Mapping Delayed Canopy Loss and Durable Fire Refugia for the 2020 Wildfires in Washington State Using Multiple Sensors by Anika M. Anderson, Meg A. Krawchuk, Flavie Pelletier, Jeffrey A. Cardille

“…The algorithm compiles Normalized Burn Ratio data from Sentinel-2 and Landsat 8 and 9 and uses Bayes’ Theorem to map land cover changes. …”
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Mapping landforms of a hilly landscape using machine learning and high-resolution LiDAR topographic data by Netra R. Regmi, Nina D.S. Webb, Jacob I. Walter, Joonghyeok Heo, Nicholas W. Hayman

“…Here we implemented such an objective approach applying a random forest machine learning algorithm to a set of observed landform data and 1m horizontal resolution bare-earth digital elevation model (DEM) developed from airborne light detection and ranging (LiDAR) data to rapidly map various landforms of a hilly landscape. …”
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A novel voting ensemble model empowered by metaheuristic feature selection for accurate flash flood susceptibility mapping by Radhwan A. Saleh, Ahmed M. Al-Areeq, Amran A. Al Aghbari, Mustafa Ghaleb, Mohammed Benaafi, Nabil M. Al‑Areeq, Baqer M. Al-Ramadan

“…As climate change is expected to increase extreme rainfall events, communities globally will need robust data-driven methodologies for flash flood susceptibility mapping. The Key recommendations of the current study include investigating hybrid feature selection methods to better enhance predictive inputs and analyzing transferability across hydro-climatic zones.…”
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Enhancing the Accuracy of Land Use/Cover Map Using Some Spectral Indices in Sarab County–East Azerbaijan by A. Sarabchi, H. Rezaei, F. Shahbazi

“…The results of image classification indicated that the performance of the SVM algorithm across different band combinations is superior to that of the maximum likelihood method. …”
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UAV as a Bridge: Mapping Key Rice Growth Stage with Sentinel-2 Imagery and Novel Vegetation Indices by Jianping Zhang, Rundong Zhang, Qi Meng, Yanying Chen, Jie Deng, Bingtai Chen

“…Here, we propose utilizing UAVs as an alternative means to collect spatially continuous ground reference data across larger areas, thereby enhancing the efficiency and scalability of training and validation processes for rice growth stage mapping products. …”
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Intelligent generative design: a transfer learning-enhanced bidirectional mapping framework for customised parametric structural design by Jiajie Hu, Yayun Wang, Hua Tian, Peng Zheng, Liang Chi, Lulu Xue, Qian Su, Qing Jiang, Yong He, Lan Li, Liya Zhu

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Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

“…Three distinct soil TN inversion models were constructed using these algorithms. To optimize model performance, ten-fold cross-validation was employed to determine the optimal parameters for each model. …”
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MAS-YOLOv11: An Improved Underwater Object Detection Algorithm Based on YOLOv11 by Yang Luo, Aiping Wu, Qingqing Fu

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Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification by Lochana Mendis, Debjyoti Karmakar, Marimuthu Palaniswami, Fiona Brownfoot, Emerson Keenan

“…However, their progress is impeded by limited CTG training datasets and the absence of a standardized evaluation workflow, hindering algorithm comparisons. In this study, we use a private CTG dataset of 9,887 CTG recordings with pH measurements and 552 CTG recordings from the open-access CTU-UHB dataset to conduct a cross-database evaluation of six deep-learning models for fetal compromise detection. …”
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Evidence on the performance of nature-based solutions interventions for coastal protection in biogenic, shallow ecosystems: a systematic map by Avery B. Paxton, Trevor N. Riley, Camille L. Steenrod, Brandon J. Puckett, Jahson B. Alemu I., Savannah T. Paliotti, Alyssa M. Adler, Laura Exar, Josette E. T. McLean, James Kelley, Y. Stacy Zhang, Carter S. Smith, Rachel K. Gittman, Brian R. Silliman

“…To help fill this gap, we systematically mapped the global evidence base on the ecological, physical, economic, and social performance of NBS interventions related to coastal protection. …”
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Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

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Machine Learning Enhances Soil Aggregate Stability Mapping for Effective Land Management in a Semi-Arid Region by Pegah Khosravani, Ali Akbar Moosavi, Majid Baghernejad, Ndiye M. Kebonye, Seyed Roohollah Mousavi, Thomas Scholten

“…Thus, we developed cost-efficient wall-to-wall spatial prediction maps for two fundamental SAS proxies [mean weight diameter (MWD) and geometric mean diameter (GMD)], across a 5000-hectare area in Southwest Iran. …”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Cross-view geolocalization (CVGL) describes the general problem of determining a correlation between terrestrial and nadir oriented imagery. …”
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Cross-domain 3D Model Retrieval Based on Viewpoint Alignment by ZHANG Libao, WANG Tao, GAO Zheng, DING Bo, HE Yongjun

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From Historical Archives to Algorithms: Reconstructing Biodiversity Patterns in 19th Century Bavaria by Malte Rehbein

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MSM: a scaling-based feature matching algorithm for images with large-scale differences by Qifeng Ge, Xiaoping Du, Chen Xu, Jianhao Xu, Zhenzhen Yan, Xiangtao Fan

“…This algorithm extract feature points across multiple scales, identifying them as scale-invariant keypoints. …”
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Deep Learning-Based Feature Matching Algorithm for Multi-Beam and Side-Scan Images by Yu Fu, Xiaowen Luo, Xiaoming Qin, Hongyang Wan, Jiaxin Cui, Zepeng Huang

“…Side-scan sonar and multi-beam echo sounder (MBES) are the most widely used underwater surveying tools in marine mapping today. The MBES offers high accuracy in depth measurement but is limited by low imaging resolution due to beam density constraints. …”
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Traffic environment perception algorithm based on multi-task feature fusion and orthogonal attention by Zhengfeng LI, Mingen ZHONG, Yihong ZHANG, Kang FAN, Zhiying DENG, Jiawei TAN

“…This module is designed to capture fine-grained global image features by facilitating cross-layer information fusion. By integrating features across different scales, C2f-K effectively reduces background noise and interference, thereby improving the understanding of complex scenes of the model. …”
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Few-shot segmentation based on multi-level and cross-scale clustering by Shuai Yuan, Junhai Qiu, Hongxia Xu, Yan Zhang, Jiaxing Zhang

“…A novel method that consists of two modules is proposed: a multi-level fuzzy clustering guidance module and a cross-scale feature fusion module. The former module can extract image features in a class-independent feature space and fuse them with different scale information, while the latter module can reduce the information loss caused by cross-scale transmission. …”
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Efficient Depth Map Estimation Method Based on Gradient Weight Cost Aggregation Strategy for Distributed Video Sensor Networks by Gwang-Soo Hong, Byung-Gyu Kim, Kee-Koo Kwon

“…Video sensor networking technologies have developed very rapidly in the last ten years. In this paper, a cross-based framework strategy for cost aggregation is presented for the depth map estimation based on video sensor networks. …”
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