20 papers · ranked by Valyu relevance
John R. Giles, Derek A. T. Cummings, Bryan T. Grenfell, Andrew J. Tatem + 4 more
'Andrew J. Tatem' 'Elisabeth zu Erbach-Schoenberg' 'CJE Metcalf' 'Amy Wesolowski' 'Alex Perkins'] Human travel is one of the primary drivers of infectious disease spread. Models of travel are often used that assume the amount of travel to a specific destination decreases as cost of travel increases with higher travel…
Wieger H. Scheurer, Micha Heilbron
Prediction is foundational to theories of perceptual processing and learning, in both neuroscience and AI. However, it remains unclear whether prediction occurs routinely during naturalistic perception, and at what level of abstraction the brain predicts. Here, we address both questions by analysing 7T fMRI recordings…
Kamil Smolak, Katarzyna Siła-Nowicka, Jean-Charles Delvenne, Michał Wierzbiński + 1 more
'Michał Wierzbiński' 'Witold Rohm'] Predictability of human movement is a theoretical upper bound for the accuracy of movement prediction models, which serves as a reference value showing how regular a dataset is and to what extent mobility can be predicted. Over the years, the predictability of various human mobility…
Diogo Pacheco, Marcos Oliveira, Zexun Chen, Hugo Barbosa + 3 more
'Brooke Foucault Welles' 'Gourab Ghoshal' 'Ronaldo Menezes'] Human travelling behaviours are markedly regular, to a large extent, predictable, and mostly driven by biological necessities (e.g. sleeping, eating) and social constructs (e.g. school schedules, synchronisation of labour). Not surprisingly, such…
Akihiko Mougi
The prediction of an ecosystem’s response to an environmental disturbance or the artificial control of ecosystems is a challenging task in ecology. Ecological theory predicts that disturbances frequently result in unexpected responses between interacting species due to the many indirect interactions within a complex…
En Xu, Yilin Bi, Hongwei Hu, Xin Chen + 4 more
a Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China b CompleX Lab, University of Electronic Science and Technology of China, Chengdu, 611731, China c Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China d School of Computer…
Peng Luo, Yongze Song, Wenwen Li, Lingsheng Meng
Understanding the complex nature of spatial information is crucial for problem solving in social and environmental sciences. This study investigates how the underlying patterns of spatial data can significantly influence the outcomes of spatial predictions. Recognizing unique characteristics of spatial data, such as…
Zhe Jiang
—With the advancement of GPS and remote sensing technologies, large amounts of geospatial and spatiotemporal data are being collected from various domains, driving the need for effective and efficient prediction methods. Given spatial data samples with explanatory features and targeted responses (categorical or…
Edin Lind Ikanovic, Anders Mollgaard
Next place prediction algorithms are invaluable tools, capable of increasing the efficiency of a wide variety of tasks, ranging from reducing the spreading of diseases to better resource management in areas such as urban planning. In this work we estimate upper and lower limits on the predictability of human mobility…
Bibandhan Poudyal, Diogo Pacheco, Marcos Oliveira, Zexun Chen + 3 more
mobility Dynamic predictability and activity-location contexts in human mobility Authors: Bibandhan Poudyal, Diogo Pacheco, Marcos Oliveira, Zexun Chen, Hugo S. Barbosa, Ronaldo Menezes, Gourab Ghoshal Human travelling behaviours are markedly regular, to a large extent predictable, and mostly driven by biological…
Song Qi, Logan Cross, Toby Wise, Xin Sui + 2 more
Humans, like many other animals, pre-empt danger by moving to locations that maximize their success at escaping future threats. We test the idea that spatial margin of safety (MOS) decisions, a form of pre-emptive avoidance, results in participants placing themselves closer to safer locations when facing more…
Johan van den Hoogen, Niamh Robmann, Devin Routh, Thomas Lauber + 3 more
Geospatial modelling can give fundamental insights in the biogeography of life, providing key information about the living world in current and future climate scenarios. Emerging statistical and machine learning approaches can help us to generate new levels of predictive accuracy in exploring the spatial patterns in…
Martin Jung
Biodiversity varies in space and time, and often in response to environmental heterogeneity. Indicators in the form of local biodiversity measures – such as species richness or abundance – are common tools to capture this variation. The rise of readily available remote sensing data has enabled the characterization of…
Mortier Frederik, Masier Stefano, Bonte Dries
Fragmentation of natural landscapes results in habitat and connectedness loss, making it one of the most impactful avenues of anthropogenic environmental degradation. Populations living in a fragmented landscape can adapt to this context, as witnessed in changing dispersal strategies, levels of local adaptation and…
Benoît Pichon, Sophie Donnet, Isabelle Gounand, Sonia Kéfi
Resource-limited ecosystems, such as drylands, can exhibit self-organized spatial patterns. Theory suggests that these patterns can reflect increasing degradation levels as ecosystems approach possible tipping points to degradation. However, we still lack ways of estimating a distance to degradation points that is…
Lluis Franch-Gras, Eduardo Moisés García-Roger, Belen Franch, María José Carmona + 2 more
'María José Carmona' 'Manuel Serra' 'Christopher D. Lippitt'] Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the…
Authors not listed
Gibbs’ paradox—the apparent discontinuity in mixing entropy for gases of varying similarity and the seeming reversibility of mixing-separation cycles—has resisted fully satisfactory resolution for 150 years. We present a solution based on categorical state theory, which posits that physical con f igurations are…
Ling Huang, Shannon Stokes, Qining Chen, Felipe Cardoso-Saldaña + 1 more
Total column loadings of methane measured by satellites are increasingly used to estimate methane emission rates, using inversion calculations. Forward calculations of methane column loadings, based on detailed emission inventories at fine spatial resolution, coupled with fine spatial scale gridded chemical transport…
Mei Tessum, Susan Anenberg, Zoe Chafe, Daven Henze + 4 more
To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside…
Sarah Chambliss, Carlos Pinon, Kyle Messier, Brian LaFranchi + 5 more
Disparity in air pollution exposure arises from variation at multiple spatial scales: along urbanto-rural gradients, between individual cities within a metropolitan region, within individual neighborhoods, and between city blocks. Here, we improve on existing capabilities to systematically compare urban variation at…