Article
Environmental Sciences
Qunming Wang, Xinyu Ding, Xiaohua Tong, Peter M. Atkinson
Summary: The study introduces a spatio-temporal spectral unmixing (STSU) approach, which extends spectral unmixing into the spatio-temporal domain to obtain more reliable land cover information. This method does not require pure endmember extraction and directly uses extracted mixed training samples to construct a learning model, making it suitable for dynamic monitoring of land cover changes.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Computer Science, Software Engineering
Marina Evers, Karim Huesmann, Lars Linsen
Summary: The paper proposes a two-step procedure for visual analysis of correlations between different spatial regions. The first step involves mapping spatial samples to a 3D embedding based on a pairwise correlation matrix computed from the time series ensemble. The second step generates a hierarchical image segmentation based on color images, enabling visual analysis of region correlations at all levels.
COMPUTER GRAPHICS FORUM
(2021)
Article
Engineering, Electrical & Electronic
Meiqin Che, Anna Vizziello, Paolo Gamba
Summary: The aim of this work is to automatically extract and recognize urban change time series in sequences of SAR data. By combining SAR time-series segmentation and unsupervised classification, areas with the same urban change pattern can be identified. Experimental results show that the proposed approach is effective in characterizing temporal patterns of different types of intraurban changes.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Physics, Multidisciplinary
Zhuo-Lin Li, Jie Yu, Xiao-Lin Zhang, Ling-Yu Xu, Bao-Gang Jin
Summary: This paper proposes a multi-hierarchical attention network for multi-scale prediction of multivariate time series in Earth system science, which effectively captures correlations between different spacetime variables and demonstrates its effectiveness and robustness on real-world datasets.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Patricia Maldonado-Salguero, Maria Carmen Bueso-Sanchez, Angel Molina-Garcia, Juan Miguel Sanchez-Lozano
Summary: This study proposes a methodology to characterize and cluster spatio-temporal solar resource variability through global horizontal irradiance analysis. The study selected Spain as a case study and evaluated spatial variability and geographical clustering differences of solar resources in different time windows. The research findings contribute to understanding the spatiotemporal variations of solar resources in Spain.
Article
Computer Science, Artificial Intelligence
Yuteng Xiao, Hongsheng Yin, Yudong Zhang, Honggang Qi, Yundong Zhang, Zhaoyang Liu
Summary: The study introduces a convolutional LSTM network model with two-stage attention for multivariate time series prediction, effectively addressing the issue of insufficient time dependency in MTS prediction. The model improves prediction accuracy by extracting spatio-temporal correlations of MTS and utilizing attention mechanism, showing promising application prospects.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Jiaxun Chen, Athanasios C. Micheas, Scott H. Holan
Summary: This study introduces a flexible spatio-temporal area-interaction point process model for spatial point patterns with discrete time stamps, which is suitable for describing the dependency between point patterns over time. A hierarchical model is implemented to incorporate the underlying evolution process of model parameters, and a double Metropolis-Hastings within Gibbs sampler is used for parameter estimation. The performance of the estimation algorithm is evaluated through simulation studies.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2022)
Article
Green & Sustainable Science & Technology
Carlos A. Severiano, Petronio Candido de Lima e Silva, Miri Weiss Cohen, Frederico Gadelha Guimaraes
Summary: This study introduces an evolving forecasting model e-MVFTS based on fuzzy time series and an evolving clustering method based on the TEDA framework for forecasting problems in renewable energy systems. Evaluations were conducted on solar and wind energy forecasting as well as concept drift events.
Article
Environmental Sciences
Huijin Yang, Heping Li, Wei Wang, Ning Li, Jianhui Zhao, Bin Pan
Summary: This study aimed to estimate the spatio-temporal distribution of rice height using time series Sentinel-1A images. VH backscatter was found to be potentially accurate for estimating rice height compared to VV backscatter, the VH backscatter to VV backscatter ratio, and the Radar Vegetation Index. The particle filter method generated better results compared to the simplified water cloud model, with higher rice height in the south and east compared to the north and west.
Article
Engineering, Civil
Luigi Barazzetti
Summary: The paper discusses the importance of S-T analysis in structural monitoring applications, introduces the method of using the structural monitoring dataset of the Milan Cathedral for spatio-temporal analysis, and explores different S-T processing methods and opportunities.
JOURNAL OF CIVIL STRUCTURAL HEALTH MONITORING
(2023)
Article
Computer Science, Information Systems
Yanjun Qin, Haiyong Luo, Fang Zhao, Yuchen Fang, Xiaoming Tao, Chenxing Wang
Summary: We propose a novel spatio-temporal hierarchical MLP network (STHMLP) for traffic forecasting, which can capture the trend-cyclical and seasonal features of traffic time series. By using a decomposition architecture and designing fine and coarse modules, the STHMLP can extract spatio-temporal information from roads and regions and effectively capture both fine-grained and coarse-grained spatial dependencies. Experimental results on real-world traffic datasets demonstrate that the STHMLP outperforms state-of-the-art baselines.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Yue Pan, Xiaojing Zhou, Shuigen Qiu, Limao Zhang
Summary: This paper proposes a network-enabled approach for analyzing time series data related to tunnel boring machine (TBM) excavation behavior. The main objective is to capture spatio-temporal patterns of TBM dynamic excavation behavior from a topological structure perspective. The novelty is the developed time series analysis approach relying on the complex network perspective.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Azad Deihim, Eduardo Alonso, Dimitra Apostolopoulou
Summary: The prevalence of multivariate time series data has led to significant research and advancements in multivariate time series analysis. In this study, we propose a Spatio-Temporal Transformer with Relative Embeddings (STTRE) that incorporates the spatio-temporal nature of the data and achieves improved accuracy compared to other models.
Article
Geosciences, Multidisciplinary
Israel Martinez-Hernandez, Marc G. Genton
Summary: The development of complex and performant technologies enables the collection of large-scale spatio-temporal data. However, statistically modeling such datasets poses various challenges, including dealing with large datasets and nonstationarity. This research proposes a novel methodology that estimates continuous surfaces at each time point and models the sequence of surfaces using functional time series techniques. The advantages of this approach are demonstrated through a simulation study and the analysis of a high-resolution wind speed dataset. Overall, this method offers a valuable approach in the context of big data by considering random fields as a single entity.
SPATIAL STATISTICS
(2023)
Review
Computer Science, Artificial Intelligence
Jin Fan, Ke Zhang, Yipan Huang, Yifei Zhu, Baiping Chen
Summary: As industrial systems become more complex and monitoring sensors become more ubiquitous, multivariate time series prediction plays an increasingly important role in society. While recurrent neural networks with attention are the current state-of-the-art for this task, their limitations in handling complex data and long-term forecasting are recognized. This paper introduces a framework called PSTA-TCN, which combines parallel spatio-temporal attention mechanisms and stacked temporal convolutional networks (TCNs) to address these challenges. The proposed framework significantly reduces training time and improves accuracy, enabling stable predictions with windows up to 13 times longer than current methods.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Ecology
Alfonso Allen-Perkins, Ainhoa Magrach, Matteo Dainese, Lucas A. Garibaldi, David Kleijn, Romina Rader, James R. Reilly, Rachael Winfree, Ola Lundin, Carley M. McGrady, Claire Brittain, David J. Biddinger, Derek R. Artz, Elizabeth Elle, George Hoffman, James D. Ellis, Jaret Daniels, Jason Gibbs, Joshua W. Campbell, Julia Brokaw, Julianna K. Wilson, Keith Mason, Kimiora L. Ward, Knute B. Gundersen, Kyle Bobiwash, Larry Gut, Logan M. Rowe, Natalie K. Boyle, Neal M. Williams, Neelendra K. Joshi, Nikki Rothwell, Robert L. Gillespie, Rufus Isaacs, Shelby J. Fleischer, Stephen S. Peterson, Sujaya Rao, Theresa L. Pitts-Singer, Thijs Fijen, Virginie Boreux, Maj Rundlof, Blandina Felipe Viana, Alexandra-Maria Klein, Henrik G. Smith, Riccardo Bommarco, Luisa G. Carvalheiro, Taylor H. Ricketts, Jaboury Ghazoul, Smitha Krishnan, Faye E. Benjamin, Joao Loureiro, Silvia Castro, Nigel E. Raine, Gerard Arjen de Groot, Finbarr G. Horgan, Juliana Hipolito, Guy Smagghe, Ivan Meeus, Maxime Eeraerts, Simon G. Potts, Claire Kremen, Daniel Garcia, Marcos Minarro, David W. Crowder, Gideon Pisanty, Yael Mandelik, Nicolas J. Vereecken, Nicolas Leclercq, Timothy Weekers, Sandra A. M. Lindstrom, Dara A. Stanley, Carlos Zaragoza-Trello, Charlie C. Nicholson, Jeroen Scheper, Carlos Rad, Evan A. N. Marks, Lucie Mota, Bryan Danforth, Mia Park, Antonio Diego M. Bezerra, Breno M. Freitas, Rachel E. Mallinger, Fabiana Oliveira da Silva, Bryony Willcox, Davi L. Ramos, Felipe D. da Silva e Silva, Amparo Lazaro, David Alomar, Miguel A. Gonzalez-Estevez, Hisatomo Taki, Daniel P. Cariveau, Michael P. D. Garratt, Diego N. Nabaes Jodar, Rebecca I. A. Stewart, Daniel Ariza, Matti Pisman, Elinor M. Lichtenberg, Christof Schueepp, Felix Herzog, Martin H. Entling, Yoko L. Dupont, Charles D. Michener, Gretchen C. Daily, Paul R. Ehrlich, Katherine L. W. Burns, Montserrat Vila, Andrew Robson, Brad Howlett, Leah Blechschmidt, Frank Jauker, Franziska Schwarzbach, Maike Nesper, Tim Diekoetter, Volkmar Wolters, Helena Castro, Hugo Gaspar, Brian A. Nault, Isabelle Badenhausser, Jessica D. Petersen, Teja Tscharntke, Vincent Bretagnolle, D. Susan Willis Chan, Natacha Chacoff, Georg K. S. Andersson, Shalene Jha, Jonathan F. Colville, Ruan Veldtman, Jeferson Coutinho, Felix J. J. A. Bianchi, Louis Sutter, Matthias Albrecht, Philippe Jeanneret, Yi Zou, Anne L. Averill, Agustin Saez, Amber R. Sciligo, Carlos H. Vergara, Elias H. Bloom, Elisabeth Oeller, Ernesto I. Badano, Gregory M. Loeb, Heather Grab, Johan Ekroos, Vesna Gagic, Saul A. Cunningham, Jens Astrom, Pablo Cavigliasso, Alejandro Trillo, Alice Classen, Alice L. Mauchline, Ana Montero-Castano, Andrew Wilby, Ben A. Woodcock, C. Sheena Sidhu, Ingolf Steffan-Dewenter, Ioannis N. Vogiatzakis, Jose M. Herrera, Mark Otieno, Mary W. Gikungu, Sarah J. Cusser, Thomas Nauss, Lovisa Nilsson, Jessica Knapp, Jorge J. Ortega-Marcos, Jose A. Gonzalez, Juliet L. Osborne, Rosalind Blanche, Rosalind F. Shaw, Violeta Hevia, Jane Stout, Anthony D. Arthur, Betina Blochtein, Hajnalka Szentgyorgyi, Jin Li, Margaret M. Mayfield, Michal Woyciechowski, Patricia Nunes-Silva, Rosana Halinski de Oliveira, Steve Henry, Benno I. Simmons, Bo Dalsgaard, Katrine Hansen, Tuanjit Sritongchuay, Alison D. O'Reilly, Fermin Jose Chamorro Garcia, Guiomar Nates Parra, Camila Magalhaes Pigozo, Ignasi Bartomeus
Summary: This article introduces CropPol, a dynamic, open, and global database on crop pollination. The database contains records from 202 crop studies, covering 47,752 insect records from 48 commercial crops worldwide. This is the most comprehensive open global dataset on measurements of crop flower visitors, crop pollinators, and pollination to date.
Article
Forestry
Juan Aguero, Carolina Coulin, Juan P. Torretta, Lucas A. Garibaldi
Summary: The study found that disturbances can promote an increase in both native and exotic floral visitors, mainly due to the generalist interactions between plants and pollinators. Harvesting intensity had a significant positive effect on native floral visitors, and also impacted the density of exotic floral visitors, though the effects varied by site.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Article
Biodiversity Conservation
Adrian Gonzalez-Chaves, Luisa G. Carvalheiro, Lucas A. Garibaldi, Jean Paul Metzger
Summary: Enhancing biodiversity-based ecosystem services can lead to win-win opportunities for conservation and agricultural production. Forest cover is a crucial factor affecting coffee yields, and coffee cover is the most relevant management practice associated with coffee yield prediction.
JOURNAL OF APPLIED ECOLOGY
(2022)
Letter
Ecology
Rebecca Chaplin-Kramer, Kate A. Brauman, Jeannine Cavender-Bares, Sandra Diaz, Gabriela Teixeira Duarte, Brian J. Enquist, Lucas A. Garibaldi, Jonas Geldmann, Benjamin S. Halpern, Thomas W. Hertel, Colin K. Khoury, Joana Madeira Krieger, Sandra Lavorel, Thomas Mueller, Rachel A. Neugarten, Jesus Pinto-Ledezma, Stephen Polasky, Andy Purvis, Victoria Reyes-Garcia, Patrick R. Roehrdanz, Lynne J. Shannon, M. Rebecca Shaw, Bernardo B. N. Strassburg, Jason M. Tylianakis, Peter H. Verburg, Piero Visconti, Noelia Zafra-Calvo
NATURE ECOLOGY & EVOLUTION
(2022)
Review
Biology
Lucas A. Garibaldi, Dulce S. Gomez Carella, Diego N. Nabaes Jodar, Matthew R. Smith, Thomas P. Timberlake, Samuel S. Myers
Summary: This article reviews the impacts of pollinator health on human health and identifies four pathways connecting them, including nutrition, medicine provisioning, mental health, and environmental quality. The authors suggest that pollinator diversity could serve as a proxy for the benefits that landscapes provide to human health.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2022)
Article
Biodiversity Conservation
Ainhoa Magrach, Angel Gimenez-Garcia, Alfonso Allen-Perkins, Lucas A. Garibaldi, Ignasi Bartomeus
Summary: Recent research suggests that agricultural landscapes can provide significant opportunities for biodiversity conservation and crop productivity. Practices such as maintaining small field sizes and high crop richness values can increase crop yields, particularly for crops that depend on pollinator activity for reproduction.
JOURNAL OF APPLIED ECOLOGY
(2023)
Article
Biology
N. Perez-Mendez, C. Alcaraz, A. Bertolero, M. Catala-Forner, L. A. Garibaldi, J. P. Gonzalez-Varo, S. Rivaes, M. Martinez-Eixarch
Summary: This study evaluated the effects of changes in water management in rice farming on greenhouse gas emissions and waterbird diversity. The results showed that drying rice fields reduced methane emissions but decreased waterbird diversity, suggesting that post-invasion policies may have unintended negative consequences on biodiversity conservation.
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2022)
Article
Environmental Sciences
Matthew R. Smith, Nathaniel D. Mueller, Marco Springmann, Timothy B. Sulser, Lucas A. Garibaldi, James Gerber, Keith Wiebe, Samuel S. Myers
Summary: Insufficient animal pollination has a significant impact on global human health and agricultural economy, especially in low-income countries. Promoting pollinator-friendly practices is crucial.
ENVIRONMENTAL HEALTH PERSPECTIVES
(2022)
Review
Ecology
Fabrice Requier, Nestor Perez-Mendez, Georg K. S. Andersson, Elsa Blareau, Isabelle Merle, Lucas A. Garibaldi
Summary: Pollinators, especially non-bee pollinators, play a critical role in food security, yet their contribution to locally important crops is not well understood. We reviewed the diversity, conservation status, and role of bee and non-bee pollinators in 83 different crops of global or local importance. While bees are the most commonly recorded floral visitors, non-bee pollinators are frequently observed in locally important crops, including nocturnal insects, bats, and birds in tropical ecosystems. Neglected in current research, nocturnal pollinators are declining and urgently require integration into scientific studies and conservation efforts to promote sustainable agriculture and safeguard food security.
TRENDS IN ECOLOGY & EVOLUTION
(2023)
Editorial Material
Biodiversity Conservation
Diego Nabaes N. Jodar, Nestor Perez-Mendez, Cristina Botias, Lucas A. Garibaldi, Pablo L. Hunicken, Elena Velado-Alonso, Carlos Zaragoza-Trello
Summary: Abundant and diverse floral resources are crucial for the survival of pollinator populations and the benefits they provide to human societies. However, several agricultural practices, such as pesticide use and weed removal, have negative effects on pollinators. The proposal to remove ground vegetation after the crop's flowering period may reduce pesticide exposure, but it has limitations in terms of pollinator abundance and diversity. Additionally, it fails to address the importance of providing accessible, sufficient, safe, and seasonally-spread feeding resources for crop pollinators.
INSECT CONSERVATION AND DIVERSITY
(2023)
Article
Green & Sustainable Science & Technology
Maria Noel Szudruk Pascual, Veronica Chillo, Lucas A. Garibaldi, Mariano M. Amoroso
Summary: This study evaluates the effects of landscape and local variables on natural enemies' communities in small-scale agriculture, with a focus on functional response traits. The results show that landscape heterogeneity, local habitat, and management practices do not significantly affect the functional diversity of natural enemies. However, two management practices do impact the abundance of natural enemies. These findings highlight the importance of management in a heterogeneous landscape for promoting the resilience of pest control to land-use change.
Article
Forestry
S. A. Varela, J. P. Diez, F. Letourneau, E. Bianchi, M. Weigandt, A. J. Porte, S. Sergent, M. E. Nacif, L. A. Garibaldi, M. E. Fernandez
Summary: Globally, increasing forests vulnerability and drought-induced forest mortality events can rapidly alter forest functioning and ecosystem services provision. The Patagonian forests in Southern South America are important reservoirs of wildlife and highly productive. However, very little is known about the response of different woody species in these forests to climatic variation and severe drought, which is crucial for improving management strategies. This study aimed to identify the most vulnerable and most resilient species to drought and their response under different competition levels through physiological measurements. The results suggest that the effect of summer drought cannot be modulated by density management and the adaptability of the species studied may not be improved.
FOREST ECOLOGY AND MANAGEMENT
(2023)
Article
Biodiversity Conservation
Lucas A. Garibaldi, Paula F. Zermoglio, Esteban G. Jobbagy, Lucas Andreoni, Alejo Ortiz de Urbina, Ingo Grass, Facundo J. Oddi
Summary: This article discusses guidelines for transitioning to multifunctional landscapes and proposes an iterative process for designing these landscapes. It emphasizes the importance of restoring natural habitats and creating biological corridors, as well as redesigning field size and configuration. The authors argue that multifunctional landscapes will play a critical role in achieving global biodiversity targets and moving towards net-zero emissions.
JOURNAL OF APPLIED ECOLOGY
(2023)
Article
Entomology
Angela M. Cortes-Gomez, Adrian Gonzalez-Chaves, Nicolas Urbina-Cardona, Lucas A. Garibaldi
Summary: Pollination is crucial for food and nutritional security, and its different functional traits in insects remain poorly understood. This study investigates the relationship between insect functional traits and pollen transport in sweet granadilla crops. Bees were the most abundant insects and carried the highest amounts of pollen, with exotic honeybees being the most common species but carrying less pollen than native bees. Large-bodied native bees, such as Bombus hortulanus, carried more sweet granadilla pollen despite their low abundance. Body size was the most important trait influencing pollen transport, while traits related to body hairs had no significant effect.
NEOTROPICAL ENTOMOLOGY
(2023)
Review
Entomology
Juan Pablo Torretta, Hugo J. Marrero, Rocio Gonzalez-Vaquero, Lucas A. Garibaldi
Summary: This article presents the species diversity and threats faced by solitary bees in the Pampean region's agricultural ecosystem. The study found that low floral diversity and the use of agrochemicals could limit the population of these insects. In the current agricultural scenario, solitary bee species face a challenging situation.
JOURNAL OF APICULTURAL RESEARCH
(2023)