Historical habitat mapping from black-and-white aerial photography: A proof of concept for post World War II Switzerland by Nica Huber, Matthias Bürgi, Christian Ginzler, Birgit Eben, Andri Baltensweiler, Bronwyn Price

“…Information regarding the spatial arrangement and extent of past habitats is important for understanding present biodiversity, restoration potential, and fighting extinction-debt effects. …”
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Rainfall forecasting in arid regions in response to climate change using ARIMA and remote sensing by Hany F. Abd-Elhamid, Amr M. El-Dakak, Martina Zeleňáková, Saleh O. K, Mohamed Mahdy, Samah H. Abd El Ghany

“…Climate changes in increasing at alarming rates which caused outward changes in the hydrological cycle parameters such as temperature and precipitation. The spatial and temporal distribution of rainfall has changed all over the world. …”
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Seasonal and Interannual Variations in Hydrological Dynamics of the Amazon Basin: Insights from Geodetic Observations by Meilin He, Tao Chen, Yuanjin Pan, Lv Zhou, Yifei Lv, Lewen Zhao

“…Results reveal pronounced spatial heterogeneity in the annual amplitude of TWS, exceeding 65 cm near the Amazon River and decreasing to less than 25 cm in peripheral mountainous regions. …”
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Control Performance and Preliminary Application Investigation of Novel Rotational Impact Dampers by SHEN Junjie, WANG Jingjing

“…Following the verification of the effectiveness of the numerical model and the correctness of the theoretical model, the numerical model of the RID was used for subsequent numerical simulation research. …”
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Coseismic crustal seismic velocity changes associated with the 2024 MW 7.5 Noto earthquake, Japan by Nicolas Paris, Yuji Itoh, Florent Brenguier, Qing-Yu Wang, Yixiao Sheng, Tomomi Okada, Naoki Uchida, Quentin Higueret, Ryota Takagi, Shin’ichi Sakai, Satoshi Hirahara, Shuutoku Kimura

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Estimation of Soil Salinity by Combining Spectral and Texture Information from UAV Multispectral Images in the Tarim River Basin, China by Jiaxiang Zhai, Nan Wang, Bifeng Hu, Jianwen Han, Chunhui Feng, Jie Peng, Defang Luo, Zhou Shi

“…Spatial distribution maps of soil salinity were then generated for each model. …”
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AAMS-YOLO: enhanced farmland parcel detection for high-resolution remote sensing images by Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang

“…To improve detection accuracy in these contexts, this study proposes AAMS-YOLO, a YOLO-based farmland parcel detection model. In the feature extraction stage, the model incorporates an Adaptive Mix Attention (AMA) Block, balancing robust feature extraction with low computational overhead through spatial mixing and Efficient Multi-Scale Attention (EMA). …”
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LoadSeer: Exploiting Tensor Graph Convolutional Network for Power Load Forecasting With Spatio-Temporal Characteristics by Jiahao Zhang, Bin Yu, Hanbin Lai, Lin Liu, Jinghui Zhou, Fengliang Lou, Yili Ni, Yan Peng, Ziheng Yu

“…Existing spatio-temporal prediction methods can only handle one factor in each dimension of time and space. …”
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Stacking data analysis method for Langmuir multi-probe payload by Jin Wang, Jin Wang, Duan Zhang, Qinghe Zhang, Qinghe Zhang, Xinyao Xie, Fangye Zou, Qingfu Du, Qingfu Du, V. Manu, Yanjv Sun

“…This study uses a stacking algorithm to process m-NLP data and incorporates the International Reference Ionosphere (IRI) model to correct the predicted electron density (Ne) values. …”
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Leveraging ResNet50 With Swin Attention for Accurate Detection of OCT Biomarkers Using Fundus Images by S. Tamilselvi, M. Suchetha, Rajiv Raman

“…Therefore, regular screening of diabetes patients for the early detection of retinal abnormalities is essential to prevent the development and progression of DR and DME. The proposed model predicts DME-associated biomarkers, typically identified in Optical Coherence Tomography (OCT), using 2D fundus images. …”
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A novel coal-rock recognition method in coal mining face based on fusing laser point cloud and images by Yang Liu, Lei Si, Zhongbin Wang, Miao Chen, Xin Li, Dong Wei, Jinheng Gu

“…Subsequently, the 2D target candidate box is calculated through the improved Mask R-CNN, and the frustum point cloud in the 2D target candidate box is extracted to reduce the calculation scale and spatial search range. Then, the self-attention PointNet is constructed to segment the fused point cloud within the frustum range, and the bounding box regression network is used to predict the bounding box parameters. …”
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Remote sensing reveals the role of forage quality and quantity for summer habitat use in red deer by Thomas Rempfler, Christian Rossi, Jan Schweizer, Wibke Peters, Claudio Signer, Flurin Filli, Hannes Jenny, Klaus Hackländer, Sven Buchmann, Pia Anderwald

“…Results The combination of vegetation indices and optical traits greatly improved predictive power in both the biomass (R2 = 0.60, Root mean square error (RMSE) = 88.55 g/m2) and relative nitrogen models (R2 = 0.34, RMSE = 0.28%). …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…This design reduces the computational complexity from quadratic to linear while preserving spatial context awareness. XFCOS enhances the original TSP-FCOS (Transformer-based Set Prediction with FCOS) model by integrating XFA into the transformer encoder, creating a CNN-ViT hybrid architecture, significantly reducing computational costs without sacrificing accuracy. …”
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Evaluation of 3D‐Var and 4D‐Var data assimilation on simulation of heavy rainfall events over the Indian region by Shivaji S. Patel, Ashish Routray, Vivek Singh, R. Bhatla, Rohan Kumar, Elena Surovyatkina

“…Similarly, it is found that satellite wind assimilation improved the statistical skill scores in predicting heavy precipitation in all three cases. Overall, the study suggested that the performance of the NCUM‐R model integrated with the 4D‐Var technique improved the model's forecast skill in the simulation of HREs.…”
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Evaluation of ground based spectral imaging for real time maize biomass monitoring by Andrea Szabó, Andrea Szabó, Nxumalo Gift Siphiwe, Nxumalo Gift Siphiwe, Erika Buday-Bódi, Erika Buday-Bódi, Blessing Ademola, János Tamás, János Tamás, Attila Nagy, Attila Nagy

“…Conversely, the chlorophyll prediction model showed improved accuracy, achieving an R² of 0.64, an MBE of 0.04 µg/g, and an NRMSE of 15.92%. …”
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The Origin of the Cluster of Local Interstellar Clouds by Catherine Zucker, Seth Redfield, Sara Starecheski, Ralf Konietzka, Jeffrey L. Linsky

“…Our model predicts that the formation of the individual CLIC clouds occurred progressively over the past 1 Myr and offers a natural explanation for the observed distribution, column density, temperature, and magnetic field structure of the complex.…”
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Toward skillful forecasting of super El Niño events using a diffusion-based westerly wind burst parameterization by Chaopeng Ji, Mu Mu, Bo Qin, Tao Lian, Shijin Yuan, Jie Feng, Xunshu Song, Yuntao Wei, Guokun Dai, Jinyu Wang, Xianghui Fang

“…The DDPM-based scheme effectively captures observed WWBs’ characteristics (e.g., frequency, intensity, and spatial center). When implemented in the Community Earth System Model, it outperforms both the control (CTRL, without WWBs parameterization) and conventional warm pool eastern edge (WPEE)-dependent parameterization in predicting intensity and seasonal phase-locking for super El Niños (1982/83, 1997/98, 2015/16). …”
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Dynamics of street environmental features and emotional responses in urban areas: implications for public health and sustainable development by Yangfei Huang, Yangfei Huang, Chenjian Zhong, Chenjian Zhong, Tangtao He, Yuyang Jiang

“…By integrating an emotion dataset assessed by 40 experts, a random forest model was constructed to predict emotional responses to different street spaces. …”
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Biomass distribution law of winter wheat in mining-affected area based on UAV remote sensing by Jing WANG, Wenbing GUO, Zhichao CHEN, Erhu BAI

“…The results show that: ① The selected vegetation indices and texture features were significantly correlated with biomass, and the combination of vegetation indices and texture features as input variables achieved the highest estimation accuracy. The SVR model had the highest prediction accuracy. ② Biomass in regions III (414–661 g/m2) and IV (662–822 g/m2) accounted for 66.4% of the total, indicating that most samples concentrated in the middle and high biomass range. …”
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Landscapes, habitat, and migratory behaviour: what drives the summer movements of a Northern viper? by Chloe R. Howarth, Christine A. Bishop, Karl W. Larsen

“…Migratory distance was best predicted by two top models: terrain and combined effects (including terrain, physiology, and vegetation factors). …”
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