Observation and Numerical Simulation of Cross-Mountain Airflow at the Hong Kong International Airport from Range Height Indicator Scans of Radar and LIDAR by Ying Wa Chan, Kai Wai Lo, Ping Cheung, Pak Wai Chan, Kai Kwong Lai

“…In order to study the feasibility of predicting such disturbed airflow, a mesoscale meteorological model and a computational fluid dynamics model with high spatial resolution are used in this paper. …”
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Assessing the Impact of Land Use and Land Cover Change on Environmental Parameters in Khyber Pakhtunkhwa, Pakistan: A Comprehensive Study and Future Projections by Mehjabeen Khan, Ruishan Chen

“…Projections for 2100 predict LST rising to 55.3 °C, with NDVI, MNDWI, and NDMI dropping to 0.36, 0.17, and 0.21, respectively. …”
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Real-Time Fire Risk Classification Using Sensor Data and Digital-Twin-Enabled Deep Learning by In-Seop Na, Vani Rajasekar, Velliangiri Sarveshwaran

“…A key innovation is the use of digital twin technology, which dynamically integrates real-time data from IoT sensors and simulation models to predict fire disaster scenarios accurately. …”
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Estimating corn leaf chlorophyll content using airborne multispectral imagery and machine learning by Fengkai Tian, Jianfeng Zhou, Curtis J. Ransom, Noel Aloysius, Kenneth A. Sudduth

“…A UAV-based multispectral camera collected imagery at the same time as manual readings. Machine learning models developed based on image features derived from UAV images were used to predict leaf chlorophyll content. …”
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Canopy height mapping in French Guiana using multi-source satellite data and environmental information in a U-Net architecture by Kamel Lahssini, Nicolas Baghdadi, Guerric le Maire, Guerric le Maire, Ibrahim Fayad, Ibrahim Fayad, Ludovic Villard

“…The potential of a U-Net architecture trained on sparse and unevenly distributed GEDI data to generate a continuous canopy height map at a regional scale was assessed. The developed model, named CHNET, successfully produced a canopy height map of French Guiana at a 10-m spatial resolution, achieving relatively good accuracy compared to a validation airborne LiDAR scanning (ALS) dataset. …”
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ENHANCING WEIGHTED FUZZY TIME SERIES FORECASTING THROUGH PARTICLE SWARM OPTIMIZATION by Armando Jacquis Federal Zamelina, Suci Astutik, Rahma Fitriani, Adji Achmad Rinaldo Fernandes, Lucius Ramifidisoa

“…Furthermore, the length of the interval and the extent to which previous values (Order length) are utilized in predicting the subsequent value are pivotal factors in WFTS modelization and its forecasting accuracy. …”
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Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials by Jingjing Sun, Xin Guan, Siqi Yuan, Yalin Guo, Yepei Tan, Yajuan Gao

“…The model utilized convolutional and pooling layers to capture local features and spatial information from image datasets, with tasks including image classification and segmentation.ResultsThe survey results indicate high awareness of smart cities (80%), with 60% associating them with environmental protection and green living. …”
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Influence of Sea Level Rise on Storm Surges in the Pearl River Estuary by HU Yaohui, WANG Zhili, ZHANG Juan, WU Yufu

“…Simultaneously, the variation of water level increase of storm surge within the Pearl River Estuary exhibits a spatially non-uniform characteristic, with an escalation in water level on the northeastern side and a reduction on the southwestern side of the Pearl River Estuary. ③ The ascent of sea level will give rise to an earlier peak water level of the storm surge. …”
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The theoretical cognition and research paradigm of land system science by LONG Hualou, CHEN Kunqiu, ZHENG Yuhan, ZHANG Yingnan

“…The research paradigm of land system science has gradually transformed from knowledge and phenomenon description to the simulation and prediction of complex land systems, which emphasizes the integration of multidisciplinary theories and methods as well as understanding the local-distant coupled interactions of land systems based on the integrated multiscale analysis of expanding boundaries, and focuses on the construction of large-scale quantitative land system models to provide comprehensive and dynamic integrated analysis, prediction and simulation of its dynamic mechanisms, integrated effects and future scenarios and risks, and appeals for an opening scientific collaboration in the era of big data.…”
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Neurophysiological predictors of deep learning based unilateral upper limb motor imagery classification by Justin Sonntag, Lin Yu, Xilu Wang, Thomas Schack

“…To understand whether neurophysiological features, which are directly related to neural mechanisms of motor imagery, might influence classification accuracy, most studies have largely leveraged traditional machine learning frameworks, leaving deep learning-based techniques underexplored.MethodsIn this work, three different deep learning models from the literature (EEGNet, FBCNet, NFEEG) and two common spatial pattern-based machine learning classifiers (SVM, LDA) were used to classify imagined right elbow flexion and extension from participants using electroencephalography data. …”
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CT texture analysis in patients with locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy: A potential imaging biomarker for treatment response and prognosis. by Choong Guen Chee, Young Hoon Kim, Kyoung Ho Lee, Yoon Jin Lee, Ji Hoon Park, Hye Seung Lee, Soyeon Ahn, Bohyoung Kim

“…Cox proportional hazards models were constructed to predict prognosis based on stage, age, and each texture feature. …”
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Aeromagnetic delineation of iron ore deposits in a complex geological terrain aided by fuzzy logic by Fahad Abubakar, Felix Bamidele Fatoye, Momohjimoh Abdulsalami, Abdullateef Aliyu

“…Validation using four known iron ore mining sites confirmed model accuracy, with all sites located within predicted high-potential zones. …”
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A global overview of marine heatwaves in a changing climate by Antonietta Capotondi, Regina R. Rodrigues, Alex Sen Gupta, Jessica A. Benthuysen, Clara Deser, Thomas L. Frölicher, Nicole S. Lovenduski, Dillon J. Amaya, Natacha Le Grix, Tongtong Xu, Juliet Hermes, Neil J. Holbrook, Cristian Martinez-Villalobos, Simona Masina, Mathew Koll Roxy, Amandine Schaeffer, Robert W. Schlegel, Kathryn E. Smith, Chunzai Wang

“…To make progress on predicting and projecting marine heatwaves and their impacts, a more complete mechanistic understanding of these extremes over the full ocean depth and at the relevant spatial and temporal scales is needed, together with models that can realistically capture the leading mechanisms at those scales. …”
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Infilling of missing rainfall radar data with a memory-assisted deep learning approach by J. Meuer, L. M. Bouwer, L. M. Bouwer, F. Kaspar, R. Lehmann, W. Karl, T. Ludwig, C. Kadow

“…<p>Incomplete spatiotemporal meteorological observations can result in misinterpretations of the current climate state, uncertainties in early warning systems, or inaccuracies in nowcasting models and can thereby pose significant challenges in hydrology research or similar applications. …”
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Artificial Intelligence and Objective‐Function Methods Can Identify Bankfull River Channel Extents by Jonathan Garber, Karen Thompson, Matthew J. Burns, Joshphar Kunapo, Geordie Z. Zhang, Kathryn Russell

“…To address this limitation, we developed and tested two automated channel delineation methods that define bankfull according to different conceptualisations of bankfull extent: (a) a cross‐sectional method called HydXS that identifies the elevation which maximizes hydraulic depth (cross‐section area/wetted width); and (b) a neural network image segmentation model based on a pretrained model (ResNet‐18), retrained with images derived from a digital elevation model. …”
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Incorporating long-term numerical weather forecasts to quantify dynamic vulnerability of irrigation supply system: A case study of Shihmen Reservoir in Taiwan by Chia-Chuan Hsu, Yu-Pin Lin

“…Techniques including K-nearest neighbors (KNN) for spatial downscaling, Long Short-Term Memory (LSTM) networks for simulating rainfall runoff, and Monte Carlo simulations (MCS) for analyzing system vulnerability are employed. …”
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Potential risk of heavy metals release in sediments and soils of the Yellow River Basin (Henan section): A perspective on bioavailability and bioaccessibility by Peng Wang, Furong Yu, Haonan Lv, Lin Wu, Hui Zhou

“…The sediment-soil system in the middle and lower reaches of the Yellow River Basin (Henan section) was explored. The spatial distribution characteristics of heavy metals (HMs) showed that tributaries, which are affected by anthropogenic activities, contain higher concentrations of HMs than the main channel. …”
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Boundary-Aware Transformer for Optic Cup and Disc Segmentation in Fundus Images by Soohyun Wang, Byoungkug Kim, Doo-Seop Eom

“…Furthermore, the proposed model more accurately captures the relative size and spatial alignment of the OD and OC and produces smooth and consistent boundary predictions in clinically significant regions such as the region of interest (ROI). …”
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A method to quantify jump dispersal of invasive species from occurrence data: the case of the spotted lanternfly, Lycorma delicatula by Nadège Belouard, Sebastiano De Bona, Matthew R. Helmus, Isabella G. Smith, Jocelyn E. Behm

“…The accuracy of predicting the spread of biological invasions is improved if models explicitly incorporate the two main dispersal mechanisms: diffusive spread and jump dispersal. …”
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Role of Cairns–Gurevich ion distribution on nonlinear wave propagation in negatively charged dusty plasma by N.S. Alharthi

“…The results demonstrated that soliton waves, explosive waves, and kink waves exhibit distinct behaviors depending on these parameters and the spatial context of Earth's magnetosphere. These findings provide new insights compared to previous studies into the conditions under which these waveforms emerge and evolve, especially in magnetized environments where earlier models were less effective at accurately characterizing or predicting wave behavior. …”
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