Long time-series and high-frequency ecological evaluation of Henan section of the Yellow River by Jianzhong Guo, Daozhu Xu, Jian Xu, Ruoxin Zhu, Ning Li

Get full text

Spatiotemporal, environmental, and behavioral predictors of Varroa mite intensity in managed honey bee apiaries. by Laura Boehm Vock, Lauren M Mossman, Zoi Rapti, Adam G Dolezal, Sara M Clifton

“…We examine risk factors for Varroa infestation using apiary inspection data collected across the state of Illinois over 2018-2019, and we test the models using inspection data from 2020-2021. After accounting for spatial and temporal trends, we find that most environmental factors (e.g., floral quality, insecticide load) are not predictive of Varroa intensity, while lower numbers of nearby apiaries and several beekeeper behaviors (e.g., supplemental feeding and mite monitoring/treatment) are protective against Varroa. …”
Get full text

iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…Finally, a hybrid model combining an unsupervised SOM and followed by the supervised Random Forest model returned an accuracy of 83.47% for the training and 80.77% for the test, with Bathymetry, Chlorophyll, and Coarse Sand as key predictive variables. …”
Get full text

An integrated approach to flood risk assessment using multi-criteria decision analysis and geographic information system. A case study from a flood-prone region of Pakistan by Muhammad Ibrahim, Aidi Huo, Aidi Huo, Aidi Huo, Waheed Ullah, Safi Ullah, Zhao Xuantao

Get full text

Identifying monthly rainfall erosivity patterns using hourly rainfall data across India by Subhankar Das, Manoj Kumar Jain, Karl Auerswald, Carlos Rogerio de Mello, Peter Molnar

“…Monthly erosivity estimates derived from hourly data were linked with monthly rainfall, enabling a simplified and efficient estimation approach. To predict monthly erosivity based on rainfall, temperature, and topographic variables, we developed and evaluated three modeling approaches: linear regression, a machine learning-based XGBoost model, and an ensemble model. …”
Get full text

Mode use in long-distance travel by Alexander Reichert, Christian Holz-Rau

“…The aim of this paper is to analyze the mode use in long-distance travel in different spatial settings by using multivariate regression models. …”
Get full text

Nonlinear and synergistic effects of demographic characteristics on urban polycentric structure using SHAP by Yichen Ruan, Xiaoyi Zhang, Mingyu Zhang, Feiyang Sun, Qiuxiao Chen

“…Spatial heterogeneity is observed in the demographic profiles of urban centers; for instance, primary central cores are predominantly young, single females, whereas peripheral and secondary centers have stronger presence of highly educated residents.…”
Get full text

Estimation of Relative Sea Level Change in Locations Without Tide Gauges Using Artificial Neural Networks by Heeryun Kim, Young Il Park, Wansik Ko, Taehyun Yoon, Jeong-Hwan Kim

“…Unlike conventional forecasting approaches focused on future time series prediction, the proposed model is designed to learn spatial distribution patterns and temporal rates of sea level change from a fusion of satellite altimetry and tide gauge data. …”
Get full text

Physical forcing mechanisms controlling the variability of chlorophyll-a over the Royal-Charlotte and Abrolhos Banks-Eastern Brazilian Shelf. by Renato David Ghisolfi, Meyre Pereira da Silva, Felipe Thomaz dos Santos, Ricardo Nogueira Servino, Mauro Cirano, Fabiano Lopes Thompson

“…The present study investigates the seasonal and spatial distributions of chlorophyll-a (Chl-a) and water conditions by analyzing nine years (2003-2011) of level-3 Moderate-resolution Imaging Spectroradiometer (MODIS) derived Chl-a, National Centers for Environmental Prediction (NCEP)/ETA model-derived winds, NCEP model-derived heat fluxes, thermohaline and velocity results from the Hybrid Circulation Ocean Model (HYCOM) 1/12o assimilated simulation. …”
Get full text

Radar Echo Extrapolation Based on Translator Coding and Decoding Conditional Generation Adversarial Network by Xingang Mou, Yuan He, Wenfeng Li, Xiao Zhou

“…In response to the shortcomings of current spatiotemporal prediction models, which frequently encounter difficulties in temporal feature extraction and the forecasting of medium to high echo intensity regions over extended sequences, this study presents a novel model for radar echo extrapolation that combines a translator encoder-decoder architecture with a spatiotemporal dual-discriminator conditional generative adversarial network (STD-TranslatorNet). …”
Get full text

Driving Factors in the Development of Eye Movement Patterns in Chinese Reading: The Roles of Linguistic Ability and Oculomotor Maturation by Meihua Guo, Nina Liu, Jingen Wu, Chengchieh Li, Guoli Yan

“…Path analysis explored how these factors predict temporal and spatial eye movement measures. …”
Get full text

MAD-RAPPEL: Mobility Aware Data Replacement And Prefetching Policy Enrooted LBS by Ajay K. Gupta, Udai Shanker

“…The cache replacement and invalidation module uses the next location prediction algorithm by the application of the mobility Markov model on mobile user’s trajectories. …”
Get full text

Finger Knuckle Print classification: Leveraging vision Mamba for low complexity and high accuracy by Chiron Bang, Ali Salem Altaher, Ahmed Altaher, Hawraa Moamin, Thamer Alshammari, Basmh Alkanjr, Hasan Altaher, Mohammed G. Al-Jassani, Hanqi Zhuang

Get full text

Federated LeViT-ResUNet for Scalable and Privacy-Preserving Agricultural Monitoring Using Drone and Internet of Things Data by Mohammad Aldossary, Jaber Almutairi, Ibrahim Alzamil

“…Spectral normalization, spatial–temporal alignment, and dimensionality reduction provide reliable input representation. …”
Get full text

Quantifying heat-related risks from urban heat island effects: A global urban expansion perspective by Ming Hao, Xue Liu, Xia Li

Get full text

Evaluation of 2024 Meteorological Drought Forecasts for Türkiye: Using ECMWF SEAS5 Data and the SPEI Index by Gülten Çamalan, Sercan Akil

“…Long-term precipitation and temperature data from 190 meteorological observation stations, with records starting from 1969, were employed to identify climate trends using the Mann-Kendall rank correlation method. The study presents spatial and temporal distributions of drought conditions and assesses the SEAS5 model’s success in predicting droughts across different months and seasons. …”
Get full text

Reconstructing tropical monthly sea surface temperature variability by assimilating coral proxy datasets by Wenqing Hu, Liang Ning, Zhengyu Liu, Jian Liu, Fen Wu, Mi Yan, Leilei Jiang, Lili Lei, Fangmiao Xing, Haohao Sun, Kefan Chen, Yanmin Qin, Weiyi Sun, Qin Wen, Benyue Li

Get full text

Pretreatment PET dissemination features as biomarkers for survival outcomes in melanoma patients treated with immune-checkpoint inhibitors by Hanna Saadani, Else A. Aalbersberg, Mutamba T. Kayembe, John B.A.G. Haanen, Otto S. Hoekstra, Ronald Boellaard, Marcel P.M. Stokkel

“…The validated dissemination model, clinical model and combination model showed similar low discriminative ability with an Area Under the Curve (AUC) of 0.61–0.66 for OS and an AUC of 0.59–0.66 for PFS. …”
Get full text

The impact of international institutions on Brussels: a multi‑criteria analysis approach by Eric Corijn, Cathy Macharis, Theo Jans, Michel Huysseune

“…Possible distributive effects will be tracked across existing patterns of spatial diversity. The proposed model embeds identification, measurement and assessment in a fine-grained understanding of Belgian urban systems, thus allowing the disaggregation and localisation of impacts. …”
Get full text

L’impact des institutions internationales à Bruxelles : une approche multicritères by Eric Corijn, Cathy Macharis, Theo Jans, Michel Huysseune

“…Possible distributive effects will be tracked across existing patterns of spatial diversity. The proposed model embeds identification, measurement and assessment in a fine-grained understanding of Belgian urban systems, thus allowing the disaggregation and localisation of impacts. …”
Get full text