Identifying key aspects to enhance predictive modeling for early identification of schistosomiasis hotspots to guide mass drug administration. by Yewen Chen, Fangzhi Luo, Leonardo Martinez, Susan Jiang, Ye Shen

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Spatial Analysis of the Livability Status of the Three Areas of Gorgan Based On the Physical-Spatial Index by Mostafa Ariankia, Shaghayegh Shirazi Irai

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Geospatial Modelling of Flood Susceptibility of the Calabar City, Cross River State, Nigeria by Joel Efiong, Eme Efiong, Oluyemi Akintoye, Ebin Inah, Obianuju Awan, Francis Ogban

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Landslide assessment considering spatial calibration zoning of physical and mechanical parameters of rock and soil mass by Weimin YIN, Yuanyao LI, Xing LI, Ming LI, Le JU, Ou XIE

“…However, traditional SINMAP models overlook the spatial differences in rock and soil characteristics due to geological environmental changes, resulting in low accuracy in assessment results. …”
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Study on the spatial spillover effect of reclaimed water utilization efficiency in water environment-sensitive areas with heterogeneous technology by Wei Jin, Shuhan Gao, Wei Jiang, Huimin Wang

“…This paper uses the three-stage Slack-Based Measure (SBM) model to measure the efficiency of recycled water utilization in 41 cities in the Yangtze River Delta, and based on the characteristics of technological heterogeneity, systematically exploring the spatial correlation mechanism of recycled water utilization. …”
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An Analysis of the Effects of Spatial Dependence on Economic Growth Among Regencies and Cities in Java by Ma’rufa Khotiawan, Rachmad Kresna Sakti, Setyo Tri Wahyudi

“…Exploratory Spatial Data Analysis (ESDA) and Spatial Durbin Model (SDM) were used to analyze the determinants of the spatial dependence and its impact on regional economic growth. …”
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Modelling of spatially correlated weather-based electricity forecasting using combined frequency-based signal decomposition with optimized boosting approach by Indra A. Aditya, Didit Adytia

“…The primary contribution is a spatially correlation-driven feature selection technique to choose ideal weather input sites, coupled with the extraction of predominant frequency components from the load signal to enhance model input. …”
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Nonlocal fractional MGT-non-Fourier photothermal model with spatial and temporal nonlocality for controlling the behavior of semiconductor materials with spherical cavities by Mofareh Alhazmi, Ahmed E. Abouelregal

“…In this work, we present the nonlocal Moore-Gibson-Thompson photothermal (NMGTPT) theory, a novel framework that integrates spatial and temporal nonlocality to address limitations in both traditional and advanced thermoelastic models. …”
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High-spatial-resolution surface soil moisture retrieval using the Deep Forest model in the cloud environment over the Tibetan Plateau by Zhenghao Li, Qiangqiang Yuan, Xin Su

“…As a key climate variable, soil moisture plays a crucial role in drought detection, flood warning, and crop yield prediction. In recent years, the demand for high-spatial-resolution soil moisture has increased, particularly in environmental management. …”
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Spatial Effects and Mechanisms of the Digital Economy on Energy Efficiency: Empirical Findings from China by Rongbin Zhang, Xiaoxiao Wu, Yifei Chen

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An EG-Tree Model Incorporating Spatial Heterogeneity for Analyzing Multifactorial Coupling Effects on Carbon Emissions Across Industries and Regions in China by Jinrui Zang, Xin Hu, Kun Qie, Zian Zhang, Shi Zhang

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Collaborative Superpixelwised PCA for Hyperspectral Image Classification by Chao Yao, Junrui Gu, Zehua Guo, Miao Ma, Qingrui Guo, Gong Cheng

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Assessment of Geostatistical Approach to Spatial Distribution of Soil Fertility Characteristics of the Southwest of Shiraz in Different Land Uses by H.R. Owliaie, A.R. Salehi, Gh.R. Zareian

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Study on the effect of technological innovation on carbon emission intensity in 278 prefecture-level cities in China by Xuelian Zhu, Jianan Che, Xiaogeng Niu, Nannan Cao, Meiyu Liu

“…This study investigates the impact of technological innovation on the carbon intensity of Chinese cities using a spatial Durbin model combined with prefecture-level data. …”
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SFSCDNet: A Deep Learning Model With Spatial Flow-Based Semantic Change Detection From Bi-Temporal Satellite Images by K. S. Basavaraju, N. Sravya, Vibha Damodara Kevala, Shilpa Suresh, Shyam Lal

“…Existing deep learning-based methods, particularly those relying on triple-branch architectures, often struggle to accurately localize and predict changes in complex spatial environments characterized by diverse land-cover types. …”
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Spatio-temporal modelling and prediction of malaria incidence in Mozambique using climatic indicators from 2001 to 2018 by Chaibo Jose Armando, Joacim Rocklöv, Mohsin Sidat, Yesim Tozan, Alberto Francisco Mavume, Maquins Odhiambo Sewe

“…This study aims to develop and evaluate a spatial–temporal prediction model for malaria incidence in Mozambique for potential use in a malaria early warning system (MEWS). …”
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Spatial disparities of antenatal care utilization among pregnant women in sub-Saharan Africa—Bayesian geo-additive modelling approach by Denekew Bitew Belay, Denekew Bitew Belay, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Nigussie Adam Birhan, Najmeh Nakhaei Rad, Ding-Geng Chen, Ding-Geng Chen

“…A Bayesian geo-additive model with Besag-York-Mollié (BYM) mixed effect was found to be the best model to assess the spatial dependencies and the non-linear effects of the factors on ANC utilization among women of reproductive age. …”
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Spatial–Temporal Reconstruction of Trajectories in Free Space Using Automatic Target Position Detection Data by Yang Chen, Xin Chen, Bin Bai, Linjiang Zheng

“…Then, based on the reconstructed spatial trajectory of the target, this paper proposes a time series prediction model based on historical trajectories and an attention mechanism, which considers the impact of the target’s activity cycle and the surrounding status to predict the time series inside the trajectory. …”
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Modeling regional aboveground carbon stock dynamics affected by land use and land cover changes by A.D. Malik, M.C.W. Arief, S. Withaningsih, P. Parikesit

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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…The proposed charging demand gravity model optimizes users' charging station selection behavior by integrating factors such as charging station size， electricity price， and user time cost， resulting in a more reasonable spatial and temporal distribution of the charging load[Conclusions] This study constructed a spatial and temporal distribution prediction model for electric vehicle charging loads by integrating information from multiple sources. …”
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