Performance factors in the new combined event of modern pentathlon

International audienceTo determine the individual tactics employed by elite modern pentathletes within each discipline of the new combined running-shooting event, and the consequences of these strategies on the overall performance. 36 male pentathletes competing in a world cup event, where running velocity, transition time, shooting time, shooting accuracy and delay per shot were measured. Performances of the top third pentathletes (TOP), the middle third pentathletes (MIDDLE) and the bottom third pentathletes in the combined event (BOTTOM) were compared. The difference in overall performance between TOP and MIDDLE/BOTTOM was predominately associated with a better shooting accuracy (79 ± 13%, 68 ± 12% and 64 ± 10% success rate, for TOP, MIDDLE, BOTTOM, respectively) and a quicker shooting time (86 ± 16s, 109 ± 19s and 117 ± 23s, for the TOP, MIDDLE, BOTTOM, respectively). No significant difference was observed on running velocity, transition time and delay per shot among the three groups. All the competitors started significantly faster over the first 200 m of each of the three 1 km running stages. The last third of the approximately 3km race was completed significantly faster by all pentathletes (p < 0.05). The main finding was that the best performers of the combined event distinguished themselves due to their greater shooting accuracy

Detection of irrigated and rainfed crop fields in temperate areas using Sentinel-1, Sentinel-2 and rainfall time series

International audience&lt;p&gt;&lt;span&gt;Human activities have an impact on the different components of the hydrosphere and 80 % of the world's population is now facing water shortages that will worsen with global warming. Faced with this emergency situation, it is necessary to develop adaptation strategies to monitor and manage water resources for the entire population and to maintain agricultural activity. One of the adaptation strategies that has been favoured is the management of crop irrigation to optimize the use of scarce water ressources. &lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;To meet this objective, it is necessary to have explicit information on irrigated areas. However, up to now, this information is missing or imprecise at the field scale (it is only produced as aggregated statistics or maps at the regional or national scales). In this work, we propose a method for detecting irrigated and rainfed plots in a temperate areas (Adour-Amont watershed of 1500 km&amp;#178; located in south-western France) jointly using optical (Sentinel-2), radar (Sentinel-1) and rainfall (SAFRAN) time series, through the random forest classification algorithm. This spectral information was synthesized in the form of cumulative monthly indices corresponding to the sum of the spectral information for each element (optical, radar, rainfall). This cumulative approach makes it possible to reduce the redundancy of the spectral information and the calculation time of the classification process.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&lt;span&gt;The summer crops studied were maize, soybean and sunflower, representing respectively 82%, 9% and 8% of the crops cultivated of the studied area, but only part of these crops were irrigated. In order to make the distinction for the same crop, we assume that the speed and amplitude of canopy development differs between irrigated and rainfed crop. Five scenarios were used to evaluate the performance of classification models. They have been built according to the different spatialized data, i.e (Optic; Radar; Optic &amp; Radar; Optic, Radar &amp; Rainfall and 10-day images, which is reference scenario without the cumulative monthly indices). Finally, generated classification maps were evaluated using ground truth data collected during 2 years with contrasted meteorological conditions. &lt;/span&gt;&lt;/p&gt;&lt;p&gt; &lt;span&gt;The use of separate radar and optical data gives low results (Overall Accuracy (OA) &lt; 0.5) compared to the combined classifications of the cumulated data set (optical &amp; radar), which gives good results (OA &amp;#177; 0.7). The use of the monthly cumulated rainfall allows a significant improvement of the Fscore of the irrigated and rainfed crop classes. Our study also reveals that the use of cumulative monthly indices leads to performances similar to those of the use of 10-day images while considerably reducing computational resources.&lt;/span&gt;&lt;/p&gt

Physiological demand and pacing strategy during the new combined event in elite pentathletes

International audiencePurpose: To evaluate the physiological demands and effects of different pacing strategies on performance during the new combined event (CE) of the modern pentathlon (consisting of three pistol shooting sessions interspersed by three 1-km running legs).Methods: Nine elite pentathletes realised five tests: a free-paced CE during an international competition; an incremental running test to determine VO2max and its related velocity (vVO2max) and three experimental time-trial CE, where the pacing strategy was manipulated (CEref, CE100%, CE105%). CEref reproduced the international competition strategy with a 170m fast running start within the first 2kilometres. CE100% and CE105% imposed a constant strategy over km-1 and km-2 with a velocity of 100% and 105% of the mean speed adopted over the same sections during the international competition, respectively. Km-3 was always self-paced.Results: The subjects ran CEref at 99±4% of vV .12 O2max and reached 100±5%, 100±7%, 99±8% of VO2max at the end of kilometres 1, 2, and 3, respectively (VO2max: 72±6mlO2.min-1.kg-113 ), with a peak blood lactate concentration of 13.6±1.5mmol.L-114 . No significant differences in overall performance were found between the pacing conditions (753±30s, 770±39s, 768±27s for CEref, CE100% and CE105%,respectively, p=0.63), but all of the shooting performance parameters were only stable in CEref.Conclusion: Completion of CE by elite pentathletes elicits a maximal aerobic contribution coupledwith a high glycolytic supply. Manipulating the mean running speed over km-1 and km-2 had stronginfluence on the overall pacing strategy and induced minor differences in shooting performance but itdidn’t affect overall performance

Detection of irrigated and rainfed crops in temperate areas using Sentinel-1 and Sentinel-2 time series

International audienceThe detection of irrigated areas by means of remote sensing is essential to improve agricultural water resource management. Currently, data from the Sentinel constellation offer new possibilities for mapping irrigated areas at the plot scale. Until now, few studies have used Sentinel-1 (S1) and Sentinel-2 (S2) data to provide approaches for mapping irrigated plots in temperate areas. This study proposes a method for detecting irrigated and rainfed plots in a temperate area (southwestern France) jointly using optical (Sentinel-2), radar (Sentinel-1) and meteorological (SAFRAN) time series, through a classification algorithm. Monthly cumulative indices calculated from these satellite data were used in a Random Forest classifier. Two data years have been used, with different meteorological characteristics, allowing the performance of the method to be analysed under different climatic conditions. The combined use of the whole cumulative data (radar, optical and weather) improves the irrigated crop classifications (Overall Accuary (OA) ≈ 0.7) compared to the classifications obtained using each data separately (OA < 0.5). The use of monthly cumulative rainfall allows a significant improvement of the Fscore of irrigated and rainfed classes. Our study also reveals that the use of cumulative monthly indices leads to performances similar to those of the use of 10-day images while considerably reducing computational resources