Predicting future evapotranspiration based on remote sensing and deep learning by Xin Zheng, Sha Zhang, Shanshan Yang, Jiaojiao Huang, Xianye Meng, Jiahua Zhang, Yun Bai

“…Study focus: This study validates the efficiency of Convolutional Long Short-Term Memory Network (ConvLSTM) models for site-scale ETa prediction. We enhanced the ConvLSTM model by adding a Spatial Pyramid Pooling module (SPPM) and a Multi-head Self-Attention Module (MSA-Module), creating the Multi-head Self-Attention ConvLSTM (MSA-ConvLSTM) model, which we applied to predicting regional-scale actual evapotranspiration (ETa). …”
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Review on development and utilization of offshore renewable energy: An analysis based on a five-dimensional framework by DU Wenjie, CAI Guotian, Qi Xiaoling, WANG Peng, ZHANG Jixiang

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The Optimal Dispatch for a Flexible Distribution Network Equipped with Mobile Energy Storage Systems and Soft Open Points by Yu Ji, Ying Zhang, Lei Chen, Juan Zuo, Wenbo Wang, Chongxin Xu

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Mapping Wetlands with High-Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand by Md. Saiful Islam Khan, Maria C. Vega-Corredor, Matthew D. Wilson

“…In this research, our motivation was to test whether high-spatial-resolution PlanetScope imagery can be used with pixel-based machine learning to support the mapping and monitoring of wetlands at a national scale. (2) Methods: This study compared four machine learning classification models—Random Forest (RF), XGBoost (XGB), Histogram-Based Gradient Boosting (HGB) and a Multi-Layer Perceptron Classifier (MLPC)—to detect and map wetland areas across New Zealand. …”
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Model Test of Mechanical Response of Negative Poisson’s Ratio Anchor Cable in Rainfall-Induced Landslides by Guangcheng Shi, Zhigang Tao, Feifei Zhao, Jie Dong, Xiaojie Yang, Zhouchao Xu, Xiaochuan Hu

“…This study investigates the stabilizing performance of slopes reinforced with negative Poisson’s ratio (NPR) anchor cables under rainfall conditions through physical model tests. A scaled geological model of a heavily weathered rock slope is constructed using similarity-based materials, building a comprehensive experimental setup that integrates an artificial rainfall simulation system, a model-scale NPR anchor cable reinforcement system, and a multi-parameter data monitoring system. …”
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Bi-modal contrastive learning for crop classification using Sentinel-2 and Planetscope by Ankit Patnala, Scarlet Stadtler, Scarlet Stadtler, Martin G. Schultz, Martin G. Schultz, Juergen Gall, Juergen Gall

“…First, we adopt the uni-modal contrastive method (SCARF) and, second, we use a bi-modal approach based on Sentinel-2 and Planetscope data instead of standard transformations developed for natural images to accommodate the spectral characteristics of crop pixels. Evaluation in three regions of Germany and France shows that crop classification with the pre-trained multi-modal model is superior to the pre-trained uni-modal method as well as the supervised baseline models in the majority of test cases.…”
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Machine Learning-Driven Multimodal Feature Extraction and Optimization Strategies for High-Speed Railway Station Area by Xiang Li, Fa Zhang, Ziyi Liu, Yao Wei, Runlong Dai, Zhiyue Qiu, Yuxin Gu, Hong Yuan

“…This research develops a multimodal feature extraction and evaluation framework specifically designed for the large-scale analysis of HSR station areas. The nine-category strategic recommendations with defined quantitative threshold intervals provide decision-makers with visually intuitive, operationally implementable, and practically significant guidance for spatial planning and resource allocation.…”
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Nighttime light intensity and brightness suitability in urban functional zones by Ming Liu, Ruicong Li, Yiwei Li, Ezzaddeen Ali Mohammed Saeed AL-Mowallad, Chenglong Wu, Wenjing Wang

“…The differences in brightness of the nocturnal light environment further reveal the characteristics of urban functions. This study takes the main urban area of Dalian as an example, integrates Point of Interest and OpenStreetMap data to generate functional zone samples, and proposes a multi-scale evaluation framework at the levels of administrative districts, streets, and blocks, combined with Luojia-1 night-time remote sensing imagery. …”
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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

“…This study employs a Multi-Attention Network (MANet) for WWTP extraction, integrating channel and spatial feature attention. …”
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Key technologies and approaches for water resource conservation and utilization in arid to semi-arid open-pit coal mining areas in the northern sand prevention belt of China by Jie FANG, Zhimin XU, Wei CHENG, Zihan LU, Yongqiang ZHAO, Yuhao ZHU, Tianci CHEN

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A review of SAR tomography by Xin Zhao, Jie Dong, Yanghai Yu, Mingsheng Liao, Lu Zhang, Jianya Gong

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Image-based machine learning and cluster analysis for urban road network: employing Orange for codeless visual programming by Zuo Zhang, Mengwei Zhang, Xiangxiang Song, Zhi Li

“…With the continuous evolution of advanced data and computational technologies, it is now feasible to construct intricate models for an in-depth exploration of urban spatial structures. In this study, we constructed an analytical framework that leveraged road network image recognition, multi-scale influence factors analysis, and predictions using codeless visual programming. …”
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Research on Semantic Driven Urban Pipeline Dataspace Construction Method by B. Li, L. Huo, Y. Yang, P. Bao, M. Zhang, Y. Li

“…Firstly, this method combines the classification and characteristics of urban pipelines, and expresses the semantic information of pipeline geographic entities from four dimensions: semantic description, spatial location, attribute characteristics and time evolution. …”
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Night and Day Aerial Photogrammetry by L. Morelli, G. Perda, S. Malek, F. Remondino, K. Legat

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The accuracy of image-based individual tree crown detection and delineation across vegetation types by N. Pucino, T. McVicar, S. Levick, A. van Dijk

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A Comparative Study of Deep Learning-Based Models for Object Detection in Remote Sensing Imagery by A. V. Coulson, W. H. Thomas, C. Wang

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Regional Sea Level Changes in the East China Sea from 1993 to 2020 Based on Satellite Altimetry by Lujie Xiong, Fengwei Wang, Yanping Jiao

“…Based on the altimetry grid data processed by the local mean decomposition method, the spatiotemporal changes of ECS sea level are analyzed from the multi-scale perspective in terms of multi-year, seasonal, interannual, and multi-modal scales. …”
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Assessment Method for Feeding Intensity of Fish Schools Using MobileViT-CoordAtt by Shikun Liu, Xingguo Liu, Haisheng Zou

“…The method employs a lightweight MobileViT backbone network, integrated with a Coordinate Attention (CoordAtt) mechanism and a multi-scale feature fusion strategy. Specifically, the CoordAtt module enhances the model’s spatial perception by encoding spatial coordinate information, enabling precise capture of the spatial distribution characteristics of fish schools. …”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…For residual networks in classification networks, multi-scale convolution is introduced to enhance the information interaction between features, so that residual networks can fully perceive the multi-level information contained in feature maps.Results and Discussions　Feature validity test was carried out for the six emotional features selected, that is, MFCC, MFCC-TEO, LPCC and Jitter features were added in turn on the basis of short-term energy, zero cross rate and sound intensity, and accuracy (Acc), root mean square error (RMSE) and mean absolute error (MAE) under different input characteristics were calculated. …”
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Analysis of Sediment Variation in Important Tributaries of the Yellow River in the Sandy and Coarse Sediment Area Based on Detrital Zircons and Hydrological Observations by Ting BAI, Niannian FAN, Yuanjian WANG, Ruihua NIE, Xingnian LIU

“…Although extensive research has been conducted, the multi-temporal and spatial scale characteristics of sediment production and transport remain unclear.Methods This study examines the Huangfu River and Kuye River tributaries in the high coarse sediment area of the Loess Plateau to analyze the multi-temporal and spatial characteristics of sediment production and transport. …”
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