dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2009; Laroche et al. , 2006). In fact, at NUTS3 scale (Isère department), the artificialization process observed using CLC is +1. 57% (1990-2000)  and 2. 42% (2000-2006). However, our study, located in the southern half of the Isère department (but including 3/4 of the department's population) showed a high and steady increase of +6% for urbanization along the 10 year study period, with even greater rates in valley, plain and plateau areas (+7% to 8%) but lower rates (3. 5%) in the mountain areas. At fine scale, in a region dominated by small-to medium-sized urban areas and only small changes around the existing ones, the observed trends appear to exceed interpretation limits of the CLC database. This fully supports the development of a multi-temporal cartographic database for our study.
Changes in landscapes in mountain regions of the Alps Few other studies have mapped and quantified regional-scale land use and land cover dynamics in mountain regions using appropriate data and typology. However, despite differences in data, typology, spatial and temporal resolution, the major trends of landscape pattern dynamics recur across all studies. For example, two main studies at a large spatial and temporal scale took the challenge of the fine-grain analysis of land use and land cover in alpine landscapes. representative of landscape diversity across the region, and stratified by ecoregions and topography. Their study was based on historical maps and remote sensing data to determine LUCC trends since the 19th century. The typology of their study was very precise, using 35 land cover classes to estimate plant species richness and temporal dynamics.
Second, the OPS program (Swiss Landscape Observation -OFEV, 2010), studied across Switzerland the state and changes of Swiss landscapes, based on national statistical analysis, topographic databases and indicators, since the 1980's. For these two studies, and more generally for analyzing the state and dynamics of a large and complex landscapes, no unique and ideally suited data set can be found. Even remote sensing cannot fulfill all criteria of fine spatial resolution to produce a fine typology relevant over a large area, and covering several decades of retrospective / historical analysis  (Kuenzer et al. , 2014). This imposes methodological trade-offs, which are particularly acute for built-up land or urban settlements, for which precise data is scant  (Antrop, 2004). Despite such methodological trade-offs, but taking into account the main topographic conditions, Zimmerman et al.
However, in the Rhône-Alpes region and particularly in the Grenoble area such an agricultural abandonment process at the benefit of reforestation cannot be observed in our data. Forest boundaries have been very stable for several decades. Some local colonization can however be observed along forest edges in steep and closed landscapes resulting from agricultural abandonment, or in the plain, pending an urbanization process. Our study database allowed us to detect these two processes at specific locations but can be only partially validated because of the lack of externa precise spatial data for encroachment. While our database is not appropriate for describing the dynamics of cropping systems (lack of precise typology and monitoring), these can be observed using remote sensing data even in mountain region (Atzberger 2013;  Ayanu et al.
, 2012; Kuenzer et al. , 2014). Finally the urban densification process, which is the main strategy to reduce urban sprawl, is one of the gaps in our database. While we were able to quantify urban sprawl precisely, observing the densification of existing urban areas proved to be impossible at this spatial scale. Quantifying and mapping urban densification over time needs multitemporal and high or very-high spatial resolution remote sensing data  (Bhatta et al. , 2010; Wurm et al. , 2010; Banzhaf and Hofer, 2008; Rashed, 2008). The Urban Atlas (from the European Environment Agency -EEA) could allow us to quantify urban sprawl. This database, created using remote sensing classification and photo-interpretation, maps precisely land cover and urban density for all large urban zones with more than 100,000 inhabitants in Europe.
Landscape analysis for ecosystem services assessments and land planning This study was developed in partnership with local stakeholders of the Grenoble region. The ultimate aim for this database was to produce spatially-explicit and exhaustive knowledge for the whole Grenoble area at three dates. The spatial scale, map typology and indicators of landscape dynamic analysis were developed according to the needs of stakeholders, as identified during dedicated workshops. This participatory experience allowed us to develop a database and targeted indicators such as the synthetic map (presented in section 3. 2. ) that could be useful for stakeholders and public dissemination. This synthetic map represents trajectories of changes at the municipality scale. It displays in compact visual form the nature of changes and highlights the importance of urbanization as the dominant driver of change in the study area during the 1998-2009 period.
Typologies, such as the one we developed, are a common tool to cluster spaces with similar characteristics and possibly similar policy needs  (Davis and Hansen, 2011; Verburg et al. , 2010). Therefore, we believe that the synthetic map we proposed at municipality scale should help managers, decision makers and land use planners in their decision exercises by providing information on land use trajectories. Furthermore the whole database will be used for supporting ecosystem services mapping taking into account and addressing stakeholders main concerns. Indeed, the ecosystem.
process was initially conducted for the 2009 data. The 2003 and 1998 land cover maps were then produced by identifying changes, which were manually digitized using IGN orthophotoplans of 2003 and 1998. From the 2009 final map, we identified the changes that occurred over the 2003-2009 period by photo-interpretation of the 2003 orthophotoplan and thus obtained the 2003 final map through this backwards updating process. We repeated the same process to obtain the 1998 land cover map. The use of the BD Topo database by 1998 and 2003 (Table.
Patterns of landscape change in a rapidly urbanizing mountain region Cybergeo : European Journal of Geography , Cartographie, Imagerie, SIG | 2016 la fusion de données spatiales multi-sources et de l'interprétation de photographies aériennes. Cette analyse, sur trois dates, à partir d'une base de données de 4450 km² au 1:15000 ème comportant 23 classes d'occupation des sols, a permis de montrer la croissance urbaine rapide et régulière, supérieure à 6% le long des onze années de la période étudiée, ayant lieu pour l'essentiel au détriment des espaces agricoles. Une carte de synthèse des changements observés, présentée à l'échelle communale, montre l'importance des zones nouvellement artificialisées non seulement dans le fond de la vallée autour de Grenoble, mais également dans les principales zones de plaines agricoles de la Bièvre et du Voironnais.
La plupart des changements d'occupation des sols s'effectuent dans la continuité des espaces similaires existants. Ils induisent une fragmentation limitée du paysage, comme c'est le cas des espaces nouvellement urbanisés apparaissant dans la continuité de la tache urbaine existante. Les résultats obtenus dans cette étude illustrent une des préoccupations majeures des Alpesd'Europe occidentale (Suisse, Italie, Autriche. ), à savoir que le taux actuel d'urbanisation n'est pas soutenable à long terme dans des vallées alpines fragilisées. A cet égard, notre base de données cartographique fournit une information de base pour un exercice prospectif participatif effectué avec les acteurs locaux de la région de Grenoble dans le but de soutenir une gestion territoriale et une planification locale durables.
Climate We estimated temperature, precipitation, and relative humidity from two different sources. First, in 2007, HOBO Pro V2 microloggers (Onset Computer, Cape Cod, Massachusetts, USA) were placed at each sampling site, and they registered daily maximum and minimum temperatures, the average relative humidity, and total precipitation  (Cailleret and Davi 2011). Second, we used climate data from the French weather service ("SAFRAN" data set from Meteo France;  Vidal et al. 2010) , which are available at an 8-km grid scale for the period from 1959 to 2013, to estimate the long-term climatic variables at each site. We used linear models with daily time steps to correct the SAFRAN data for the local climatic conditions based on the relationship between the observed HOBO data and the SAFRAN data for the period of overlap  (i.
Cone production data sets In this study, we compiled nine cone production data sets: six from Mont Ventoux and one each from Lure, Issole, and Vésubie (see Table  1 ). Brown, ripened cones were always counted using binoculars at the end of the summer prior to seed release; aborted cones were not included. This visual counting is a good approximation of the total number of cones, although this number may be underestimated  (LaMontagne et al. 2005). The data set covers the period from 1998 to 2014 without interruption, except for the year 2001.
Endogenous variables We measured the diameter at breast height (dbh) and height (H) of each tree using a Forester VERTEX III (Haglöf, Langsele, Sweden). Using binoculars, we assessed the crown defoliation rate in the late summer of  2007 , 2008 , 2011 , 2012 , 2013 , and 2014 along the Ventoux DET; in 2007 , 2008 , 2012 , 2013 , and 2014 along the Ventoux CLT; and in 2007 , 2008 , 2013 , and 2014  along the Issole DET and the Vésubie DET (details in  Cailleret et al. 2014). The interannual variability and the intertree variability in annual radial growth were assessed using classical treering width analysis. All of the trees included in the Ventoux DET, Ventoux CLT, Issole DET, and Vésubie DET data sets were sampled with an increment borer at breast height in 2009, whereas only a subsample of the trees located in P34, Contrat, Mont Serein, and Lure were sampled in 2007.
Cores were prepared with a razor blade and scanned at 1200 dpi, and ring limits were identified using CooRecorder v5. 3 semiautomatic software (see  Cailleret and Davi 2011, Cailleret et al. 2014). To express the level and variance in annual radial growth and the asymmetry in the ring width distribution, we calculated the mean ring width (rw), the mean sensitivity (MS), and the skewness of the ring width distribution, respectively; MS was calculated after detrending the raw chronology using smoothing splines (dplR package in R). Tree-ring data were also used to assess cambial age (at breast height), and because the trees differed in age and not all of the cores were sampled in the same year, all these variables were estimated for the common period 1974-2003 (all trees were born in 1974 and many trees died after 2003 because of repeated droughts)  (Cailleret et al.
Statistical analyses First, we estimated the average cone production across years and the relationship between cone production and its coefficient of variation using the Ventoux data set. Using all the different data sets, we then estimated the Spearman correlation coefficient between years to test whether the high producers remained the same between years. Because of the multicollinearity between the variables used to characterize tree structure or function (e. g. , dbh and H), we performed a principal component analysis (PCA) to reduce the number of variables and thus to perform the regression analysis on independent variables. This was carried out using the FactoMine package in R  (Lê et al. 2008)  with the following variables (hereafter termed endogenous factors): dbh, H, age, crown defoliation rate, mean rw, skewness of the ring width series, and MS.
We used the first four principal axes obtained from this PCA in the subsequent analyses. These axes correspond to the main sources of variation and represent the endogenous factors related to cone production. We performed two PCA: one for DEG data sets and one for CLT data sets. Next, a generalized linear mixed model  (Littell et al. 2006 ) was used to disentangle the effects of the endogenous factors (using the lme4 R package;  Bates et al. 2014) ; the random effect for the intercept was grouped by tree to consider that trees may have different cone production irrespective of the factors included here (e. g. , genetic variability). We chose a logarithmic link function to account for the cone production distribution and a Poisson distribution to describe the error distribution. We compared the effects of each variable using F-values obtained by ANOVA.
Model 1: where λ ise is the annual number of cones produced by each tree. On the Ventoux CLT data set, all trees are at same elevation, and thus, we created a generalized linear mixed model with only the endogenous factors. Model 2: For the DET data sets (pooling the Ventoux, Vésubie, and Issole sites), both models 1 and 2 were used; the residuals of model 2 were plotted against the elevation of every site and year to identify any potential non-monotonic effects of elevation and the complex interactions between site, year, and elevation. Indeed, two different limiting factors may constrain reproduction at the two edges of the elevation gradient: low temperature at high elevations and drought at low elevations, their intensity varying among sites and years. According to the Ventoux CLT data set, the axes obtained from the PCA could differ slightly, especially because we excluded some variables (SITE for CLT and CET and ELV for CLT) from model 2.
Structure of the endogenous factors The PCA of the endogenous factors revealed that 81. 06% and 87. 45% of the variation in cone production in the DET and CLT data sets, respectively, were explained by the first four axes (Fig. 3 ). In both data sets, tree dbh and height were the main components of the variability in the endogenous factors and were positively related to axis 1 (Fig. 3 , r = 0. 85 and r = 0. 88 with dbh for the DET and CLT data sets, respectively). Mean rw was not related to tree size, but was negatively correlated with axis 2 (Fig. 3 , r = -0. 7 and r = -0. 61 for the DET and CLT data sets, respectively). Finally, crown defoliation and the skewness index of rw distribution were the last components of the endogenous factors and were positively correlated with axis 3 (r = 0.
Effects of tree characteristics on cone production A first key result is the large variability in cone production observed between trees. The coefficient of variation averaged 160% that was in line with the values found by  Lamontagne and Boutin (2007)  on Picea abies (between 184% and 215%). Using mixed-effects linear models allowed for decomposition between the various   fixed effects (i. e. , the environment and the endogenous effects summarized by the PCA) and the random effects not explicitly considered in the model (e. g. , tree name as a grouping variable of the random effect on the intercept). For both CET and DET data sets, respectively, 30% and 40% of the variability between trees were not explained by the fixed effects. This variability likely includes the genetic variation among trees in terms of the allocation to reproduction, but also the interactions between endogenous factors  (Barringer et al.
2013 ) and the endogenous factors that have been not measured (e. g. , crown volume, local crown overlap, or the content of nonstructural carbohydrates). If tree size and/or age were the most important drivers of cone production, trees being more productive as they become older and larger  (Debain et al. 2003 , Amm et al. 2012 , Viglas et al. 2013) , this study also demonstrates that other biotic effects must be considered. This size effect can be disentangled from the effect of recent radial growth. Indeed, recent growth was negatively related to cone production in the DET data sets. This negative relationship was also found in Ventoux CLT before 2000, for both old and young trees by comparing past growth of high-producing vs. low-producing trees. A negative correlation between radial growth and tree size (see  Bowman et al.
Relationships between climate conditions and mast events Only 16 yr were available in our data set, which limits the inference of strong climate impacts on cone production. However, we demonstrated that the use of separate data sets does not bias the conclusions because the year effect was similar when using raw data (average cone production per year) or when analyzing the coefficients associated with the year effect in a modeling approach. We tested many climatic variables (e. g. , minimum monthly relative humidity or global radiation) that have never been tested in previous studies. The climatic variables that best explained the interannual variability in cone production and mast events included precipitation, temperature, and relative humidity. Moreover, in line with the recent study by  Kelly et al.
We wish to thank N. Mariotte, W. Brunetto, F. Courdier, and the UEFM team (especially O. Gilg, N. Turion and F. Jean) for their contribution to field measurements and dendrochronological analyses. The French Research National Agency (ANR) and INRA supported research funding in the frame of the DRYADE project (ANR-06-VULN-004) and this work was also supported by the metaprogramme Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for AgriculturalResearch (INRA). This were supported also by the ERAnet BiodivERsA project, LinkTree (ANR-08-Biodiversa-006-06) and was made possible by the grant, Conservation des Ressources Génétiques Forestières from the French Ministry of Agriculture to INRA-URFM. Financial support to Gwendal Restoux during his Ph. D.
acknowledgMents We wish to thank N. Mariotte, W. Brunetto, F. Courdier, and the UEFM team (especially O. Gilg, N. Turion and F. Jean) for their contribution to field measurements and dendrochronological analyses. The French Research National Agency (ANR) and INRA supported research funding in the frame of the DRYADE project (ANR-06-VULN-004) and this work was also supported by the metaprogramme Adaptation of Agriculture and Forests to Climate Change (AAFCC) of the French National Institute for AgriculturalResearch (INRA). This were supported also by the ERAnet BiodivERsA project, LinkTree (ANR-08-Biodiversa-006-06) and was made possible by the grant, Conservation des Ressources Génétiques Forestières from the French Ministry of Agriculture to INRA-URFM. Financial support to Gwendal Restoux during his Ph.
ABSTRACT The net radiation flux available at the Earth's surface drives evapotranspiration, photosynthesis and other physical and biological processes. The only cost-effective way to capture its spatial and temporal variability at regional and global scales is remote sensing. However, the accuracy of net radiation derived from remote sensing data has been evaluated up to now over a limited number of in situ measurements and ecosystems. This study aims at evaluating estimates and uncertainties on net radiation derived from Landsat-7 images depending on reliability of the input surface variables albedo, emissivity and surface temperature. The later includes the reliability of remote sensing information (spectral reflectances and top of canopy brightness temperature) and shortwave and longwave incoming radiations.
Primary information describing the surface is derived from remote sensing observations. Surface albedo is estimated from spectral reflectances using a narrow-tobroadband conversion method. Land surface temperature is retrieved from top of canopy brightness temperature by accounting for land surface emissivity and reflection of atmospheric radiation; and emissivity is estimated using a relationship with a vegetation index and a spectral database of soil and plant canopy properties in the study area. The net radiation uncertainty is assessed using comparison with ground measurements over the Crau-Camargue and lower Rhone valley regions in France. We found Root Mean Square Errors between retrievals and field measurements of 0. 25-0. 33 (14-19 %) for albedo, ~1. 7 K for surface temperature and ~20 Wm -2 (5 %) for net radiation.
g. , for Moderate-Resolution Imaging Spectroradiometer (MODIS), SPOT-VEGETATION or PROBA-V sensors). The use of these products has made it possible strong progresses in global water and carbon cycle studies and monitoring the impact of recent climate evolutions over land (e. g. ,  Ciais et al. (2005) ,  Tang et al. (2014) ,  Xia et al. (2014) ). The development of similar products for Earth Observation satellites at higher resolution is in project with the supply of new services for distributing ready-to-use information to the user community. Evidence of this is a data center dedicated to land surfaces named THEIA which has started to operate in 2014 in France  (Hagolle et al. 2015; WWW1). It is a French national inter-agency organization designed to foster the use of images coming from the space observation of land surfaces.
Within the Land Data Centre, the French Space Agency CNES set up a production center named MUSCATE (WWW2) which aims to provide operational products derived from time series of images acquired by Landsat, SPOT and Formosat-2 and later by the future satellites Sentinel-2 and Venµs  (L'Helguen et al. (2014) ;  Leroy et al. (2014) ;  Hagolle et al. (2015) ). Concerning Landsat, the data presently available consist in Top Of Canopy (TOC) spectral reflectances, together with a cloud mask, and Top Of Atmosphere (TOA) brightness temperatures. Work is undergoing for the production of TOC brightness temperature and surface temperature  (Rivalland et al. 2014). The main advantages of using land surface products result from 1) the availability of information that can be used in applications without requiring a strong expertise in the preprocessing of remote sensing images (e.
We focused on the derivation of albedo, emissivity and surface temperature from Landsat-7 products provided by the THEIA Land Data Centre. The analysis was performed over the lower Rhône Valley region, South Eastern France, where a dense network of ground stations measuring surface energy balance components and meteorological variables was set up on various surfaces for several years. The methodology and data are presented in Section 2. Results are presented in Section 3 and discussed in Section 4, respectively.
Landsat data The ETM+ (on board of Landsat-7) acquires data following a Sun synchronous orbit with a revisit interval of 16 days since 1999. Since May 2003, only the central part of the scene is easily workable, with approximately 44 km swath available  (Chander et al. 2009). ETM+ measures radiances in 7 spectral bands covering the solar and the thermal domains. Instantaneous fields of view of the sensor correspond to a spatial resolution at the ground of 30 m for bands 1 to 4 (visible to near infrared), 5 and 7 (middle infrared) and 60 m for band 6 (thermal infrared band). Landsat data used in this study were provided as ready-to-use products by the production center named MUSCATE set up by CNES within THEIA  (Hagolle et al. 2015; L'Helguen et al. 2014; WWW1). They consist in TOC spectral reflectances and TOA brightness temperatures.
We also produced TOC brightness temperature as a prototyping phase of future products  (Rivalland et al. 2014). The original data were downloaded from USGS (US Geological Survey) and then processed by MUSCATE. Images were corrected for geolocation, radiometric calibration and atmospheric effects according to the methods described by  Baillarin et al. (2008)  and  Hagolle et al. (2008 Hagolle et al. ( , 2010 Hagolle et al. ( , 2015)). Radiometric calibration was performed using the calibration coefficients provided by USGS  (Chander et al. 2009 ). The calibration uncertainties of at-sensor spectral radiances are 5 %  (Chander et al. 2009). Atmospheric corrections in the solar domain, as well as the creation of masks for clouds, cloud's shadows, water bodies and snow surfaces were performed using the Multisensor Atmospheric Correction and Cloud Screening (MACCS)  (Hagolle et al.