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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Estimates of Lake Nitrogen, Phosphorus, and Chlorophyll‐a Concentrations to Characterize Harmful Algal Bloom Risk Across the United States by Meredith M. Brehob, Michael J. Pennino, Amalia M. Handler, Jana E. Compton, Sylvia S. Lee, Robert D. Sabo

“…We then used these RF models to extrapolate lake TN and TP predictions to lakes without nutrient observations and predict chlorophyll‐a for ∼112,000 lakes across the CONUS. …”
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Potential of solar-induced chlorophyll fluorescence for monitoring long-term dynamics of soil salinity in Central Asia the Xinjiang Region China by Kuangda Cui, Kuangda Cui, Jianli Ding, Jianli Ding, Jinjie Wang, Jinjie Wang, Jiao Tan, Jiao Tan, Lijing Han, Jiangtao Li, Jiangtao Li

“…Model performance, seasonal sensitivity, and spatial variation were analyzed across Central Asian countries and Xinjiang.ResultsSIF effectively detected salinization dynamics, with highest sensitivity in Kazakhstan and Xinjiang. …”
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Spatiotemporal hybrid deep learning for estimating and analyzing carbon stocks: a case study in Jiangsu province, China by Lizhi Miao, Jvmin Wang, Kaiwen Wu, Heng Xu, Xiying Sun, Gang Lu, Mei-Po Kwan

“…The model demonstrated excellent performance in predicting carbon (R2 = 0.91, 10-fold CV R2 = 0.80). …”
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Interface Thermal Conductance of Nonequilibrium Thermal Transport across Nanoscale Metal Multilayers by Donghao Li, Zhongyin Zhang, Ziyang Wang, Gen Li, Jing Zhou, Jie Zhu, Dawei Tang

“…These experiment results revealed that nonequilibrium ITC at the Au/Cr interface closely matched the predicted value of 6 GW m−2 K−1 by the electronic diffuse mismatch model, which captures ultrafast thermal behavior within the first few picoseconds following femtosecond laser heating. …”
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HO 2 Generation Above Sprite‐Producing Thunderstorms Derived from Low‐Noise SMILES Observation Spectra by T. Yamada, T. O. Sato, T. Adachi, H. Winkler, K. Kuribayashi, R. Larsson, N. Yoshida, Y. Takahashi, M. Sato, A. B. Chen, R. R. Hsu, Y. Nakano, T. Fujinawa, S. Nara, Y. Uchiyama, Y. Kasai

“…A total of three areas was identified with enhanced HO 2 levels of approximately 10 25 molecules. A chemical sprite model indicates an increase in HO 2 in the considered altitude region; however, the predicted production due to a single sprite event is smaller than the observed enhancement. …”
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Mapping the groundwater potential zones in mountainous areas of Southern China using GIS, AHP, and fuzzy AHP by Meng Chen, Shuangxi Zhang, Shengbo Liu, Mengkui Li, Tao Zhang, Tengfei Wu, Xiangyu Bu

“…The model performance was validated using borewell data, receiver operating characteristic (ROC) curves, and yield prediction models. …”
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TraxVBF: A hybrid transformer-xLSTM framework for EMG signal processing and assistive technology development in rehabilitation by Seyyed Ali Zendehbad, Athena Sharifi Razavi, Marzieh Allami Sanjani, Zahra Sedaghat, Saleh Lashkari

“…This allows the model to predict movement trajectories accurately, enabling motor learning and functional recovery of patients through real time feedback without the expensive hardware. …”
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Estimating latent heat flux of subtropical forests using machine learning algorithms by Harekrushna Sahu, Pramit Kumar Deb Burman, Palingamoorthy Gnanamoorthy, Qinghai Song, Yiping Zhang, Huimin Wang, Yaoliang Chen, Shusen Wang

“…This study highlights the robustness of support vector regression and accentuates the impact of climatic and environmental conditions on model performance, ultimately contributing to more precise predictions of latent heat flux.…”
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Integration of Drone and Satellite Imagery Improves Agricultural Management Agility by Michael Gbenga Ogungbuyi, Caroline Mohammed, Andrew M. Fischer, Darren Turner, Jason Whitehead, Matthew Tom Harrison

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C-Band Radar-Based Improved Snow Depth Estimation (C-RISE) in the Indian Western Himalayas and Colorado Rocky Mountains by R. Chandra Prabha, Srinivasarao Tanniru, RAAJ Ramsankaran

“…Monitoring snow depth (SD) in mountainous regions is essential for water resource management, climate studies, and disaster predictions. Synthetic aperture radar (SAR)-based remote sensing, with its high spatial resolution and penetration capability, is more suited for such areas. …”
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Radial Flow Component of Sun’s High-frequency Retrograde Inertial Waves by Chris S. Hanson, Vivek Menon, Shravan Hanasoge, Katepalli R. Sreenivasan

“…We demonstrate that this signal is indeed part of the HFR modes and not spatial leakage from prograde flows associated with magnetic regions. …”
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Risk analysis of distribution network outages under a typhoon–rainstorm–flood disaster chain by Hui Hou, Wenjie Wu, Ruizeng Wei, Huan He, Lei Wang, Zhengtian Li, Xiangning Lin

“…Second, a one‐dimensional pipe network and a two‐dimensional surface‐coupled urban flood model are constructed to predict flood depth based on the typhoon–rainstorm time series. …”
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Prediciendo el crimen en ciudades intermedias: un modelo de “machine learning” en Bucaramanga, Colombia by Juan David Gelvez Ferreira, María-Paula Nieto-Rodríguez, Carlos-Andrés Rocha-Ruiz

“…The results show that the best crime prediction outcomes were obtained when using the models with spatial relationships of graphs by weeks. …”
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Dual Graph for Traffic Forecasting by Long Wei, Zhengxu Yu, Zhongming Jin, Liang Xie, Jianqiang Huang, Deng Cai, Xiaofei He, Xian-Sheng Hua

“…It is challenging due to the complex spatial-temporal correlation on road networks. Most existing research works use sequential Graph Neural Networks (GNN) to model traffic inference. …”
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Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit by Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

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Tree species classification using intensity patterns from individual tree point clouds by Andreas Tockner, Ralf Kraßnitzer, Christoph Gollob, Sarah Witzmann, Tim Ritter, Arne Nothdurft

“…However, recent studies assessing tree species labels on single tree point clouds have been insufficiently accurate in complex forest ecosystems; moreover, explainability of machine-learning methods used in published studies has been insufficient. Whether the predictions of black-box models suffer from over-fitting or whether they are based on characteristic species traits often remains unclear. …”
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Monitoring sub-arctic wetland vegetation using nested scales of spectrometry to inform multiple endmember spectral unmixing of Sentinel-2A imagery by Heidi Cunnick, Joan M Ramage, Dawn Magness, Stephen C Peters

“…We develop a bottom–up reference library for unmixing based on nested scales of data beginning with the highest resolution of a ground collected handheld spectral measurements, progressing to 1 m ^2 resolution using fused hyperspectral-LiDAR data, and then subsequently map predictively at the spatial resolution of the 10 m ^2 multi-spectral imagery of the European Space Agency’s Sentinel-2A. …”
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Trends of Desertification Change and Its Driving Factors in Aksu Region by Zheng Jiaxiang, Sun Guili, Su Xiangling, Ran Yajun, Zheng Xu

“…The mode and intensity of action showed enhancement and non-linear enhancement, respectively. ③ The prediction results from the CA-Markov model showed that if the driving factors did not change, the degree of desertification in the Aksu region would continue to reverse during 2019—2024, and the overall change for the area would be from extremely severe desertification to severe desertification. …”
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Retrospective evaluation of Facial nerve monitoring to prevent nerve damage during robotic drilling in the largest series of patients undergoing the HEARO-procedure. by Jaouad Abari, Marco Matulic, Pablo Galeazzi, Masoud Zoka Assadi, Paul Van de Heyning, Vedat Topsakal

“…Linear regression was used to determine if the minimum stimulation thresholds (FNM) could significantly predict the intra-operative distance (CBCT) between the drilled trajectory and the facial nerve. …”
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