometric MODIS LST at 100 m resolution by including the Sentinel-1 (S-1) backscatter, which is indirectly linked to surface soil moisture, in addition to the Landsat-7 and Landsat-8 (L-7 & L-8) reflectances. The approach is tested over two different sites – an 8 km by 8 km irrigated crop area named “R3” and a 12 km by 12 km rainfed area named “Sidi Rahal” in central Morocco (Marrakech) – on the seven dates when S-1, and L-7 or L-8 acquisitions coincide with a one-day precision during the 2015–2016 growing season. The downscaling methods are applied to the 1 km resolution MODIS-Terra LST data, and their performance is assessed by comparing the 100 m disaggregated LST to Landsat LST in three cases: no disaggregation, disaggregation using Landsat fgv only, disaggregation using both Landsat fgv and S-1 backscatter. When including fgv only in the disaggregation procedure, the mean root mean square error in LST decreases from 4.20 to 3.60 °C and the mean correlation coefficient (R) increases from 0.45 to 0.69 compared to the non-disaggregated case within R3. The new methodology including the S-1 backscatter as input to the disaggregation is found to be systematically more accurate on the available dates with a disaggregation mean error decreasing to 3.35 °C and a mean R increasing to 0.75. Numéro de notice : A2019-136 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.02.004 date de publication en ligne : 15/02/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.02.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92467 [article]

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Urban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)  

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Introduction to multiple regression equations in datum transformations and their reversibility / A.C. Ruffhead in Survey review, vol 50 n° 358 (January 2018)  

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Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds / Paweł Hawryło in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)  

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Fusing tree‐ring and forest inventory data to infer influences on tree growth / Margaret E.K. Evans in Ecosphere, vol 8 n° 7 (July 2017)  

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Data science par la pratique : fondamentaux avec Python / Joël Grus (2017)

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Space-time multiple regression model for grid-based population estimation in urban areas / Ko Ko Lwin in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)  

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Relationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)  

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La ville à l’échelle de l’Europe : apports du couplage et de l’expertise de bases de données issues de l’imagerie satellitale / Anne Bretagnolle in Revue internationale de géomatique, vol 26 n° 1 (janvier - mars 2016)

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Estimation of forest biomass using multivariate relevance vector regression / Alireza Sharifi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 1 (January 2016)

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Regional dynamics of terrestrial vegetation productivity and climate feedbacks for territory of Ukraine / Dmytro Movchan in International journal of geographical information science IJGIS, vol 29 n° 8 (August 2015)  

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