An Adaptive Graph Convolutional Network with Spatial Autocorrelation for Enhancing 3D Soil Pollutant Mapping Precision from Sparse Borehole Data by Huan Tao, Ziyang Li, Shengdong Nie, Hengkai Li, Dan Zhao

“…We propose an adaptive graph convolutional network with spatial autocorrelation (ASI-GCN) model to overcome this challenge. …”
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A single-cell and spatial wheat root atlas with cross-species annotations delineates conserved tissue-specific marker genes and regulators by Yuji Ke, Vincent Pujol, Jasper Staut, Lotte Pollaris, Ruth Seurinck, Thomas Eekhout, Carolin Grones, Maite Saura-Sanchez, Michiel Van Bel, Marnik Vuylsteke, Andrea Ariani, Christophe Liseron-Monfils, Klaas Vandepoele, Yvan Saeys, Bert De Rybel

“…Here, we generated a single-cell RNA sequencing atlas of soil-grown wheat roots and annotated cluster identities by transferring annotations from publicly available datasets in wheat, rice, maize, and Arabidopsis. The predictions from our orthology-based annotation approach were next validated using untargeted spatial transcriptomics. …”
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Assessment of the spatial and temporal heterogeneity of available phosphorus content in arable soil on the scale of one field (using the example of the Republic of Tatarstan, Russi... by Sakhabiev Ilnas, Giniyatullin Kamil, Smirnova Elena

“…It is analyzed that random forest models describe 64-68% of the spatial heterogeneity of the available phosphorus content depending on the year. …”
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Research on Diagnostic Methods for Zero-Value Insulators in 110 kV Transmission Lines Based on Spatial Distribution Characteristics of Electric Fields by Lei Zheng, Pengxiang Yin, Jian Li, Hui Liu, Tao Li, Hao Luo

“…Based on the electric field changes, a detection method for zero-value insulators is proposed. Additionally, a prediction model for the electric field strength of insulators with zero-value defects is developed using a Multilayer Perceptron (MLP) neural network. …”
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Towards global elimination of lymphatic filariasis: a systematic review of the application of spatial epidemiological methods to enhance surveillance and support elimination progra... by Angela Cadavid Restrepo, Colleen L Lau, Beatris Mario Martin, Helen J Mayfield

“…The most frequent model outputs were prevalence maps (17 studies, 27.9%), followed by risk maps based on environmental suitability (7 studies, 11.5%) and maps of the odds of seroprevalence being above a predetermined threshold (7 studies, 11.5%).Interpretation By demonstrating the applicability of spatial methods for investigating transmission drivers, identifying clusters and predicting hotspots, we highlight innovative ways in which spatial epidemiology has provided valuable evidence to support LF elimination. …”
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Application of Machine Learning and Multi-Dimensional Perception in Urban Spatial Quality Evaluation: A Case Study of Shanghai Underground Pedestrian Street by Tianning Yao, Yao Xu, Liang Sun, Pan Liao, Jin Wang

“…The study proposes a comprehensive and applicable spatial quality evaluation model integrating spatial quantification methods, machine learning algorithms, and multidimensional perception measurements. …”
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Enhancing Year-Round Thermal Comfort with Solar Control Films: A Solar-Adjusted and Spatial Assessment Considering Adaptive Clothing Behavior by Maureen De Gastines, Darío Jaime, Andrea E. Pattini

“…The methodology employs the Predicted Mean Vote adjusted via the SolarCal model and long-term comfort metrics to evaluate the effectiveness of Solar Control Films (SCFs) across twelve orientations at 30º intervals, in a cold arid (BWk) climate. …”
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Advanced satellite-based remote sensing and data analytics for precision water resource management and agricultural optimization by Awais Ali, Muhammad Yousuf Jat Baloch, Muhammad Naveed, Anam Nigar, Abdulrahman Seraj Almalki, Ayesha Ghulam Rasool, Meseret Abeje Gedfew, Ahmed A. Arafat

“…This manuscript reflects the multi-dimensional approach to synthesizes multi-index, multi-temporal remote sensing analysis to deliver both spatial and predictive insights. This multi-model fusion bridges the gap between biophysical water availability, vegetation health, land transition trends, and future irrigation scenarios, offering a more holistic and scalable solution for water-scarce regions, driven by climate change provides critical insights into the interplay of water supply, land suitability, and climate variability, offering a foundation for adaptive strategies that support food security, livelihoods, and environmental sustainability in vulnerable regions.…”
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A Binary Logistic Regression Model for Severe Convective Weather with Numerical Model Data by Guqian Pang, Jian He, Yuming Huang, Liuhong Zhang

“…Through analyzing the spatial distributions and the binary logistic regressions of the indexes, estimated values of the predictors and severe convective weather diagnostic prediction equations were established to get a severe weather predictor P for forecasting severe convective weather for the next 12 hours in Guangdong province. …”
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Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios. by Naser Shiri, Jalal Shiri, Zaher Mundher Yaseen, Sungwon Kim, Il-Moon Chung, Vahid Nourani, Mohammad Zounemat-Kermani

“…Among all the applied AI models, the developed hybrid support vector machine-firefly algorithm (SVM-FFA) model achieved the best predictability performance for both investigated scenarios. …”
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Data-Driven Modeling of Systemic Air Traffic Delay Propagation: An Epidemic Model Approach by Shanmei Li, Dongfan Xie, Xie Zhang, Zhaoyue Zhang, Wei Bai

“…The model can thus help managers as a tool to effectively predict the temporal and spatial evolution of air traffic delay.…”
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Machine learning approach for water quality predictions based on multispectral satellite imageries by Vicky Anand, Bakimchandra Oinam, Silke Wieprecht

“…The main objective of this study to retrieve and map the water quality parameters from Sentinel-2 and ResourceSat-2 [Linear Imaging Self-Scanning Sensor (LISS)–IV] multi-spectral satellite data, using Support Vector Machines (SVM), Random Forests (RF), and Multi-Linear regression (MLR) models. This study represents the first attempt to demonstrate the applicability and performance of high-spatial resolution ResourceSat-2 remote sensing satellite's LISS-4 sensor, which operates in three spectral bands in the Visible and Near Infrared Region (VNIR), to predict water quality. …”
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Deep learning-based InSAR time-series deformation prediction in coal mine areas by Chuanzeng Shu, Zhiguo Meng, Ying Yang, Yongzhi Wang, Shanjun Liu, Xiaoping Zhang, Yuanzhi Zhang

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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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Study on the influence mechanism of land use on carbon storage under multiple scenarios: A case study of Wenzhou by Quan Wei, Huang Xuankai, Xu Gang, Hao Jun, Lv Kangting, Jiang Xiaomin

“…An integrated framework based on the System Dynamics model, the Patch Generation Land Simulation model, and the Integrated Valuation of Ecosystem Services and Trade-offs model was constructed to dynamically simulate the LUCC demand and CS of Wenzhou under four scenarios in 2035, and to analyze the spatial evolution mechanisms of LUCC and CS. …”
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Park City 2035: Analysis of Policy-Driven Urban Expansion and Heat Island Effects Under Scenario Simulation by Rong Lin, Yujing Wu, Yuqiu Wu, Ran Wu, Jing Yang

“…Different urban development policies not only shape the evolution of urban spatial patterns but also have a profound impact on the urban heat island effect (UHI) and cooling benefits. …”
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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…The approaches' correlation value was nearly 0.99, indicating exceptional prediction accuracy. Up to 6 % perturbations were used to test the ANN model's performance, and it maintained its accuracy and robustness. …”
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The evaluation of Decision Plan Nets for bridging the gap between the ideal dwelling and the accepted dwelling by Roland Goetgeluk, Pieter Hooimeijer

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Pedestrian Trajectory Prediction Based on Transformer and Multi-relation Graph Convolutional Networks by LIU Guihong, ZHOU Zongrun, MENG Xiangfu

“…Pedestrian trajectories are highly random, dynamic, and influenced by their surroundings, necessitating the effective modeling of their temporal and spatial interactions. …”
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Species Distribution Modeling of Killer Whales (Orcinus orca) in Australian Waters by Marissa J. Hutchings, Guido J. Parra, John A. Totterdell, Rebecca Wellard, David M. Donnelly, Jonathan Sandoval‐Castillo, Luciana Möller

“…While research efforts have been made to study these animals, a broader understanding of their range and drivers of occurrence is lacking. In this study, we model the spatial distribution of killer whales in Australian waters to identify potential areas of habitat suitability and conservation priority. …”
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