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Keywords = flower constellation

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12 pages, 231 KB  
Article
Nicolas Poussin’s Realm of Flora: The Botanical Renaissance and the Mysteries of the Flower, Sign, Circle and Ellipse
by Frederick A. De Armas
Arts 2026, 15(2), 36; https://doi.org/10.3390/arts15020036 - 6 Feb 2026
Viewed by 1781
Abstract
In spite of the preeminence of Nicolas Poussin as one of the great classicist painters in seventeenth century France, some of his earlier work has not received the attention it deserves. This article turns to his Realm of Flora (c. 1631) in order [...] Read more.
In spite of the preeminence of Nicolas Poussin as one of the great classicist painters in seventeenth century France, some of his earlier work has not received the attention it deserves. This article turns to his Realm of Flora (c. 1631) in order to study some salient aspects that have been neglected. First, Poussin followed what I call the “Botanical Renaissance.” This study foregrounds which elements he followed and which he transformed. In conjunction with this movement, this article highlights Poussin’s uses of Platonic philosophy through the works of Marsilio Ficino. The importance of Sol in his works is replicated here in the power of the solar rays to nourish nature. Thirdly, we consider the many metamorphoses in the work and their significance. Finally, we turn to the circle in the heavens with the planets, stars and twelve constellations and contrast it with the more elongated circle of the metamorphic figures on Earth in order to highlight the relation between zodiacal signs/stars and the flowers depicted. The circular constellations contrast with an elongated, even elliptical shape of the figures on Earth, perhaps to suggest the conflict, prevalent at the time, between the Copernican heliocentric and circular system with Kepler’s elliptical view of the path of the heavenly planets. Full article
(This article belongs to the Special Issue Myths in Art, XV–XVII Centuries)
31 pages, 24798 KB  
Article
A Study of Cislunar-Based Small Satellite Constellations with Sustainable Autonomy
by Mohammed Irfan Rashed and Hyochoong Bang
Aerospace 2024, 11(9), 787; https://doi.org/10.3390/aerospace11090787 - 23 Sep 2024
Viewed by 3036
Abstract
The Cislunar economy is thriving with innovative space systems and operation techniques to enhance and uplift the traditional approaches significantly. This paper brings about an approach for sustainable small satellite constellations to retain autonomy for long-term missions in the Cislunar space. The methodology [...] Read more.
The Cislunar economy is thriving with innovative space systems and operation techniques to enhance and uplift the traditional approaches significantly. This paper brings about an approach for sustainable small satellite constellations to retain autonomy for long-term missions in the Cislunar space. The methodology presented is to align the hybrid model of the constellation for Earth and Moon as an integral portion of the Cislunar operations. These hybrid constellations can provide a breakthrough in optimally utilizing the Cislunar space to efficiently deploy prominent missions to be operated and avoid conjunction or collisions forming additional debris. Flower and walker constellation patterns have been combined to form a well-defined orientation for these small satellites to operate and deliver the tasks satisfying the mission objectives. The autonomous multi-parametric analysis for each constellation based in Earth and Moon’s environment has been attained with due consideration to local environments. Specifically, the Solar Radiation Pressure (SRP) is a critical constraint in Cislunar operations and is observed during simulations. These are supported by conjunction analysis using the Monte Carlo technique and also the effect of the SRP on the operating small satellites in real-time scenarios. This is followed by the observed conclusions and the way forward in this fiercely competent Cislunar operation. Full article
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19 pages, 7953 KB  
Article
Crop Phenology Modelling Using Proximal and Satellite Sensor Data
by Anne Gobin, Abdoul-Hamid Mohamed Sallah, Yannick Curnel, Cindy Delvoye, Marie Weiss, Joost Wellens, Isabelle Piccard, Viviane Planchon, Bernard Tychon, Jean-Pierre Goffart and Pierre Defourny
Remote Sens. 2023, 15(8), 2090; https://doi.org/10.3390/rs15082090 - 15 Apr 2023
Cited by 36 | Viewed by 6623
Abstract
Understanding crop phenology is crucial for predicting crop yields and identifying potential risks to food security. The objective was to investigate the effectiveness of satellite sensor data, compared to field observations and proximal sensing, in detecting crop phenological stages. Time series data from [...] Read more.
Understanding crop phenology is crucial for predicting crop yields and identifying potential risks to food security. The objective was to investigate the effectiveness of satellite sensor data, compared to field observations and proximal sensing, in detecting crop phenological stages. Time series data from 122 winter wheat, 99 silage maize, and 77 late potato fields were analyzed during 2015–2017. The spectral signals derived from Digital Hemispherical Photographs (DHP), Disaster Monitoring Constellation (DMC), and Sentinel-2 (S2) were crop-specific and sensor-independent. Models fitted to sensor-derived fAPAR (fraction of absorbed photosynthetically active radiation) demonstrated a higher goodness of fit as compared to fCover (fraction of vegetation cover), with the best model fits obtained for maize, followed by wheat and potato. S2-derived fAPAR showed decreasing variability as the growing season progressed. The use of a double sigmoid model fit allowed defining inflection points corresponding to stem elongation (upward sigmoid) and senescence (downward sigmoid), while the upward endpoint corresponded to canopy closure and the maximum values to flowering and fruit development. Furthermore, increasing the frequency of sensor revisits is beneficial for detecting short-duration crop phenological stages. The results have implications for data assimilation to improve crop yield forecasting and agri-environmental modeling. Full article
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12 pages, 3165 KB  
Article
On the Constellation Design of Multi-GNSS Reflectometry Mission Using the Particle Swarm Optimization Algorithm
by Yi Han, Jia Luo and Xiaohua Xu
Atmosphere 2019, 10(12), 807; https://doi.org/10.3390/atmos10120807 - 13 Dec 2019
Cited by 12 | Viewed by 4544
Abstract
Due to the great success of the CYclone Global Navigation Satellite System (CYGNSS) mission, the follow-on GNSS Reflectometry (GNSS-R) missions are being planned. In the perceivable future, signal sources for GNSS-R missions can originate from multiple global navigation satellite systems (GNSSs) including Global [...] Read more.
Due to the great success of the CYclone Global Navigation Satellite System (CYGNSS) mission, the follow-on GNSS Reflectometry (GNSS-R) missions are being planned. In the perceivable future, signal sources for GNSS-R missions can originate from multiple global navigation satellite systems (GNSSs) including Global Positioning System (GPS), Galileo, GLONASS, and BeiDou. On the other hand, to facilitate the operational capability for sensing ocean, land, and ice features globally, multi-satellite low Earth orbit (LEO) constellations with global coverage and high spatio-temporal resolutions should be considered in the design of the follow-on GNSS-R constellation. In the present study, the particle swarm optimization (PSO) algorithm was applied to seek the optimal configuration parameters of 2D-lattice flower constellations (2D-LFCs) composed of 8, 24, 60, and 120 satellites, respectively, for global GNSS-R observations, and the fitness function was defined as the length of the time for the percentage coverage of the reflection observations reaches 90% of the globe. The configuration parameters for the optimal constellations are presented, and the performances of the optimal constellations for GNSS-R observations including the visited and the revisited coverages, and the spatial and temporal distributions of the reflections were further compared. Although the results showed that all four optimized constellations could observe GNSS reflections with proper temporal and spatial distributions, we recommend the optimal 24- and 60-satellite 2D-LFCs for future GNSS-R missions, taking into account both the performance and efficiency for the deployment of the GNSS-R missions. Full article
(This article belongs to the Special Issue GNSS Meteorology and Climatology)
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17 pages, 5050 KB  
Article
Seeking Optimal GNSS Radio Occultation Constellations Using Evolutionary Algorithms
by Xiaohua Xu, Yi Han, Jia Luo, Jens Wickert and Milad Asgarimehr
Remote Sens. 2019, 11(5), 571; https://doi.org/10.3390/rs11050571 - 8 Mar 2019
Cited by 14 | Viewed by 5640
Abstract
Given the great achievements of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission in providing huge amount of GPS radio occultation (RO) data for weather forecasting, climate research, and ionosphere monitoring, further Global Navigation Satellite System (GNSS) RO missions are [...] Read more.
Given the great achievements of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission in providing huge amount of GPS radio occultation (RO) data for weather forecasting, climate research, and ionosphere monitoring, further Global Navigation Satellite System (GNSS) RO missions are being followingly planned. Higher spatial and also temporal sampling rates of RO observations, achievable with higher number of GNSS/receiver satellites or optimization of the Low Earth Orbit (LEO) constellation, are being studied by high number of researches. The objective of this study is to design GNSS RO missions which provide multi-GNSS RO events (ROEs) with the optimal performance over the globe. The navigation signals from GPS, GLONASS, BDS, Galileo, and QZSS are exploited and two constellation patterns, the 2D-lattice flower constellation (2D-LFC) and the 3D-lattice flower constellation (3D-LFC), are used to develop the LEO constellations. To be more specific, two evolutionary algorithms, including the genetic algorithm (GA) and the particle swarm optimization (PSO) algorithm, are used for searching the optimal constellation parameters. The fitness function of the evolutionary algorithms takes into account the spatio-temporal sampling rate. The optimal RO constellations are obtained for which consisting of 6–12 LEO satellites. The optimality of the LEO constellations is evaluated in terms of the number of global ROEs observed during 24 h and the coefficient value of variation (COV) representing the uniformity of the point-to-point distributions of ROEs. It is found that for a certain number of LEO satellites, the PSO algorithm generally performs better than the GA, and the optimal 2D-LFC generally outperforms the optimal 3D-LFC with respect to the uniformity of the spatial and temporal distributions of ROEs. Full article
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