Échelle spatiale | EPFL Graph Search

L'échelle spatiale est la notion d'échelle appliquée à la description et la catégorisation d'espaces selon leurs tailles. Définitions Sens commun La notion d'échelle (proportion) n'est pas propre à la géographie. Elle se compose au minimum de deux niveaux. La notion exprime l'idée qu'en faisant varier la taille d'un phénomène, on modifie également les aspects associés en les rendant visibles ou invisibles, plus détaillés ou moins détaillées. Parler d'échelle spatiale revient à considérer qu'autre chose que la taille d'un espace change lorsque sa taille vient à être changée. Changement d'état et seuil L'application de la définition commune aux sciences de l'espace social n'est pas simple. La variété des ordres sociaux de grandeur ne permet pas de se référer à la res extensa cartésienne ou aux seules caractéristiques de la relativité, que sont l'espace et le temps, en physiqueIdem, 285.. Pour pallier ces difficultés, l'homme produit diffé

Spatial and temporal heterogeneity of methane ebullition in lowland headwater streams and the impact on sampling design

Headwater streams are known sources of methane (CH4) to the atmosphere, but their contribution to global scale budgets remains poorly constrained. While efforts have been made to better understand diffusive fluxes of CH4 in streams, much less attention has been paid to ebullitive fluxes. We examine the temporal and spatial heterogeneity of CH4 ebullition from four lowland headwater streams in the temperate northeastern United States over a 2-yr period. Ebullition was observed in all monitored streams with an overall mean rate of 1.00 +/- 0.23 mmol CH4 m(-2) d(-1), ranging from 0.01 to 1.79 to mmol CH4 m(-2) d(-1) across streams. At biweekly timescales, rates of ebullition tended to increase with temperature. We observed a high degree of spatial heterogeneity in CH4 ebullition within and across streams. Yet, catchment land use was not a simple predictor of this heterogeneity, and instead patches scale variability weakly explained by water depth and sediment organic matter content and quality. Overall, our results support the prevalence of CH4 ebullition from streams and high levels of variability characteristic of this process. Our findings also highlight the need for robust temporal and spatial sampling of ebullition in lotic ecosystems to account for this high level of heterogeneity, where multiple sampling locations and times are necessary to accurately represent the mean rate of flux in a stream. The heterogeneity observed likely indicates a complex set of drivers affect CH4 ebullition from streams which must be considered when upscaling site measurements to larger spatial scales.

2021

Sparse coupled logistic regression to estimate co-activation and modulatory influences of brain regions

Thomas William Arthur Bolton, Ye Tian, Dimitri Nestor Alice Van De Ville

Accurate mapping of the functional interactions between remote brain areas with resting-state functional magnetic resonance imaging requires the quantification of their underlying dynamics. In conventional methodological pipelines, a spatial scale of interest is first selected and dynamic analysis then proceeds at this hypothesised level of complexity. If large-scale functional networks or states are studied, more local regional rearrangements are then not described, potentially missing important neurobiological information. Here, we propose a novel mathematical framework that jointly estimates resting-state functional networks and spatially more localised cross-regional modulations. To do so, the changes in activity of each brain region are modelled by a logistic regression including co-activation coefficients (reflective of network assignment, as they highlight simultaneous activations across areas) and causal interplays (denoting finer regional cross-talks, when one region active at time t modulates the t to t + 1 transition likelihood of another area). A two-parameter l1

IOP PUBLISHING LTD2020

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

Dimitra Mamali, Athanasios Nenes

Aerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n(250,dry) with an uncertainty of 20 % to 40 % and S-dry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range -50 to -33 degrees C) agree within 1 order of magnitude with the in situ observations of n(INp); thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range -35 to -9 degrees C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (n(INP)) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic datasets are expected to become available in the future from EARLINET (European Aerosol Research Lidar Network) and in the frame of the European ACTRIS-RI (Aerosols, Clouds, and Trace gases Research Infrastructure). Our analysis shows that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations, are in agreement with the in situ measurements. This study gives us confidence for the production of global 3D products of cloud-relevant particle number concentrations (n(250,dry,) S-dry and n(INP)) using the CALIPSO 13-year dataset. This could provide valuable insight into the global height-resolved distribution of INP concentrations related to mineral dust, as well as possibly other aerosol types.

2019

Retrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements

Dimitra Mamali, Athanasios Nenes

2019