Landsat Next current design for geological remote sensing: VNIR-SWIR-TIR data continuity and new opportunities by Bruno Portela, Harald van der Werff, Christoph Hecker, Mark van der Meijde

“…By adapting established band ratios and applying spectral-only and spectral-spatial resampling when simulating Landsat Next data, we isolate the influence of Landsat Next's band configuration and resolution.Our results confirm that Landsat Next replicates key mineralogical patterns observed in Sentinel-2 and ASTER products. …”
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National-scale tree species mapping with deep learning reveals forest management insights in Germany by Yang Mu, Jianhua Guo, Muhammad Shahzad, Xiao Xiang Zhu

“…In addition, climatic factors, especially water deficit, are shown to play a very important role in determining tree species distribution patterns, followed by topographic and soil factors. …”
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Unraveling Phenological Dynamics: Exploring Early Springs, Late Autumns, and Climate Drivers Across Different Vegetation Types in Northeast China by Jiayu Liu, Haifeng Zou, Yinghui Zhao, Xiaochun Wang, Zhen Zhen

“…This study generated 4-day, 500 m land surface phenology (LSP) in Northeast China (NEC) from 2001 to 2021 using interpolated and Savitzky–Golay filtered kernel normalized difference vegetation index (kNDVI) derived from MODIS. Spatial patterns, trends, and climate responses of phenology were analyzed across ecoregions and vegetation. …”
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Explaining the Mechanism of Multiscale Groundwater Drought Events: A New Perspective From Interpretable Deep Learning Model by Hejiang Cai, Haiyun Shi, Zhaoqiang Zhou, Suning Liu, Vladan Babovic

“…Two interpretation methods, expected gradients (EG) and additive decomposition (AD), are adopted to decipher the DL‐captured patterns and inner workings of LSTM networks. The EG results show that: (a) temperature‐related features were the primary drivers of large‐scale groundwater droughts, with their importance increasing from 56.1% to 63.1% as the drought events approached from 6 months to 15 days. …”
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An atlas of neuropathic pain-associated molecular pathological characteristics in the mouse spinal cord by Fu-Lu Dong, Lina Yu, Pei-Da Feng, Jin-Xuan Ren, Xue-Hui Bai, Jia-Qi Lin, De-Li Cao, Yu-Tao Deng, Yan Zhang, Hui-Hui Shen, Hao Gong, Wen-Xing Sun, Dong-Qiu Chi, Yixiao Mei, Longfei Ma, Ming-Zhe Yin, Meng-Na Li, Peng-Fei Zhang, Nan Hu, Bing-Lin Zhou, Ying Liu, Xuan-Jie Zheng, Yi-Fan Chen, Da Zhong, Yuan-Xiang Tao, Min Yan, Bao-Chun Jiang

“…However, our understanding of the NP-associated spatial molecular processing landscape of SC and the non-synaptic interactions between DRG neurons and SC cells remains limited. …”
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Pelagic fish camouflage in shallow waters from the humboldt current system through intracellular structures and reflectance mechanisms by Caroline S. Montes, Ricardo F. Soto, Mario I. Sanhueza, Ignacio Sanhueza, Danny Luarte, Sebastián E. Godoy, Sergio N. Torres, Rosario Castillo, Rubén Escribano, Mauricio A. Urbina

“…These Scanning Electron Microscopy (SEM) images were analyzed using the 2D discrete Fourier transform to extract the spatial patterns that govern the light interaction with the guanine crystal structures. …”
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A Hybrid Model for Soybean Yield Prediction Integrating Convolutional Neural Networks, Recurrent Neural Networks, and Graph Convolutional Networks by Vikram S. Ingole, Ujwala A. Kshirsagar, Vikash Singh, Manish Varun Yadav, Bipin Krishna, Roshan Kumar

“…The attention mechanism enables more effective spatial feature encoding by focusing on critical image regions, while the HGNN captures interaction patterns that are complex between diverse data types. …”
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Estimating lateral nitrogen transfers over the last century through the global river network using a land surface model by M. Ma, H. Zhang, R. Lauerwald, P. Ciais, P. Regnier

“…Simulation results reveal substantial spatial heterogeneities in annual mean TN flows and denitrification rates, while their seasonal amplitude is of similar magnitude to the large-scale spatial variability. …”
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A 60-year drought analysis of meteorological data in the western Po River basin by E. Mombrini, S. Tamea, A. Viglione, R. Revelli

“…The analysis is carried out over the last 60 <span class="inline-formula">years</span> using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at 3- and 12-month timescales and deriving drought events at the local and regional spatial scales. By leveraging on a continuous and spatially coherent precipitation and temperature dataset, we explore the temporal and spatial variability of drought conditions and compare results obtained with different approaches.…”
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Using Pleiades Satellite Imagery to Monitor Multi-Annual Coastal Dune Morphological Changes by Olivier Burvingt, Bruno Castelle, Vincent Marieu, Bertrand Lubac, Alexandre Nicolae Lerma, Nicolas Robin

“…Strong erosion and accretion patterns over spatial scales ranging from hundreds of meters (e.g., blowouts) to tens of kilometers (e.g., dune retreat) were captured well, and allowed to quantify changes with reasonable errors (30%). …”
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Assessing the Consistency of Five Remote Sensing-Based Land Cover Products for Monitoring Cropland Changes in China by Fuliang Deng, Xinqin Peng, Jiale Cai, Lanhui Li, Fangzhou Li, Chen Liang, Wei Liu, Ying Yuan, Mei Sun

“…Current accuracy assessments of remote sensing-based cropland products focused on the consistency of spatial patterns for specific years, yet the reliability of these cropland products in time-series analysis remains unclear. …”
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Multi-View Intrusion Detection Framework Using Deep Learning and Knowledge Graphs by Min Li, Yuansong Qiao, Brian Lee

“…First, we introduce the knowledge graph (KG) as one of the feature views and neural networks as additional views, forming a multi-view feature fusion strategy that emphasizes the integration of spatial and relational features. The KG represents relational features combined with spatial features extracted by neural networks, enabling a more comprehensive representation of attack patterns through the synergy of both feature types. …”
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Understanding and simulating cropland and non-cropland burning in Europe using the BASE (Burnt Area Simulator for Europe) model by M. Forrest, J. Hetzer, M. Billing, M. Billing, S. P. K. Bowring, S. P. K. Bowring, E. Kosczor, L. Oberhagemann, L. Oberhagemann, O. Perkins, O. Perkins, D. Warren, D. Warren, F. Arrogante-Funes, K. Thonicke, T. Hickler, T. Hickler

“…We first examined fire occurrence across land cover types and found that all non-cropland vegetation (NCV) types (comprising 26 % of burnt area) burnt with similar spatial and temporal patterns, which were very distinct from those in croplands (74 % of burnt area). …”
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Vegetation Baseline and Urbanization Development Level: Key Determinants of Long-Term Vegetation Greening in China’s Rapidly Urbanizing Region by Ke Zeng, Mengyao Ci, Shuyi Zhang, Ziwen Jin, Hanxin Tang, Hongkai Zhu, Rui Zhang, Yue Wang, Yiwen Zhang, Min Liu

“…Urban vegetation shows significant spatial differences due to the combined effects of natural and human factors, yet fine-scale evolutionary patterns and their cross-scale feedback mechanisms remain limited. …”
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Research on Time Series Interpolation and Reconstruction of Multi-Source Remote Sensing AOD Product Data Using Machine Learning Methods by Huifang Wang, Min Wang, Pan Jiang, Fanshu Ma, Yanhu Gao, Xinchen Gu, Qingzu Luan

“…The reconstructed full-coverage AOD product exhibited a spatial distribution trend of significantly higher values in the southern plain areas compared to mountainous regions, consistent with the actual aerosol distribution patterns in the Beijing–Tianjin–Hebei area. …”
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Incorporating Community Knowledge Into Analysis of Air Quality Monitoring Network Data by R. Gardner‐Frolick, S. Jain, N. Martinussen, S. Chambliss, D. Jackson, N. Zimmerman, A. Giang

“…Abstract We conducted a pilot study to explore methods of incorporating qualitative community knowledge into quantitative assessment of temporal and spatial air quality patterns in a neighborhood in Vancouver, British Columbia. …”
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Predicting changes in maximum temperatures in the mid-future period in Sistan and Baluchestan under SSP scenarios by abdolreza kashki, ghorban jafari

“…Geographical and climatic factors significantly influence temperature patterns. Continuous monitoring and improved management strategies are crucial for mitigating climate change.Innovation: This study utilizes advanced CMIP6 models to predict changes in the mean maximum temperature in Sistan and Baluchestan Province and provides spatial maps of these changes using the IDW interpolation method in a GIS environment. …”
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Improving seasonal precipitation forecasts in the Western United States through statistical downscaling by B Vernon, W Zhang, Y Chikamoto

“…While current seasonal forecasting systems provide monthly precipitation forecasts operationally, their coarse resolution limits their effectiveness in capturing the localized precipitation patterns and snowpack conditions essential for water resource managers in the mountainous regions. …”
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Vision Transformer-Based Unhealthy Tree Crown Detection in Mixed Northeastern US Forests and Evaluation of Annotation Uncertainty by Durga Joshi, Chandi Witharana

“…These findings highlight SegFormer’s superior ability to capture complex spatial patterns, even in relatively low-resolution (60 cm) datasets. …”
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A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making. by Alexander C Keyel, Morgan E Gorris, Ilia Rochlin, Johnny A Uelmen, Luis F Chaves, Gabriel L Hamer, Imelda K Moise, Marta Shocket, A Marm Kilpatrick, Nicholas B DeFelice, Justin K Davis, Eliza Little, Patrick Irwin, Andrew J Tyre, Kelly Helm Smith, Chris L Fredregill, Oliver Elison Timm, Karen M Holcomb, Michael C Wimberly, Matthew J Ward, Christopher M Barker, Charlotte G Rhodes, Rebecca L Smith

“…The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. …”
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