High-Resolution Mapping of Litter and Duff Fuel Loads Using Multispectral Data and Random Forest Modeling by Álvaro Agustín Chávez-Durán, Miguel Olvera-Vargas, Inmaculada Aguado, Blanca Lorena Figueroa-Rangel, Ramón Trucíos-Caciano, Ernesto Alonso Rubio-Camacho, Jaqueline Xelhuantzi-Carmona, Mariano García

“…Moreover, the relative root mean squared errors were 33.75% for litter and 27.71% for duff fuel loads, with a relative bias of less than 5% for litter and less than 20% for duff fuel loads. The spatial distribution of the litter and duff fuel loads was coherent with the structure of the vegetation, despite the high complexity of the study area. …”
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Spatial Distribution Pattern of Forests in Yunnan Province in 2022: Analysis Based on Multi-Source Remote Sensing Data and Machine Learning by Guangyang Li, Hongyan Lai, Bangqian Chen, Xiong Yin, Weili Kou, Zhixiang Wu, Zongzhu Chen, Guizhen Wang

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Explosion Resistance of Three-Dimensional Mesoscopic Model of Complex Closed-Cell Aluminum Foam Sandwich Structure Based on Random Generation Algorithm by Zhen Wang, Wen Bin Gu, Xing Bo Xie, Qi Yuan, Yu Tian Chen, Tao Jiang

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Example of Structure Modeling and Analysis of Ultrasound Scattering for Trabecular Bone by Janusz WÓJCIK, Jerzy LITNIEWSKI, Andrzej NOWICKI

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Single-Shot, Monochrome, Spatial Pixel-Encoded, Structured Light System for Determining Surface Orientations by Ahsan Elahi, Qidan Zhu, Jun Lu, Umer Farooq, Ghulam Farid, Muhammad Bilal, Yong Li

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A Marginal Maximum Likelihood Approach for Hierarchical Simultaneous Autoregressive Models with Missing Data by Anjana Wijayawardhana, David Gunawan, Thomas Suesse

“…This complexity applies when the spatial weight matrix is constructed based on a local neighbourhood structure. …”
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Spatial association characteristics and evolutionary mechanisms of water pollution in China: A network structure dependence perspective by Ning Zhang, Hongjie Liu, Hongji Dong, Zhijie Cao, Ruoxin Zhan

“…This has led to the emergence of a more complex and multilayered GWF spatial association network. …”
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Hybridizing spatial machine learning to explore the fine-scale heterogeneity between stunting prevalence and its associated risk determinants in Rwanda by Gilbert Nduwayezu, Ali Mansourian, Jean Pierre Bizimana, Petter Pilesjö

“…Childhood stunting is a serious global public health issue that exhibits local spatial variations. Previous studies have used traditional statistical methods to identify stunting risk factors, and little is known about the application and usefulness of spatial machine learning techniques in identifying localized stunting risk factors based on complex datasets. …”
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Cost-Efficient RSSI-Based Indoor Proximity Positioning, for Large/Complex Museum Exhibition Spaces by Panos I. Philippopoulos, Kostas N. Koutrakis, Efstathios D. Tsafaras, Evangelia G. Papadopoulou, Dimitrios Sigalas, Nikolaos D. Tselikas, Stefanos Ougiaroglou, Costas Vassilakis

“…RSSI data, temporal and spatial management with simple low-processing methods adopted, achieved a maximum prediction accuracy average of 81.53% across all datasets, while ML algorithms (Random Forest) achieved a maximum prediction accuracy average of 87.24%.…”
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On Hierarchical Bayesian Spatial Small Area Model for Binary Data under Spatial Misalignment by Kindie Fentahun Muchie, Anthony Kibira Wanjoya, Samuel Musili Mwalili

“…Model-based Bayesian analysis is popular for its ability to combine information from several sources as well as taking account uncertainties in the analysis and spatial prediction of spatial data. Nevertheless, things become more complex when the geographic boundaries of interest are misaligned. …”
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Analyzing the Impact of Land-Use Characteristics and Demographic Factors on Spatial Variations in Public Bus Usage: A Comparison of Pre- and During COVID-19 Periods by Sukchan Hong, Byungyun Yang

“…The geographical random forest method, an advanced variant of the random forest model, integrates spatial concepts to explain local patterns more effectively than traditional machine learning techniques. …”
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PROPERTIES OF NETWORKS BUILT ON DIGITAL IMAGES by Oleh Kushnir, Oleksiy Kravchuk, Volodymyr Franiv

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Multi-target detection and tracking based on CRF network and spatio-temporal attention for sports videos by Xi Chen, Hui Zhang, Achyut Shankar, Bharat Bhushan, Kireet Joshi

“…In addition, we also introduce local adaptive filters and spatial-temporal attention mechanisms into this framework to further improve target detection performance, especially when dealing with complex scenes and target interactions. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…The results reveal the following: (1) NTU and EER levels steadily improved from 2004 to 2022, although coordination between cities still requires enhancement; (2) CCD exhibited a temporal pattern of “progressive escalation and continuous optimization,” and a spatial pattern of “dual-core leadership and regional diffusion,” with most cities shifting from NTU-lagged to synchronized development; (3) environmental regulations (MAR) and fixed asset investment (FIX) emerged as the most influential CCD drivers, and significant nonlinear interactions were observed, particularly those involving population size (HUM); (4) CCD drivers exhibited complex spatiotemporal heterogeneity, characterized by “stage dominance—marginal variation—spatial mismatch.” …”
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Park Development, Potential Measurement, and Site Selection Study Based on Interpretable Machine Learning—A Case Study of Shenzhen City, China by Haihong Li, Li He

“…Aiming at the lack of systematic consideration in the traditional park siting research, this study utilizes geographically weighted regression to explore the various characteristic factors affecting the spatial distribution of parks, and based on this, combines the random forest model and the interpretable model to accurately assess the potential of parks on urban land in Shenzhen and provide the basis for site selection. …”
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The Effective Healing Strategy against Localized Attacks on Interdependent Spatially Embedded Networks by Kai Gong, Jia-Jian Wu, Ying Liu, Qing Li, Run-Ran Liu, Ming Tang

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Exploiting spatial dimensions to enable parallelized continuous directed evolution by Ting Wei, Wangsheng Lai, Qian Chen, Yi Zhang, Chenjian Sun, Xionglei He, Guoping Zhao, Xiongfei Fu, Chenli Liu

“…Abstract Current strategies to improve the throughput of continuous directed evolution technologies often involve complex mechanical fluid‐controlling system or robotic platforms, which limits their popularization and application in general laboratories. …”
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SPATIAL MODELING OF POVERTY IN BENGKULU PROVINCE WITH MIXED GEOGRAPHICALLY WEIGHTED REGRESSION by Sigit Nugroho, Dyah Setyo Rini, Tommy Jomecho, Cinta Rizky Oktarina, Stevy Cahya Pratiwi, Elisabeth Evelin Karuna

“…Spatial dependency occurs due to spatial error correlation in cross section data, while spatial heterogeneity occurs due to random area effects, which is the difference between one region and another. …”
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The study of the effectiveness and safety of vitamin-mineral complex «Focus Forte» for myopia treatment by E. Yu. Egorova, N. V. Yudina, I. Yu. Torshin, O. A. Gromova, N. N. Slyshalova

“…Purpose: the estimation of the results of a randomized study of the effectiveness of vitamin-mineral complex «Focus Forte» at myopia.Methods: this study included 60 young patients (in age from 16 to18 years, university students, full-time education) in the context of complex treatment within 2 months. …”
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Measurement of spatial heterogeneity in street restorative perceptions and street refinement design by Yalun Lei, Qingqing Li, Jingwen Tian, Jia Hu, Jixiang Jiang

“…Among the regression models, the MGWR model achieved the highest R 2 value (0.615), indicating that variables like trees, roads, sidewalks, and intercepts are particularly sensitive to spatial heterogeneity. Additionally, space syntax analysis underscores the positive impact of complex street networks on accessibility, convenience, and environmental satisfaction. …”
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