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A Perspective on Gaussian Processes for Earth Observation

Gustau Camps-Valls, Dino Sejdinovic, Jakob Runge, Markus Reichstein
2019 National Science Review  
Earth observation (EO) by airborne and satellite remote sensing and in-situ observations play a fundamental role in monitoring our planet.  ...  In the last decade, machine learning and Gaussian processes (GPs) in particular has attained outstanding results in the estimation of bio-geo-physical variables from the acquired images at local and global  ...  in Earth observation.  ... 
doi:10.1093/nsr/nwz028 pmid:34691913 pmcid:PMC8291600 fatcat:o2hsdgspajb6hgak572nhb4ree

CCD-observations of asteroids: Accuracy and the nearest perspectives for application of the Laplacian orbit determination method

O.P. Bykov
1996 Symposium - International astronomical union  
They easily provide close positions on a short topocentric arc for any celestial body – from several hours during one night to several successive nights at a single observatory.  ...  topocentric angular acceleration and a curvature of visible trajectory of observed celestial body.  ...  Laplacian method can give good results in a direct processing of CCD observations immediately, during their execution on a telescope (for a circular orbit), or several days after (for an elliptical one  ... 
doi:10.1017/s0074180900127858 fatcat:zc4cslmaffgfndiqnb4hacc3si

Time-dependent tomography of hemispheric features using interplanetary scintillation (IPS) remote-sensing observations

B. V. Jackson
2003 AIP Conference Proceedings  
We check our results by comparison with additional remote-sensing observations, and observations from near-Earth spacecraft.  ...  The short time intervals of the kinematic modeling (~1 day) force the heliospheric reconstructions to depend on outward solar wind motion to give perspective views of each point in space accessible to  ...  Jackson, P.P Hick and A. Buffington was supported at the UCSD by AFOSR grant AF49620-01-1-0054, NSF grant ATM 98-199947 and NASA grant NAG5-8504.  ... 
doi:10.1063/1.1618545 fatcat:xfscsfliibcsdaxyq4rflnc2ue

Geological Objects and Physical Parameter Fields in the Subsurface: A Review [chapter]

Guillaume Caumon
2018 Handbook of Mathematical Geosciences  
Geologists and geophysicists often approach the study of the Earth using different and complementary perspectives.  ...  complex physical processes.  ...  contributions to such a stimulating research environment.  ... 
doi:10.1007/978-3-319-78999-6_28 fatcat:dnpfwczcmfhinnswcctizjnnua

Stochastic models for the Earth's relief, the shape and the fractal dimension of the coastlines, and the number-area rule for islands

B. B. Mandelbrot
1975 Proceedings of the National Academy of Sciences of the United States of America  
random surfaces/Gaussian processes) ABSTRACT The degree of irregularity in oceanic coastlines and in vertical sections of the Earth, the distribution of the numbers of islands according to area, and the  ...  The preferred parameter, one which increases with the degree of irregularity, is the fractal dimension, D, of the coastline; it is a fraction between 1 (limit of a smooth curve) and 2 (limit of a plane-filling  ...  simplest Gaussian process.  ... 
doi:10.1073/pnas.72.10.3825 pmid:16578734 pmcid:PMC433088 fatcat:lfzbonndb5gb5mn7zvvwnyfjum

Inferring causation from time series in Earth system sciences

Jakob Runge, Sebastian Bathiany, Erik Bollt, Gustau Camps-Valls, Dim Coumou, Ethan Deyle, Clark Glymour, Marlene Kretschmer, Miguel D. Mahecha, Jordi Muñoz-Marí, Egbert H. van Nes, Jonas Peters (+9 others)
2019 Nature Communications  
The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe.  ...  However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the commonly adopted correlation techniques.  ...  We also thank Veronika Eyring for helpful comments on the manuscript. We gratefully acknowledge the Netherlands Earth System Science Centre (NESSC) for funding this workshop.  ... 
doi:10.1038/s41467-019-10105-3 pmid:31201306 pmcid:PMC6572812 fatcat:ol37mo2dlvc3bkgri24wiwy2l4

System Identification with Student's t-Process Dynamical Model

Ayumu Nono, Yusuke Uchiyama
2021 Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications  
In this study, we propose a t-process dynamic estimation model, which is based on the t-distribution, and it is suggested that it is more robust than the Gaussian model.  ...  Knowing the exact location of a spacecraft is one of the most important tasks in the operation of a satellite.  ...  The random function ϕ(•) is a Gaussian process if for a set of input {x 1 , x 2 , • • •, x N } with arbitrary integer N the set of mapped values {ϕ(x 1 ), ϕ(x 2 ), • • •, ϕ(x N )} follow the Gaussian distribution  ... 
doi:10.5687/sss.2021.6 fatcat:jgfehnfidbgqzbnoe4ql2buhjq

An Automated Approach to Modeling Jupiter's Synchrotron Radiation from Radio Telescope Observations

Peyton Robertson, Connor Espenshade, Jay Sarva, Owen Dugan, Kalée Tock
2020 Astronomy: Theory, Observation and Methods  
Plotting Jupiter's flux against the longitude facing Earth at the time of each scan revealed a periodic relationship between the variables and thus a model for expected synchrotron flux from Jupiter observed  ...  We processed scans of Jupiter and calibrators taken by the Goldstone Apple Valley Radio Telescope on various dates, developing and automating algorithms for outlier removal, baseline subtraction, and Gaussian  ...  Velusamy Thangasamy for providing the GAVRT dataset and explaining his methods for processing it.  ... 
doi:10.32374/atom.2020.1.3 fatcat:r5ufnmhyxjcuvjqbvo5m6onbn4

Machine Learning for Robust Identification of Complex Nonlinear Dynamical Systems: Applications to Earth Systems Modeling [article]

Nishant Yadav, Sai Ravela, Auroop R. Ganguly
2020 arXiv   pre-print
Here we consider a chaotic system - two-level Lorenz-96 - used as a benchmark model in the climate science literature, adopt a methodology based on Gaussian Processes for parameter estimation and compare  ...  A crucial question for data scientists in this context is the relevance of state-of-the-art data-driven approaches including those based on deep neural networks or kernel-based processes.  ...  Gaussian Processes Definition 1: A Gaussian process is a collection of random variables, any finite number of which have a joint Gaussian distribution. [18] A Gaussian process (GP) is completely specified  ... 
arXiv:2008.05590v1 fatcat:l2gnge47hbgf3fi2i65xxapm5y

How Geoscientists Think and Learn

Kim A. Kastens, Cathryn A. Manduca, Cinzia Cervato, Robert Frodeman, Charles Goodwin, Lynn S. Liben, David W. Mogk, Timothy C. Spangler, Neil A. Stillings, Sarah Titus
2009 EOS  
This is Lamont-Doherty Earth Observatory contribution 7285.  ...  Acknowledgments In assembling this synthesis, we have drawn on conversations with dozens of colleagues and the writings of hundreds, as documented in the online supplement to this Eos issue (http:// www  ...  Geoscientists and geoscience educators have claimed, often passionately, that field-based learning helps students develop a feel for Earth processes and a sense of scale, and strengthens their ability  ... 
doi:10.1029/2009eo310001 fatcat:vj5f72bd6bgo7izmlnhbbciz7a

Decorrelation of GRACE Time Variable Gravity Field Solutions Using Full Covariance Information

Alexander Horvath, Michael Murböck, Roland Pail, Martin Horwath
2018 Geosciences  
Based on the simulation experience, a real data filtering procedure is designed and set up.  ...  The VADER filter is based on publicly available data that are provided by several GRACE processing centers, and does not need its own Level-2 processing chain.  ...  The input data for the observations are almost 12 years of 6 hour hydrological, ice, and solid earth signal (HIS) data from the ESA Earth system model [19] .  ... 
doi:10.3390/geosciences8090323 fatcat:mwmq7w6r4zbwpbcycylcj6ryyu

Compressive Earth observatory: An insight from AIRS/AMSU retrievals

Ardeshir M. Ebtehaj, Efi Foufoula-Georgiou, Gilad Lerman, Rafael L. Bras
2015 Geophysical Research Letters  
We illustrate this idea using retrieval products of the Atmospheric Infrared Sounder (AIRS) and Advanced Microwave Sounding Unit (AMSU) on board the Aqua satellite.  ...  We demonstrate that the global fields of temperature, humidity and geopotential heights admit a nearly sparse representation in the wavelet domain, offering a viable path forward to explore new paradigms  ...  now, at least from a hardware perspective.  ... 
doi:10.1002/2014gl062711 fatcat:jjcery7nbneanhu3dvhsbeixgi

GRACE detection of the medium- to far-field coseismic gravity changes caused by the 2004 MW9.3 Sumatra-Andaman earthquake

Jin Li, Wenbin Shen
2012 Earthquake Science  
Jing Hu for her valuable suggestions for improving the English writing in part of the original manuscript.  ...  Wenke Sun for providing us the software of the spherical dislocation model and the fault slip model of the 2004 Sumatra-Andaman earthquake. We are also grateful to Ms.  ...  to validating the spherical-Earth dislocation model in the medium field from the perspective of the time-variable satellite gravimetry.  ... 
doi:10.1007/s11589-012-0849-z fatcat:726u4kea7vannlw36ihfv52fby

Vision-based obstacle detection and grouping for helicopter guidance

Banavar Sridhar, Gano B. Chatterji
1994 Journal of Guidance Control and Dynamics  
Range Estimation Algorithm Consider a helicopter-mounted camera that observes a point P on a stationary object in the environment, as shown in Fig. 1.  ...  The grouping process involves the construction of a depth histogram and its approximation by a number of Gaussians. Grouping involves assigning the features to the groups defined by the Gaussians.  ... 
doi:10.2514/3.21289 fatcat:kwsojhfpfbditlho5rnexxwvim

Compressed sensing in astronomy and remote sensing: a data fusion perspective

J. Bobin, J.-L. Starck, Vivek K. Goyal, Manos Papadakis, Dimitri Van De Ville
2009 Wavelets XIII  
Recent advances in signal processing have focused on the use of sparse representations in various applications. A new field of interest based on sparsity has recently emerged : compressed sensing.  ...  This kind of CS data fusion concept led to an elegant and effective way to solve the problem ESA is faced with, for the transmission to the earth of the data collected by PACS, one of the instruments onboard  ...  A DATA FUSION PERSPECTIVE IN ASTRONOMY AND REMOTE SENSING In the wide field of remote sensing ranging from astronomical to earth survey, the observation of redundant data is common (just think of overcomplete  ... 
doi:10.1117/12.830633 fatcat:yahdttsmbfgipfwq46dah7htnq
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