Estimating small area population from health intervention campaign surveys and partially observed settlement data by Chibuzor Christopher Nnanatu, Amy Bonnie, Josiah Joseph, Ortis Yankey, Duygu Cihan, Assane Gadiaga, Hal Voepel, Thomas Abbott, Heather R. Chamberlain, Mercedita Tia, Marielle Sander, Justin Davis, Attila N. Lazar, Andrew J. Tatem

“…Abstract Effective governance requires timely and reliable small area population counts. Geospatial modelling approaches which utilise bespoke microcensus surveys and satellite-derived settlement maps and other spatial datasets have been developed to fill population data gaps in countries where censuses are outdated and incomplete. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…Subsequently, the center pixel coordinates of the bounding boxes predicted by the detection model were integrated with the yaw angle data recorded in the UAV's flight logs to construct an Euler angle rotation matrix. …”
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Monsoonal influence on particulate organic carbon variability through satellite data analysis by C.K. Tito, D.G. Bengen, T. Prartono, A. Damar, A.J. Wahyudi

“…This study aims to examine the spatial and temporal distribution of particulate organic carbon and to model its variance within Jakarta Bay, contributing to a deeper understanding of organic carbon dynamics in coastal ecosystems.METHODS: Monthly moderate-resolution imaging spectroradiometer satellite data for surface particulate organic carbon and chlorophyll-a during 2011 to 2023 periods were collected. …”
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Estimating Wheat Chlorophyll Content Using a Multi-Source Deep Feature Neural Network by Jun Li, Yali Sheng, Weiqiang Wang, Jikai Liu, Xinwei Li

“…Compared to the second-best model, the DNN (R² = 0.799, RMSE = 6.479, RRMSE = 18.23%), the MDFNN achieved a 6.4% increase in R², and 13.5% reductions in both RMSE and RRMSE. (3) The MDFNN exhibited strong robustness and adaptability across varying years, wheat varieties, and nitrogen application levels. …”
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Hypervelocity Stars Trace a Supermassive Black Hole in the Large Magellanic Cloud by Jiwon Jesse Han, Kareem El-Badry, Scott Lucchini, Lars Hernquist, Warren Brown, Nico Garavito-Camargo, Charlie Conroy, Re’em Sari

“…The predicted spatial and kinematic distributions of the simulated HVSs are remarkably similar to the observed distributions. …”
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Environmental factors influencing the odds of livestock predations by wolves in North–Eastern Italy across 10 years: a network analysis approach by Marcello Franchini, Salvatore Raniolo, Mirco Corazzin, Maurizio Ramanzin, Giulia Della Longa, Paolo Zanghellini, Natalia Bragalanti, Stefano Bovolenta

“…Large–scale data accessible to public institutions can help predict the temporal and spatial evolution of livestock predations by wolves. …”
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Analysing LULC transformations using remote sensing data: insights from a multilayer perceptron neural network approach by Khadim Hussain, Kaleem Mehmood, Sun Yujun, Tariq Badshah, Shoaib Ahmad Anees, Fahad Shahzad, Nooruddin, Jamshid Ali, Muhammad Bilal

“…The study highlights the effectiveness of the MLP-NN model in accurately predicting changes in LULC. The model’s exceptional accuracy and proficiency make it a powerful tool for future LULC forecasts. …”
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Characterization of 2D precision and accuracy for combined visual-haptic localization by Madeline Fischer, Umberto Saetti, Martine Godfroy-Cooper, Douglas Fischer

“…Overall, the lack of improvement in precision for bimodal cueing relative to the best unimodal cueing modality, vision, is in favor of sensory combination rather than optimal integration predicted by the Maximum Likelihood Estimation (MLE) model. …”
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Structure-guided deep learning for back acupoint localization via bone-measuring constraints by Yulong Wang, Tian Lan, Wenjian Dou, Zhi Chen, Song Zhang, Gong Chen, Gong Chen

“…The method employs an HRFormer backbone network combined with a Structure-Guided Keypoint Estimation Module (SG-KEM) and a structure-constrained loss function, ensuring anatomically consistent predictions within a standardized spatial coordinate system to improve accuracy across diverse body types. …”
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Rapid Disaster Data Dissemination and Vulnerability Assessment through Synthesis of a Web-Based Extreme Event Viewer and Deep Learning by P. Shane Crawford, Mohammad A. Al-Zarrad, Andrew J. Graettinger, Alexander M. Hainen, Edward Back, Lawrence Powell

“…Extracted building images were used to train a deep learning neural network to predict whether a building was elevated or nonelevated. …”
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Quantitative Vulnerability Assessment of Buildings Exposed to Landslides Under Extreme Rainfall Scenarios by Guangming Li, Dong Liu, Mengjiao Ruan, Yuhua Zhang, Jun He, Zizheng Guo, Haojie Wang, Mengchen Cheng

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Changes in forest ecosystem stability under climate change in a temperate landscape by Pavithra Rangani Wijenayake, Takuto Shitara, Akiko Hirata, Tetsuya Matsui, Tetsuya Matsui, Yasuhiro Kubota, Takashi Masaki

“…We hypothesize that even with the expected changes in climate, the structural stability of the species assembly will remain unchanged until the end of this century. We modeled the influence of climate change on the spatial distribution of major tree species in a temperate deciduous forest reserve using local and regional presence data. …”
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New approaches to unveil the unknown: oxygen depletion and internal eutrophication in a Baltic lagoon over decades by Gerald Schernewski, Gerald Schernewski, Thomas Neumann, Sarah Piehl, Mario von Weber

“…This approach allows us to assess the duration, spatial extent, and ecological impacts of oxygen depletion in the Oder/Szczecin Lagoon, located in the southern Baltic Sea. …”
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Ordinal METAR Cloud Cover Classification in Sentinel-2 Satellite Data by Markus Gotz, Erik Wessel, Ugur Cayoglu, Babak Jahani, Charlotte Debus, Jan Cermak, Achim Streit

“…This work proposes a novel approach for predicting cloud cover in global satellite images by leveraging ordinal point labels from ground-based weather stations, rather than relying on spatially resolved cloud masks, and demonstrates the effectiveness of this approach using a rank loss-based convolutional neural network of the EfficientNet family. …”
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A strontium (87Sr/86Sr) isoscape of Southern Ethiopia: implications for hominin land use and faunal mobility patterns by Seminew Asrat, Seminew Asrat, Francesco Lucchini, Mary Anne Tafuri, Caterina Aureli, Marina Gallinaro, Andrea Zerboni, Marianna Fusco, Enza E. Spinapolice

“…The results show that our novel baseline isoscape displayed heterogeneous 87Sr/86Sr isotope ratios in both the measured and predicted values (ranging from 0.703 to 0.712), consistent with geological units, with an accurate model performance evaluated through Leave-One-Out Cross-Validation (LOOCV) technique. …”
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Rice Disease Detection: TLI-YOLO Innovative Approach for Enhanced Detection and Mobile Compatibility by Zhuqi Li, Wangyu Wu, Bingcai Wei, Hao Li, Jingbo Zhan, Songtao Deng, Jian Wang

“…Finally, this study adopted the WIoUv3 loss function and added a dynamic non-monotonic aggregation mechanism to the standard IoU calculation to more accurately evaluate and penalize the difference between the predicted and actual bounding boxes, thus improving the robustness and generalization ability of the model. …”
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Sensitivity assessment and simulation of ecosystem services in response to land use change in arid regions: Empirical evidence from Xinjiang, China by Xiaoyun Li, Chunsheng Wu

“…An improved framework for assessing and simulating ecosystem services combining a modified equivalent factor method, a future land use simulation (FLUS) model, and a cross-sensitivity analysis is proposed. …”
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Transitional Housing and the Family Capacity Building Planner: An Urban Graduation Approach for Improving the Mental Health and Well-Being of Poor Households in Hong Kong by Siu-Ming Chan, Heng Xu, Yuen-Ki Tang, Kim Kwok, Ka-Man Leung

“…Together, these interventions address the multidimensional challenges of urban poverty while fostering sustainable improvements in residents’ capacity to achieve housing security and economic stability. (4) Conclusions: The integration of transitional housing with capacity-building services demonstrates the effectiveness of the Urban Graduation Approach in addressing urban poverty. This model highlights the importance of viewing housing not merely as a physical shelter but as a comprehensive infrastructure for well-being that combines spatial improvements with targeted social support. …”
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Harnessing InSAR and Machine Learning for Geotectonic Unit-Specific Landslide Susceptibility Mapping: The Case of Western Greece by Stavroula Alatza, Alexis Apostolakis, Constantinos Loupasakis, Charalampos Kontoes, Martha Kokkalidou, Nikolaos S. Bartsotas, Georgios Christopoulos

“…The gradient-boosted decision tree was employed in the landslide susceptibility mapping. The model was trained on three geotectonic units and five prefectures of Western Greece and performed well in predicting landslide events. …”
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Multi‑feature geological hazard susceptibility assessment by integrating improved ResNet and transfer learning: A case study of the Loess Plateau in Northern Shaanxi by Hao Cheng, Chong Xu, Rong Guo, Hai-kun Jing, Zeng-lin Hong, Feng-chen Fu, Ruo-shu Li

“…This study addressed the issues of insufficient feature utilization, poor spatial coherence, and weak generalization in conventional models for Geological hazard susceptibility assessment (GHSA) on the Loess Plateau in Northern Shaanxi. …”
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