Estimation of nitrogen uptake, biomass, and nitrogen concentration, in cover crop monocultures and mixtures from optical UAV images by Paolo Dal Lago, Nikolaos Vavlas, Lammert Kooistra, Gerlinde B. De Deyn

“…This innovative approach combined vegetation indices, textural features, and a photogrammetry-derived canopy surface model to predict CC traits. Linear models were trained for biomass, N uptake, and C:N predictions, while a K-Nearest-Neighbour model was trained for N concentration. …”
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Earth's future climate and its variability simulated at 9 km global resolution by J.-Y. Moon, J.-Y. Moon, J. Streffing, J. Streffing, J. Streffing, S.-S. Lee, S.-S. Lee, T. Semmler, T. Semmler, M. Andrés-Martínez, M. Andrés-Martínez, J. Chen, E.-B. Cho, E.-B. Cho, J.-E. Chu, C. L. E. Franzke, C. L. E. Franzke, J. P. Gärtner, R. Ghosh, J. Hegewald, J. Hegewald, S. Hong, D.-W. Kim, D.-W. Kim, N. Koldunov, J.-Y. Lee, J.-Y. Lee, Z. Lin, C. Liu, S. N. Loza, W. Park, W. Park, W. Roh, W. Roh, D. V. Sein, D. V. Sein, D. V. Sein, S. Sharma, S. Sharma, D. Sidorenko, J.-H. Son, J.-H. Son, J.-H. Son, M. F. Stuecker, Q. Wang, G. Yi, G. Yi, M. Zapponini, T. Jung, T. Jung, A. Timmermann, A. Timmermann

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Mapping Soil Available Nitrogen Using Crop-Specific Growth Information and Remote Sensing by Xinle Zhang, Yihan Ma, Shinai Ma, Chuan Qin, Yiang Wang, Huanjun Liu, Lu Chen, Xiaomeng Zhu

“…These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. …”
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A Fusion XGBoost Approach for Large-Scale Monitoring of Soil Heavy Metal in Farmland Using Hyperspectral Imagery by Xuqing Li, Huitao Gu, Ruiyin Tang, Bin Zou, Xiangnan Liu, Huiping Ou, Xuying Chen, Yubin Song, Wei Luo, Bin Wen

“…The optimal model was extended to the entire region for drawing the spatial distribution map of soil heavy metal content. …”
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Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating Malaria. by Freya M Shearer, Zhi Huang, Daniel J Weiss, Antoinette Wiebe, Harry S Gibson, Katherine E Battle, David M Pigott, Oliver J Brady, Chaturong Putaporntip, Somchai Jongwutiwes, Yee Ling Lau, Magnus Manske, Roberto Amato, Iqbal R F Elyazar, Indra Vythilingam, Samir Bhatt, Peter W Gething, Balbir Singh, Nick Golding, Simon I Hay, Catherine L Moyes

“…<h4>Methodology/principal findings</h4>A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. …”
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Lessons learned from the co-development of operational climate forecast services for vineyards management by N. Pérez-Zanón, V. Agudetse, E. Baulenas, P.A. Bretonnière, C. Delgado-Torres, N. González-Reviriego, A. Manrique-Suñén, A. Nicodemou, M. Olid, Ll. Palma, M. Terrado, B. Basile, F. Carteni, A. Dente, C. Ezquerra, F. Oldani, M. Otero, F. Santos-Alves, M. Torres, J. Valente, A. Soret

“…If the skill is negative, which means there is no proof of the added value of using the numerical model prediction, the bars are blurred, and the user can still be informed of the tercile category limits.The service has been provided for almost two consecutive years. …”
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Estimation of Strawberry Canopy Volume in Unmanned Aerial Vehicle RGB Imagery Using an Object Detection-Based Convolutional Neural Network by Min-Seok Gang, Thanyachanok Sutthanonkul, Won Suk Lee, Shiyu Liu, Hak-Jin Kim

“…Therefore, this study evaluated the spatial variability of strawberry canopy volumes using a ResNet50V2-based convolutional neural network (CNN) model trained with RGB images acquired through manual unmanned aerial vehicle (UAV) flights equipped with a digital color camera. …”
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Optimizing rural waste management: Leveraging high-resolution remote sensing and GIS for efficient collection and routing by Xi Cheng, Jieyu Yang, Zhiyong Han, Guozhong Shi, Deng Pan, Likang Meng, Zhuojun Zeng, Zhanfeng Shen

“…Notably, when compared to our field survey data, the optimized daily collection route in a rural context decreased from 256.40 km before optimization to 140.44 km, reflecting a substantial reduction of 45.23% in total distance. This study furnishes an effective model that relies solely on information from remote-sensing images for efficient rural waste collection and extends invaluable insights to planners and administrators in the realm of rural and township waste management.…”
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Beyond traditional methods: Innovative integration of LISS IV and Sentinel 2A imagery for unparalleled insight into Himalayan ibex habitat suitability. by Ritam Dutta, Lalit Kumar Sharma, Bheem Dutt Joshi, Vineet Kumar, Amira Sharief, Saurav Bhattacharjee, Mukesh Thakur, Dhriti Banerjee, Rajappa Babu

“…The integrated image demonstrated superior accuracy in predicting the suitable habitat for the species. The identification of suitable habitats was found to be contingent upon the consideration of two key factors: the Soil Adjusted Vegetation Index and elevation. …”
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CINet: A Constraint- and Interaction-Based Network for Remote Sensing Change Detection by Geng Wei, Bingxian Shi, Cheng Wang, Junbo Wang, Xiaolin Zhu

“…Remote sensing change detection (RSCD), which utilizes dual-temporal images to predict change locations, plays an essential role in long-term Earth observation missions. …”
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Spatiotemporal mapping of major trauma in Victoria, Australia. by Ben Beck, Andrew Zammit-Mangion, Richard Fry, Karen Smith, Belinda Gabbe

“…<h4>Background</h4>Spatiotemporal modelling techniques allow one to predict injury across time and space. …”
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Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…A back-propagation (BP) neural network models and predicts how structural parameters impact the acoustic transmission coefficient, elucidating the effects of geometric variations. …”
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Maintaining a cognitive map in darkness: the need to fuse boundary knowledge with path integration. by Allen Cheung, David Ball, Michael Milford, Gordon Wyeth, Janet Wiles

“…The model replicates published experimental results on place field and grid field stability without vision, and makes testable predictions including place field splitting and grid field rescaling if the true arena geometry differs from the acquired boundary map. …”
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Detection of Indoor Building Lighting Fixtures in Point Cloud Data using SDBSCAN by Humairah Mansor, Shazmin Aniza Abdul Shukor, Razak Wong Chen Keng, Nurul Syahirah Khalid

“…Building fixtures like lighting are very important to be modelled, especially when a higher level of modelling details is required for planning indoor renovation. …”
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MC-ASFF-ShipYOLO: Improved Algorithm for Small-Target and Multi-Scale Ship Detection for Synthetic Aperture Radar (SAR) Images by Yubin Xu, Haiyan Pan, Lingqun Wang, Ran Zou

“…Furthermore, comparative experiments show that our method outperforms mainstream models. Even under high-confidence thresholds, MC-ASFF-ShipYOLO is capable of predicting more high-quality detection boxes, offering a valuable solution for advancing SAR ship detection technology.…”
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Weed Types and Dynamics Associations with Catena Landscape Positions: Smallholder Farmers’ Knowledge and Perception in Zimbabwe by Justin Chipomho, Simbarashe Tatsvarei, Cosmas Parwada, Arnold Bray Mashingaidze, Joyful T. Rugare, Stanford Mabasa, Regis Chikowo

“…The data were coded and processed using the CSPro software package, and then analysed using the SPSS program. Factors that predicted the spatial distribution of weeds were determined using a binary logistic model. …”
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Effects of solar radiation modification on precipitation extremes in Southeast Asia: Insights from the GeoMIP G6 experiments by Ze-Qian Feng, Mou Leong Tan, Liew Juneng, Mari R. Tye, Li-Li Xia, Fei Zhang

“…In conclusion, SRM may effectively mitigate increases in extreme precipitation events in most of Southeast Asia, but G6solar provides a more consistent reduction, while G6sulfur shows more complex spatial responses.…”
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Harnessing Multi-Source Data and Deep Learning for High-Resolution Land Surface Temperature Gap-Filling Supporting Climate Change Adaptation Activities by Katja Kustura, David Conti, Matthias Sammer, Michael Riffler

“…This method not only preserves ECOSTRESS’s native resolution but also fills data gaps and enhances spatial and temporal coverage. In non-gap areas validated against ground truth ECOSTRESS data, the model achieves LST predictions with at least 80% of all pixel errors falling within a ±3 °C range. …”
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Advances in soil salinity diagnosis for mangrove swamp rice production in Guinea Bissau, West Africa by Gabriel Garbanzo, Jesus Céspedes, Marina Temudo, Maria do Rosário Cameira, Paula Paredes, Tiago Ramos

“…Silt raster, normalized salinity index (NDSI), and normalized difference water index (NDWI) were the main contributors in the predicted data for soil electrical conductivity of the saturation paste extract (ECe, dS m−1). …”
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Neuromorphic imaging cytometry on human blood cells by Ziyao Zhang, Haoxiang Yang, Jiayin Li, Shin Wei Chong, Jason K Eshraghian, Ken-Tye Yong, Daniele Vigolo, Helen M McGuire, Omid Kavehei

“…The proposed architecture has achieved a promising performance of 97% accuracy and F1 score with a significant reduction in computation requirements. Combining the data sparsity in neuromorphic imaging with a lightweight DL model and operation platform can enable next-generation, AI-driven cytometry to deliver point-of-care diagnostic and research solutions.…”
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