Impact of ATCO Training and Expertise on Dynamic Spatial Abilities

Dynamic spatial ability is supposed to be involved in a critical process of air traffic controllers, namely conflict detection. The present paper aims at testing whether dynamic spatial ability improves with air traffic control training and/or experience. We designed a laboratory task to assess the performance in predicting if two moving disks would collide or not. We conducted a crosssectional study with four groups of participants : ATCO trainees at the beginning (N=129), middle (N=80) or end of training (N=66) and experienced ATCOs (N=14). Results suggested on one hand that air traffic control training leads to a decrease in the number of extremely high proportions of undetected collisions from the middle of the training. On the other hand, air traffic control operational experience leads to a decrease in the number of extremely high proportions of falsely detected collisions

Building a Data Set over 12 Globally Distributed Sites to Support the Development of Agriculture Monitoring Applications with Sentinel-2

Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel­2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel­2 for Agriculture” system.Instituto de Clima y AguaFil: Bontemps, Sophie. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Arias, Marcela. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Cara, Cosmin. CS Romania S.A.; RumaniaFil: Dedieu, Gérard. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Guzzonato, Eric. CS Systèmes d’Information; FranciaFil: Hagolle, Olivier. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Inglada, Jordi. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Matton, Nicolas. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Morin, David. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Popescu, Ramona. CS Romania S.A.; RumaniaFil: Rabaute, Thierry. CS Systèmes d’Information; FranciaFil: Savinaud, Mickael. CS Systèmes d’Information; FranciaFil: Sepulcre, Guadalupe. Université Catholique de Louvain. Earth and Life Institute; BélgicaFil: Valero, Silvia. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Ahmad, Ijaz. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Bégué, Agnès. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Wu, Bingfang. Chinese Academy of Sciences. Institute of Remote Sensing and Digital Earth; República de ChinaFil: De Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Diarra, Alhousseine. Université Cadi Ayyad. Faculté des Sciences Semlalia; MarruecosFil: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: French, Andrew. United States Department of Agriculture. Agricultural Research Service. Arid Land Agricultural Research Center; ArgentinaFil: Akhtar, Ibrar ul Hassan. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; PakistánFil: Kussul, Nataliia. National Academy of Sciences of Ukraine. Space Research Institute and State Space Agency of Ukraine; UcraniaFil: Lebourgeois, Valentine. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; FranciaFil: Le Page, Michel. Université Cadi Ayyad. Faculté des Sciences Semlalia. Laboratoire Mixte International TREMA; Marruecos. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; FranciaFil: Newby, Terrence. Agricultural Research Council; SudáfricaFil: Savin, Igor. V.V. Dokuchaev Soil Science Institute; RusiaFil: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; ArgentinaFil: Koetz, Benjamin. European Space Agency. European Space Research Institute; ItaliaFil: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute; Bélgic

Visualizing complexities: the human limits of air traffic control

International audienceAir traffic management is organized into filters in order to prevent tactical controllers from dealing with complex conflicting situations. In this article, we describe an experiment showing that a dynamic conflict display could improve human performance on complex conflict situations. Specifically, we designed a display tool that represents the conflicting portions of aircraft trajectories and the evolution of the conflict zone when the user adds a maneuver to an aircraft. The tool allows the user to dynamically check the potential conflicting zones with the computer mouse before making a maneuver decision. We tested its utility on a population of forty students: twenty air traffic controller (ATC) students at the end of their initial training and twenty engineering students with the same background but no ATC training. They had to solve conflicts involving 2–5 aircraft with a basic display and with the dynamic visualization tool. Results show that in easy situations (2 aircraft), performance is similar with both displays. However, as the complexity of the situations grows (from 3 to 5 aircraft), the dynamic visualization tool enables users to solve the conflicts more efficiently. Using the tool leads to fewer unsolved conflicts and shorter delays. No significant differences are found between the two test groups except for delays: ATC students give maneuvers that generate less delays than engineering students. These results suggest that humans are better able to manage complex situations with the help of our conflict visualization tool

Impact of ATCO training and expertise on dynamic spatial abilities

International audienceDynamic spatial ability is supposed to be involved in a critical process of air traffic controllers, namely conflict detection. The present paper aims at testing whether dynamic spatial ability improves with air traffic control training and/or experience. We designed a laboratory task to assess the performance in predicting if two moving disks would collide or not. We conducted a cross-sectional study with four groups of participants : ATCO trainees at the beginning (N=129), middle (N=80) or end of training (N=66) and experienced ATCOs (N=14). Results suggested on one hand that air traffic control training leads to a decrease in the number of extremely high proportions of undetected collisions from the middle of the training. On the other hand, air traffic control operational experience leads to a decrease in the number of extremely high proportions of falsely detected collisions

Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas. With its 10 m to 20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However, many components of the ecological network are still smaller than the 10 m pixel, i.e., they are sub-pixel targets that stretch the sensor’s resolution to its limit. This paper proposes a framework to empirically estimate the minimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2. The same approach was also applied to Landsat-8 and SPOT-5 (Take 5), which can be considered as similar in terms of spectral definition and spatial resolution, respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case. Overall, results for Sentinel-2 highlight the critical importance of a good compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of 3 m and small water bodies are separable with a diameter larger than 11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications

An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series

Cropland mapping relies heavily on field data for algorithm calibration, making it, in many cases, applicable only at the field campaign scale. While the recently launched Sentinel-2 satellite will be able to deliver time series over large regions, it will not really be compatible with the current mapping approach or the available in situ data. This research introduces a generic methodology for mapping annual cropland along the season at high spatial resolution with the use of globally available baseline land cover and no need for field data. The methodology is based on cropland-specific temporal features, which are able to cope with the diversity of agricultural systems, prior information from which mislabeled pixels have been removed and a cost-effective classifier. Thanks to the JECAM network, eight sites across the world were selected for global cropland mapping benchmarking. Accurate cropland maps were produced at the end of the season, showing an overall accuracy of more than 85%. Early cropland maps were also obtained at three-month intervals after the beginning of the growing season, and these showed reasonable accuracy at the three-month stage (>70% overall accuracy) and progressive improvement along the season. The trimming-based method was found to be key for using spatially coarse baseline land cover information and, thus, avoiding costly field campaigns for prior information retrieval. The accuracy and timeliness of the proposed approach shows that it has substantial potential for operational agriculture monitoring programs

Total Metabolic Tumor Volume on 18F-FDG PET/CT Is a Useful Prognostic Biomarker for Patients with Extensive Small-Cell Lung Cancer Undergoing First-Line Chemo-Immunotherapy

Background: We aimed to evaluate the prognostic value of imaging biomarkers on 18F-FDG PET/CT in extensive-stage small-cell lung cancer (ES-SCLC) patients undergoing first-line chemo-immunotherapy. Methods: In this multicenter and retrospective study, we considered two cohorts, depending on the type of first-line therapy: chemo-immunotherapy (CIT) versus chemotherapy alone (CT). All patients underwent baseline 18-FDG PET/CT before therapy between June 2016 and September 2021. We evaluated clinical, biological, and PET parameters, and used cutoffs from previously published studies or predictiveness curves to assess the association with progression-free survival (PFS) or overall survival (OS) with Cox prediction models. Results: Sixty-eight patients were included (CIT: CT) (36: 32 patients). The median PFS was 5.9:6.5 months, while the median OS was 12.1:9.8 months. dNLR (the derived neutrophils/(leucocytes-neutrophils) ratio) was an independent predictor of short PFS and OS in the two cohorts (p high if > 241 cm3) correlated with outcomes, but only in the CIT cohort (PFS for TMTVhigh in multivariable analysis: HR 2.5; 95%CI 1.1–5.9). Conclusion: Baseline 18F-FDG PET/CT using TMTV could help to predict worse outcomes for ES-SCLC patients undergoing first-line CIT. This suggests that baseline TMTV may be used to identify patients that are unlikely to benefit from CIT

La « recommandation temporaire d’utilisation » sur le baclofène : point de vue des prescripteurs du dispositif CAMTEA

L’utilisation du baclofène hautes-doses dans l’alcoolo-dépendance a émergé en France depuis 2008 à partir de constatations empiriques, et cette utilisation se fait toujours aujourd’hui en dehors de l’autorisation de mise sur le marché. Néanmoins, en raison de la diffusion rapide de cette pratique de prescription, les autorités françaises de santé ont décidé de l’encadrer grâce à une mesure régulatoire exceptionnelle appelée « recommandation temporaire d’utilisation » (RTU). Les prescripteurs de baclofène de CAMTEA, un dispositif collégial de prescription encadré de baclofène hautes-doses mis en place bien avant la RTU, discutent ici des avantages et des inconvénients de cette mesure et de l’applicabilité de ses différentes modalités dans la pratique clinique quotidienne