Search results for "Planetary Science"
showing 10 items of 4367 documents
Dynamics of asteroid systems post-rotational fission
2022
Asteroid binaries found amongst the Near-Earth objects are believed to have formed from rotational fission. In this paper, we aim to study the dynamical evolution of asteroid systems the moment after fission. The initial condition is modelled as a contact binary, similar to that of Boldrin et al. (2016). Both bodies are modelled as ellipsoids, and the secondary is given an initial rotation angle about its body-fixed $y$-axis. Moreover, we consider six different cases, three where the density of the secondary varies, and three where we vary its shape. The simulations consider 45 different initial tilt angles of the secondary, each with 37 different mass ratios. We start the dynamical simulat…
A similar to 32-70 K FORMATION TEMPERATURE RANGE FOR THE ICE GRAINS AGGLOMERATED BY COMET 67 P/CHURYUMOV-GERASIMENKO
2015
Grand Canonical Monte Carlo simulations are used to reproduce the N$_2$/CO ratio ranging between 1.7 $\times$ 10$^{-3}$ and 1.6 $\times$ 10$^{-2}$ observed {\it in situ} in the Jupiter family comet 67P/Churyumov-Gerasimenko by the ROSINA mass spectrometer aboard the Rosetta spacecraft, assuming that this body has been agglomerated from clathrates in the protosolar nebula. Simulations are done using an elaborated interatomic potentials for investigating the temperature dependence of the trapping within a multiple guest clathrate formed from a gas mixture of CO and N$_2$ in proportions corresponding to those expected for the protosolar nebula. By assuming that 67P/Churyumov-Gerasimenko agglom…
Analysis of the planetary mass uncertainties on the accuracy of atmospherical retrieval
2023
Characterising the properties of exoplanet atmospheres relies on several interconnected parameters, which makes it difficult to determine them independently. Planetary mass plays a role in determining the scale height of atmospheres, similarly to the contribution from the average molecular weight of the gas. We investigate the relevance of planetary mass knowledge in spectral retrievals, identifying cases where mass measurements are needed for clear or cloudy and primary or secondary atmospheres, along with the relevant precision, in the context of the ESA M4 Ariel Mission. We used TauREx to simulate the Ariel transmission spectra of representative targets of the Ariel mission reference sam…
Special Section Guest Editorial: Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation
2018
This special section focuses on the use of remote sensing tools in some of these areas, including monitoring the volume and turbidity in lake fresh water resources, retrieving soil organic matter from spectral information with particular attention to abandoned croplands and areas affected by wildfires, and identification and monitoring of natural and agricultural vegetation through emerging techniques such as shallow and deep learning algorithms. These data mining and analysis approaches are particularly promising and include convolutional neural network and the application of back propagation neural network algorithms for soil water content monitoring and the extraction of other canopy inf…
A Survey of Active Learning for Quantifying Vegetation Traits from Terrestrial Earth Observation Data
2021
The current exponential increase of spatiotemporally explicit data streams from satellite-based Earth observation missions offers promising opportunities for global vegetation monitoring. Intelligent sampling through active learning (AL) heuristics provides a pathway for fast inference of essential vegetation variables by means of hybrid retrieval approaches, i.e., machine learning regression algorithms trained by radiative transfer model (RTM) simulations. In this study we summarize AL theory and perform a brief systematic literature survey about AL heuristics used in the context of Earth observation regression problems over terrestrial targets. Across all relevant studies it appeared that…
Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform
2021
Vegetation Types (VTs) are important managerial units, and their identification serves as essential tools for the conservation of land covers. Despite a long history of Earth observation applications to assess and monitor land covers, the quantitative detection of sparse VTs remains problematic, especially in arid and semiarid areas. This research aimed to identify appropriate multi-temporal datasets to improve the accuracy of VTs classification in a heterogeneous landscape in Central Zagros, Iran. To do so, first the Normalized Difference Vegetation Index (NDVI) temporal profile of each VT was identified in the study area for the period of 2018, 2019, and 2020. This data revealed strong se…
A Survey on Gaussian Processes for Earth-Observation Data Analysis: A Comprehensive Investigation
2016
Gaussian processes (GPs) have experienced tremendous success in biogeophysical parameter retrieval in the last few years. GPs constitute a solid Bayesian framework to consistently formulate many function approximation problems. This article reviews the main theoretical GP developments in the field, considering new algorithms that respect signal and noise characteristics, extract knowledge via automatic relevance kernels to yield feature rankings automatically, and allow applicability of associated uncertainty intervals to transport GP models in space and time that can be used to uncover causal relations between variables and can encode physically meaningful prior knowledge via radiative tra…
Clasificación de usos del suelo a partir de imágenes Sentinel-2
2017
[EN] Sentinel-2 (S2), a new ESA satellite for Earth observation, accounts with 13 bands which provide high-quality radiometric images with an excellent spatial resolution (10 and 20 m) ideal for classification purposes. In this paper, two objectives have been addressed: to determine the best classification method for S2, and to quantify its improve-ment with respect to the SPOT operational mission. To do so, four classifiers (LDA, RF, Decision Trees, K-NN) have been selected and applied to two different agricultural areas located in Valencia (Spain) and Buenos Aires (Argentina). All classifiers were tested using, on the one hand, all the S2 bands and, on the other hand, only selecting those…
A Critical Comparison of Remote Sensing Leaf Area Index Estimates over Rice-Cultivated Areas: From Sentinel-2 and Landsat-7/8 to MODIS, GEOV1 and EUM…
2018
Leaf area index (LAI) is a key biophysical variable fundamental in natural vegetation and agricultural land monitoring and modelling studies. This paper is aimed at comparing, validating and discussing different LAI satellite products from operational services and customized solution based on innovative Earth Observation (EO) data such as Landsat-7/8 and Sentinel-2A. The comparison was performed to assess overall quality of LAI estimates for rice, as a fundamental input of different scale (regional to local) operational crop monitoring systems such as the ones developed during the "An Earth obseRvation Model based RicE information Service" (ERMES) project. We adopted a multiscale approach f…
Data service platform for sentinel-2 surface reflectance and value-added products: System use and examples
2016
This technical note presents the first Sentinel-2 data service platform for obtaining atmospherically-corrected images and generating the corresponding value-added products for any land surface on Earth (http://s2.boku.eodc.eu/). Using the European Space Agency’s (ESA) Sen2Cor algorithm, the platform processes ESA’s Level-1C top-of-atmosphere reflectance to atmospherically-corrected bottom-of-atmosphere (BoA) reflectance (Level-2A). The processing runs on-demand, with a global coverage, on the Earth Observation Data Centre (EODC), which is a public-private collaborative IT infrastructure in Vienna (Austria) for archiving, processing, and distributing Earth observation (EO) data (http://www.…