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A second horizon scan of biogeography: Golden Ages, Midas touches, and the Red Queen

Michael N Dawson, Jan C. Axmacher, Carl Beierkuhnlein, Jessica L. Blois, Bethany A. Bradley, Anna F. Cord, Jürgen Dengler, Kate S. He, Lawrence R. Heaney, Roland Jansson, Miguel D. Mahecha, Corinne Myers (+8 others)
2016 Frontiers of Biogeography  
Acknowledgements: We thank speakers and poster presenters in all sessions and the IBS conference committee for their support in making available the text of submitted abstracts.  ...  Robert Colwell and Jack Williams reviewed and improved the manuscript. We thank the following sources for funding that supported  ...  Acknowledgements: We thank speakers and poster presenters in all sessions and the IBS conference committee for their support in making available the text of submitted abstracts.  ... 
doi:10.21425/f58429770 fatcat:h3axjzvfsnex3ayxcw2bwmvfxy

Potential and Challenges of Harmonizing 40 Years of AVHRR Data: The TIMELINE Experience

Stefan Dech, Stefanie Holzwarth, Sarah Asam, Thorsten Andresen, Martin Bachmann, Martin Boettcher, Andreas Dietz, Christina Eisfelder, Corinne Frey, Gerhard Gesell, Ursula Gessner, Andreas Hirner (+17 others)
2021 Remote Sensing  
The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous.  ...  The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.  ...  Conflicts of Interest: The authors declare no conflict of interest. Remote Sens. 2021, 13, 3618  ... 
doi:10.3390/rs13183618 fatcat:lynncr3n75gjhia5vzvlotxgeu

Reef-Scale Thermal Stress Monitoring of Coral Ecosystems: New 5-km Global Products from NOAA Coral Reef Watch

Gang Liu, Scott Heron, C. Eakin, Frank Muller-Karger, Maria Vega-Rodriguez, Liane Guild, Jacqueline De La Cour, Erick Geiger, William Skirving, Timothy Burgess, Alan Strong, Andy Harris (+5 others)
2014 Remote Sensing  
The new products increase near-shore coverage and now allow direct monitoring of 95% of coral reefs and significantly reduce data gaps caused by cloud cover.  ...  National Oceanic and Atmospheric Administration (NOAA) Coral Reef Watch (CRW) program has developed a daily global 5-km product suite based on satellite observations to monitor thermal stress on coral  ...  This preserves mathematical rigor and fine detail, while filling gaps for any regions with no satellite observations due to cloud cover or other contamination.  ... 
doi:10.3390/rs61111579 fatcat:3zukp4ckszghrmp2jddxog4zfy

Fusing optical and SAR time series for LAI gap fillingwith multioutput Gaussian processes

Luca Pipia, Jordi Muñoz-Marí, Eatidal Amin, Santiago Belda, Gustau Camps-Valls, Jochem Verrelst
2019 Remote Sensing of Environment  
The leave-one-image-out assessment technique applied to the whole vegetation cover shows MOGP predictions improve standard GP estimations over short-time gaps (R^2 of 74% vs 68%, RMSE of 0.4 vs 0.44 [m  ...  The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications.  ...  Figure 1 : 1 Horizon 2020 Research and Innovation Programme, under Grant Agreement no 730074.  ... 
doi:10.1016/j.rse.2019.111452 fatcat:gxuzwj46uve5rc6aeifpx75fu4

The State-of-the-Art Progress in Cloud Detection, Identification, and Tracking Approaches: A Systematic Review

Manisha Sawant, Mayur Kishor Shende, Andrés E. Feijóo-Lorenzo, Neeraj Dhanraj Bokde
2021 Energies  
Regarding cloud detection, dealt with in a second part, diverse methods have been analyzed, i.e., those based on the analysis of satellite images and those based on the analysis of images from cameras  ...  The first one is devoted to the analysis and explanation of clouds and their types, and about existing imaging systems.  ...  The forecasting gap of satellite imagery is filled by sky imagers mounted on the ground.  ... 
doi:10.3390/en14238119 fatcat:7b3lwmxhnfg5jikfcastns5oqm

An Integrated Multi-Time-Scale Modeling for Solar Irradiance Forecasting Using Deep Learning [article]

Sakshi Mishra, Praveen Palanisamy
2019 arXiv   pre-print
Additionally, the proposed method enables multi-time-horizon forecasts with real-time inputs, which have a significant potential for practical industry applications in the evolving grid.  ...  Our proposed method results in a 71.5% reduction in the mean RMSE averaged across all the test sites compared to the ML-based best-performing method reported in the literature.  ...  The time evolution of the air mass is analyzed using images from a satellite, by superimposing images of the same area.  ... 
arXiv:1905.02616v2 fatcat:etporntk3rd67o3kapdchpci74

Toward Seamless Multiview Scene Analysis From Satellite to Street Level

Sebastien Lefevre, Devis Tuia, Jan Dirk Wegner, Timothee Produit, Ahmed Samy Nassar
2017 Proceedings of the IEEE  
Direct (dense) matching of images on a per-pixel basis is thus often impossible, and one has to resort to alternative strategies that will be discussed in this paper.  ...  In this paper, we discuss and review how combined multi-view imagery from satellite to street-level can benefit scene analysis.  ...  of GPS images with horizon and textured model matching: the orientation of the GPS images was tested on a set of images in the Swiss Alps acquired by the authors.  ... 
doi:10.1109/jproc.2017.2684300 fatcat:r3hyfdtjzzaknl25cpygxrcgq4

A Flexible and Robust Deep Learning-Based System for Solar Irradiance Forecasting

Ignacio-Iker Prado-Rujas, Antonio Garcia-Dopico, Emilio Serrano, Maria S. Perez
2021 IEEE Access  
and horizon) compared to the baseline.  ...  Experiments carried out show that sensor failures have a mild impact on the prediction error for several forecast horizons.  ...  ACKNOWLEDGMENT The authors would like to thank María-Luisa Córdoba for her support and numerous comments during the development of this work.  ... 
doi:10.1109/access.2021.3051839 fatcat:dfbg6jgq6bezrboagyebwx26ja

Short-Term River Flood Forecasting Using Composite Models and Automated Machine Learning: The Case Study of Lena River

Mikhail Sarafanov, Yulia Borisova, Mikhail Maslyaev, Ilia Revin, Gleb Maximov, Nikolay O. Nikitin
2021 Water  
To improve the forecasting efficiency, the machine learning methods and the Snowmelt-Runoff physical model are combined in a composite modeling pipeline using automated machine learning techniques.  ...  The other approaches based on statistical and physical models could not surpass the threshold of 0.74.  ...  Imaging Spectroradiometer (MODIS) satellite imagery.  ... 
doi:10.3390/w13243482 fatcat:qnv73tm2azbchno2wdijahz4bu

Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints

Yuan-Kang Wu, Cheng-Liang Huang, Quoc-Thang Phan, Yuan-Yao Li
2022 Energies  
Probabilistic forecasting is expected to play a key role in the PV power forecasting required to meet the challenges faced by modern grid systems, and so this study provides a comparative analysis of existing  ...  on existing power systems.  ...  Conflicts of Interest: The authors declare no competing financial interests.  ... 
doi:10.3390/en15093320 fatcat:cvvedbxhtvajzi5ibqoglb6oqy

Half a century of satellite remote sensing of sea-surface temperature

P.J. Minnett, A. Alvera-Azcárate, T.M. Chin, G.K. Corlett, C.L. Gentemann, I. Karagali, X. Li, A. Marsouin, S. Marullo, E. Maturi, R. Santoleri, S. Saux Picart (+2 others)
2019 Remote Sensing of Environment  
Sea-surface temperature (SST) was one of the first ocean variables to be studied from earth observation satellites.  ...  Since then, SST has been derived from infrared and microwave radiometers on polar orbiting satellites and from infrared radiometers on geostationary spacecraft.  ...  Merchant for providing a preprint of the paper (Merchant et al., 2019) to support the description (in Section 5.1.2) of the generation of the AVHRR time series of consistent SSTs.  ... 
doi:10.1016/j.rse.2019.111366 fatcat:6bkbqmedx5bjtmvw2kkjnq3xnm

Environmental control of natural gap size distribution in tropical forests

Youven Goulamoussène, Caroline Bedeau, Laurent Descroix, Laurent Linguet, Bruno Hérault
2017 Biogeosciences  
In the future, we plan to apply our methodological framework on a larger scale using satellite data.  ...  Monitoring the size distribution of treefall gaps is important to better understand and predict the carbon budget in response to land use and other global changes.  ...  We thank the handling editor, Ervan Rutishauser and Marijn Bauters for their thoughtful comments on a previous version of this paper.  ... 
doi:10.5194/bg-14-353-2017 fatcat:nuamrhhn5rcazh3bme6y4h6yxe

Environmental control of natural gap size distribution in tropical forests

Youven Goulamoussène, Caroline Bedeau, Laurent Descroix, Laurent Linguet, Bruno Hérault
2016 Biogeosciences Discussions  
In the future, we plan scale up testing of our methodology using satellite data.  ...  We highlight strong links between gap size distribution and environment, primarily hydrological conditions and topography, with large gaps being more frequent in floodplains and on hillslopes.  ...  We thank the handling editor, Ervan Rutishauser and Marijn Bauters for their thoughtful comments on a previous version of this paper.  ... 
doi:10.5194/bg-2016-320 fatcat:iv63ub4qgnfn5h3ad2xplf2tne

Stability of the Malvinas Current [article]

FJ Beron-Vera, N. Bodnariuk, M. Saraceno, MJ Olascoaga, C Simionato
2019 arXiv   pre-print
The probabilistic tools are applied on a large collection of historical satellite-tracked drifter trajectories, revealing weakly communicating flow regions on either side of the altimetry-derived barrier  ...  The deterministic tools are applied on a multi-year record of velocities derived from satellite altimetry data, revealing a resilient cross-stream transport barrier.  ...  Figure 2 shows a satellite-derived ocean pseudo-true color image on t 0 = 12 Dec 2001 with the extracted shearless-parabolic LCS overlaid.  ... 
arXiv:1901.07109v1 fatcat:lceilyzoszfszmtotijr753rwu

Maximal Coordinate Discrepancy as Accuracy Criterion of Image Projective Normalization for Optical Recognition of Documents

I.A. Konovalenko, Institute for Information Transmission Problems of the RAS, V.V. Kokhan, D.P. Nikolaev, Institute for Information Transmission Problems of the RAS, Institute for Information Transmission Problems of the RAS
2020 Bulletin of the South Ural State University Series Mathematical Modelling Programming and Computer Software  
For this model, we prove that the image normalization accuracy criterion, which is equal to the maximal coordinate discrepancy in the text fields of a document, monotonously depends on the probability  ...  In this paper, for the case of a fixed structured document, we justify a uniform probabilistic model of recognition errors, according to which the probability of correct recognition of a character abruptly  ...  The study was carried out with the partial financial support of RFBR within scientific projects no. 17-29-03370 and no. 17-29-03514.  ... 
doi:10.14529/mmp200304 fatcat:e573smxx25he5otykalbbzmf4i
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