Landscape Pattern Changes and Ecological Vulnerability Assessment in Mountainous Regions: A Multi-Scale Analysis of Heishui County, Southwest China by Weiqi Gu, Hong Fu, Wen Jin

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Quantitative inversion of integrated hyperspectral and optical remote sensing images to monitor dust distribution in open pit mines by Simin Feng, Jin Zhang

“…The ZY1-02E satellite demonstrates high feasibility and accuracy in AOD inversion, and the results obtained effectively illustrate the spatial distribution of dust pollution. This highlights the potential for aerosol remote sensing inversion using hyperspectral satellite data, providing effective means for regional dust monitoring, and a scientific basis for subsequent development of dust reduction measures.…”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

“…The results show that this machine learning method can effectively eliminate the interference fringes in the IR spectrum, and complete the feature selection and dimensionality reduction of the high-dimensional spectral data. The 63 kinds of greases exhibit spatial clustering under certain IR spectrum recognition spectral bands, which are linked to characteristic peaks of lubricating greases and improve the recognition accuracy of these greases. …”
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Spatiotemporally weighted regression (STWR) for assessing Lyme disease and landscape fragmentation dynamics in Connecticut towns by Zhe Wang, Xiang Que, Meifang Li, Zhuoming Liu, Xun Shi, Xiaogang Ma, Chao Fan, Yan Lin

“…The integration of data-driven and model-driven approaches in this study delivers a robust framework that combines empirical pattern detection with theoretical insight, enhancing the robustness and predictive power of ecological studies.…”
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An Improved Wavelet Soft-Threshold Function Integrated with SVMD Dual-Parameter Joint Denoising for Ancient Building Deformation Monitoring by Jiaxing Zhao, Houzeng Han, Yang Deng, Youqiang Dong, Jian Wang, Wenjin Chen

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Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders by M. G. A. Hendrickx, M. G. A. Hendrickx, J. Vanderborght, J. Vanderborght, P. Janssens, P. Janssens, P. Janssens, S. Bombeke, E. Matthyssen, A. Waverijn, J. Diels, J. Diels

“…These results demonstrate that the common assumption of uncorrelated random errors to determine parameter and model prediction uncertainty is not valid when measurements from sparse in situ soil moisture sensors are used to parameterize soil hydrological models. …”
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Evaluation of Physics‐Based Data Assimilation System Driven by Neutral Density Data From a Single Satellite by Dexin Ren, Jiuhou Lei

“…The data assimilation approach that is based on the self‐consistent upper‐atmosphere model may provide better predictive capability of the coupled thermosphere system. …”
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The use and integration of airborne laser scanning and satellite time series data in precision forest management for plantations of fast-growing tree species by Gonzalo Gavilan-Acuna, Nicholas C. Coops, Piotr Tompalski, Dominik Roeser, Andrés Varhola

“…Conclusion Despite progresses, challenges remain in refining predictive models, expanding remote sensing applications, and developing tools that translate complex data into field operations. …”
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Analysis of The State of The Tourism Industry in Russia аnd The Direction of Its Development by P. G. Nikolenko, A. M. Terekhov

“…Based on the Box–Jenkins methodology, predictive models were created and medium-term forecasts were calculated for variables characterizing the number of tourist firms and the number of sanatorium-resort organizations and recreation organizations. …”
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Relating natural image statistics to patterns of response covariability in macaque primary visual cortex by Amirhossein Farzmahdi, Adam Kohn, Ruben Coen-Cagli

“…As a result, the model predicts that increasing the size of an image reduces correlations for pairs with overlapping receptive fields and increases correlations for pairs with offset receptive fields. …”
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Estimating Rainfall Erosivity in North Korea Using Automated Machine Learning: Insights into Regional Soil Erosion Risks by Jeongho Han, Seoro Lee

“…Using the optimized model, RE in North Korea was estimated, and the spatial distribution of RE was analyzed using the Kriging interpolation. …”
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Optimal control prevents itself from eradicating stochastic disease epidemics. by Rachel Russell, Nik J Cunniffe

“…Using Model Predictive Control, in which the optimisation is performed repeatedly as the system evolves to correct for deviations from the optimal control predictions, improves performance but the level of control calculated at each repeated optimisation is still insufficient. …”
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An Upscaling-Based Strategy to Improve the Ephemeral Gully Mapping Accuracy by Solmaz Fathololoumi, Daniel D. Saurette, Harnoordeep Singh Mann, Naoya Kadota, Hiteshkumar B. Vasava, Mojtaba Naeimi, Prasad Daggupati, Asim Biswas

“…The overall classification error of the upscaling strategy at spatial resolutions of 0.6, 2, 4, 6, 8, and 10 m (Upscaled), as well as that of the direct Sentinel-2 model, were 7.9%, 8.2%, 9.1%, 10.3%, 11.2%, 12.5%, and 14.5%, respectively. …”
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Digital twin-enabled post-disaster damage and recovery monitoring with deep learning: leveraging transfer learning, attention mechanisms, and explainable AI by Umut Lagap, Saman Ghaffarian

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Earthquake Recurrence Estimates for Northern Caribbean Faults from Combinatorial Optimization by Uri S. ten Brink, Eric L. Geist

“…Because of our system-modeling approach, such a configuration predicts less frequent earthquakes on EF and western Hispaniola and Muertos convergent zones. …”
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Efficient remote sensing image classification using the novel STConvNeXt convolutional network by Bo Liu, Chenmei Zhan, Cheng Guo, Xiaobo Liu, Shufen Ruan

“…Ablation studies further confirm the effectiveness of each module design, particularly demonstrating that the model maintains excellent classification accuracy despite a substantial reduction in parameters.…”
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Soil Carbon Remote Sensing: A Meta-Analysis and Systematic Review of Published Results from 1969–2022 by Savannah L. McGuirk, Iver H. Cairns

“…There is no other evidence to suggest that prediction models prepared with multispectral data perform worse than other models, however. …”
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Approach to analysis of inter-regional similarity of investment activity support measures in legislation of regions (on the example of Krasnoyarsk region) by Valentina F. Lapo

“…The proximity coefficient matrix will be especially useful in spatial econometric models. The offered approach and parameters can be applied to research the other positions of the regional legislation.…”
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Deployment and Operation of Battery Swapping Stations for Electric Two-Wheelers Based on Machine Learning by Yu Feng, Xiaochun Lu

“…Then, on a 3000 m grid scale, a prediction model of BSS quantity with random forest, support vector regression, and gradient-boosting decision tree algorithm was built. …”
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Long short-term memory exploitation of satellite gravimetry to infer floods by Omid Memarian Sorkhabi, Joseph Awange

“…Flood forecasting is a vital segment of disaster risk management in that it contributes to the prediction of the magnitude, occurrence, duration and timing of floods. …”
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