A novel multidimensional framework for bridging conservation gaps and optimizing the system of natural reserves for biodiversity: A case study of Dongying, China by Yifei Xu, Chi Li

“…Using this framework, we quantitatively explored the spatial and temporal dynamics of species dispersal and habitat quality for migratory birds in Dongying, China. …”
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Microseismic Monitoring of Energy Changes in Deep Tunnels during the TBM Tunneling of the Jinping II Hydropower Station by Duanyang Zhuang, Ke Ma, Chunan Tang, Zhengzhao Liang, Zhenwei Wang

“…A movable microseismic (MS) monitoring system was established to capture the MS events and rockbursts when the TBM excavated the headrace tunnel #1 at the Jinping II hydropower station. The spatial and temporal patterns of the energy changes in the tunnel rock masses were studied. …”
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The Value of Learning about Natural History in Biodiversity Markets. by Douglas J Bruggeman

“…I use an individually-based, spatially-explicit population model for the Red-cockaded Woodpecker (Picoides borealis) to predict spatial- and temporal- influences of landscape change on species occurrence and genetic diversity. …”
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Multimodal sleep staging network based on obstructive sleep apnea by Jingxin Fan, Jingxin Fan, Jingxin Fan, Mingfu Zhao, Li Huang, Li Huang, Bin Tang, Bin Tang, Lurui Wang, Zhong He, Zhong He, Xiaoling Peng

“…The Multi-Scale Feature Extraction Module (MFEM) employs convolutional layers with varying dilation rates to capture spatial patterns from fine to coarse granularity. …”
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Identifying gaps in protection from malaria vector biting in rural Cambodia using an entomological assessment and human behaviour observations by David J. McIver, Elodie A. Vajda, Dyna Doum, Nicholas W. Daniel, Molly Quan, Diane D. Lovin, Joanne M. Cunningham, Siv Sovannaroth, Allison Tatarsky, Neil F. Lobo

“…Conclusion This study demonstrates the importance of understanding spatial and temporal human exposure to mosquito bites, in the presence of proven vector control tools (LLINs, LLIHNs) and newly introduced bite prevention tools (VPSRs, ITCs, and TRs). …”
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Trends in Heavy Metal Pollution in Agricultural Land Soils of Tropical Islands in China (2000–2024): A Case Study on Hainan Island by Erping Shang, Yong Ma, Wutao Yao, Shuyan Zhang

“…Pb and As show similar spatial patterns, with higher concentrations in the west and lower concentrations in the east. …”
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Conv1D-GRU-Self Attention: An Efficient Deep Learning Framework for Detecting Intrusions in Wireless Sensor Networks by Kenan Honore Robacky Mbongo, Kanwal Ahmed, Orken Mamyrbayev, Guanghui Wang, Fang Zuo, Ainur Akhmediyarova, Nurzhan Mukazhanov, Assem Ayapbergenova

“…This study proposes a hybrid IDS model combining one-dimensional Convolutional Neural Networks (Conv1Ds), Gated Recurrent Units (GRUs), and Self-Attention mechanisms. A Conv1D extracts spatial features from network traffic, GRU captures temporal dependencies, and Self-Attention emphasizes critical sequence components, collectively enhancing detection of subtle and complex intrusion patterns. …”
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Assessing Coincidence of Satellite Acquisitions and Flood Events to Predict Suitability for Flood Map Synthesis by Lyle Prince, Riley C. Hales, Kel N. Markert, E. James Nelson, Gustavious P. Williams, Daniel P. Ames, Hyongki Lee, Amirhossein Rostami

“…For our processes, we used Forecasting Inundation Extents using REOF analysis (FIER), a data-driven method of synthesizing flood maps by correlating extracted spatial and temporal patterns from satellite imagery with historical hydrological variables. …”
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Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations by Bowen Chang, Haoran Liu, Chengxin Zhang, Chengzhi Xing, Wei Tan, Cheng Liu

“…This study enhances understanding of the spatial and temporal dynamics and influencing mechanisms of CNO2 and SNO2, supporting improved air quality assessments and pollution exposure evaluations.…”
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HCMMA-Net: A Hybrid Convolutional Multi-Modal Attention Network for Human Activity Recognition in Smart Homes Using Wearable Sensor Data by Nazish Ashfaq, Zeeshan Aziz, Muhammad Hassan Khan, Muhammad Adeel Nisar, Adnan Khalid

“…This study examines the role of multi-modalities in HAR using a hybrid convolutional multi-modal attention network (HCMMA-Net), designed to exploit spatial and temporal dependencies in sensor data. …”
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Spatiotemporal Coupling Characteristics Between Urban Land Development Intensity and Population Density from a Building-Space Perspective: A Case Study of the Yangtze River Delta U... by Xiaozhou Wang, Lie You, Lin Wang

“…As China shifts from rapid to high-quality development, urban growth has exhibited allometric patterns. This study evaluated land use efficiency from the perspective of architectural space, focusing on 41 cities in the Yangtze River Delta urban agglomeration from 2010 to 2020. …”
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Soil moisture forecasting in wireless sensor networks via spatiotemporal graph convolutional networks by Weixuan Wang, Yating Wei, Longfei Hao, Zushuai Wei, Tianjie Zhao

“…However, due to the combined effects of internal factors like soil types, terrain, and vegetation cover, as well as external factors such as precipitation and temperature, soil moisture data in wireless sensor networks exhibit complex spatial and temporal interdependencies. Consequently, developing predictive models that can accurately capture these dependencies and enable precise forecasts of soil moisture within these networks poses a significant challenge. …”
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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

“…Advanced deep learning architectures such as convolutional neural networks (CNNs), deep CNNs (DCNNs), and recurrent neural networks (RNNs) are utilized to identify critical spatial and temporal patterns in the data. The models are trained on a comprehensive dataset encompassing environmental indicators, fire-prone area characteristics, and real-time meteorological data. …”
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The Dynamics of Air Pollution in the Southwestern Part of the Caspian Sea Basin (Based on the Analysis of Sentinel-5 Satellite Data Utilizing the Google Earth Engine Cloud-Computin... by Vladimir Tabunshchik, Aleksandra Nikiforova, Nastasia Lineva, Polina Drygval, Roman Gorbunov, Tatiana Gorbunova, Ibragim Kerimov, Cam Nhung Pham, Nikolai Bratanov, Mariia Kiseleva

“…Additionally, the Gorgan basin exhibited elevated carbon monoxide levels, while the highest ozone concentrations were detected in the Sunzha basin. Our temporal analysis demonstrated a substantial influence of the COVID-19 pandemic on pollutant dispersion patterns. …”
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Multi-dimensional water quality indicators forecasting from IoT sensors: A tensor decomposition and multi-head self-attention mechanism. by Li Bo, Lv Junrui, Luo Xuegang

“…To overcome these limitations, we propose TGMHA (Tensor Decomposition and Gated Neural Network with Multi-Head Self-Attention), a novel hybrid model that integrates three key innovations: 1) Tensor-based Feature Extraction: We combine Standard Delay Embedding Transformation (SDET) with Tucker tensor decomposition to reconstruct raw time series into low-rank tensor representations, capturing latent spatio-temporal patterns while suppressing sensor noise. 2) Multi-Head Self-Attention for Inter-Indicator Dependencies: A multi-head self-attention mechanism explicitly models complex inter-dependencies among diverse water quality indicators (e.g., pH, dissolved oxygen, conductivity) via parallel feature subspace learning. 3) Efficient Long-Term Dependency Modeling: An encoder-decoder architecture with gated recurrent units (GRUs), optimized by adaptive rank selection, ensures efficient modeling of long-term dependencies without compromising computational performance. …”
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Monthly methane emissions in Chinese mainland provinces from 2013–2022 by Duo Cui, Siyao Yang, Xuanren Song, Xiaoting Huang, Cuncun Duan, Mingrui Ji, Zhongyan Li, Siqi Yu, Zhu Deng, Piyu Ke, Xinyu Dou, Taochun Sun, Zhu Liu

“…Methane, a potent greenhouse gas, is emitted from diverse anthropogenic and natural sources, many of which exhibit pronounced temporal variability. In particular, emissions from rice cultivation, energy use, and livestock management show strong seasonal patterns, yet high-frequency and spatially detailed methane emission inventories have been lacking. …”
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The global, regional and national burden of peptic ulcer disease attributable to smoking from 1990 to 2021: A population-based study by Shuai Wang, Tao Zhang, Dongming Li, Xueyuan Cao

“…This study analyzes the temporal and spatial patterns of PUD burden attributable to smoking globally from 1990 to 2021, providing insights for public health interventions. …”
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Spatiotemporal analysis of thermal islands in a semi-arid city: A case study of Kermanshah, Iran using machine learning and remote sensing by Peyman Karami, Seyed-Mohsen Mousavi

“…Cold Islands (CIs) and Hot Islands (HIs) were identified for each image using LST and Getis-Ord Gi analysis, and their spatio-temporal changes were evaluated with the Kappa index and landscape metrics. …”
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Exploring habitat‐density relationships and model transferability for an alpine bird using abundance models by Håkon Brandt Fjeld, Jan Eivind Østnes, Erlend B. Nilsen

“…While several previous studies have evaluated the transferability of species distribution models, much less is known about how well models that predict spatially explicit population density transfer across contexts. …”
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Urban Heat Island Effect: Remote Sensing Monitoring and Assessment—Methods, Applications, and Future Directions by Lili Zhao, Xuncheng Fan, Tao Hong

“…The paper first analyzes the formation mechanisms and impacts of urban heat islands, then traces the evolution of remote sensing technology from early traditional platforms such as Landsat and NOAA-AVHRR to modern next-generation systems, including the Sentinel series and ECOSTRESS, emphasizing improvements in spatial and temporal resolution and their application value. …”
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