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学者姓名：陈崇成
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在公网受限的应急环境中,利用无人机辅助物联网能促进传感数据的及时传递.当考虑无线通信距离时,无人机作为移动收集器在有限续航时间内收集尽可能多的传感数据的路径规划可建模为足够近定向问题(CEOP).现有求解CEOP的算法是逐个计算目标节点的访问顺序及其邻域内的采集点,这在节点邻域较大并覆盖周围多个节点时效率低下,这些方法也没有考虑数据传输时间和无人机遥控距离等约束.为此,建立了大邻域多约束无人机数据收集路径规划的数学模型,提出了基于贪婪随机自适应搜索过程(GRASP)的GRASP-LN算法进行求解.该算法不重复计算重合的采集点,而是维护路径每个航点采集的节点集合,无人机在每个航点悬停一段时间以收集集合内节点的数据.公开的CEOP数据集的实验结果表明,GRASP-LN比GSOA、VNS和GRASPopt具有更好的求解质量和更短的计算时间.与基线算法GRASPopt相比,GRASP-LN的路径奖励平均提高了5.86%,最大提高了14.91%,执行时间平均减少了69%,特别在节点邻域平均覆盖4.67个以上节点时,GRASP-LN的路径奖励和稳定性均优于GRASPopt.考虑数据传输时间和无人机遥控距离约束的实验验证了GRASP-LN算法对考虑这些约束的无人机数据收集路径规划问题的有效性.
Keyword ：
数据收集 数据收集 无人机 无人机 物联网 物联网 贪婪随机自适应搜索过程 贪婪随机自适应搜索过程 足够近定向问题 足够近定向问题 路径规划 路径规划
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| GB/T 7714 | 潘淼鑫 , 陈崇成 . 大邻域多约束无人机数据收集路径规划 [J]. | 计算机科学与探索 , 2025 , 19 (1) : 158-168 . |
| MLA | 潘淼鑫 等. "大邻域多约束无人机数据收集路径规划" . | 计算机科学与探索 19 . 1 (2025) : 158-168 . |
| APA | 潘淼鑫 , 陈崇成 . 大邻域多约束无人机数据收集路径规划 . | 计算机科学与探索 , 2025 , 19 (1) , 158-168 . |
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Three-dimensional (3D) reconstruction of trees has always been a key task in precision forestry management and research. Due to the complex branch morphological structure of trees themselves and the occlusions from tree stems, branches and foliage, it is difficult to recreate a complete three-dimensional tree model from a two-dimensional image by conventional photogrammetric methods. In this study, based on tree images collected by various cameras in different ways, the Neural Radiance Fields (NeRF) method was used for individual tree dense reconstruction and the exported point cloud models are compared with point clouds derived from photogrammetric reconstruction and laser scanning methods. The results show that the NeRF method performs well in individual tree 3D reconstruction, as it has a higher successful reconstruction rate, better reconstruction in the canopy area and requires less images as input. Compared with the photogrammetric dense reconstruction method, NeRF has significant advantages in reconstruction efficiency and is adaptable to complex scenes, but the generated point cloud tend to be noisy and of low resolution. The accuracy of tree structural parameters (tree height and diameter at breast height) extracted from the photogrammetric point cloud is still higher than those derived from the NeRF point cloud. The results of this study illustrate the great potential of the NeRF method for individual tree reconstruction, and it provides new ideas and research directions for 3D reconstruction and visualization of complex forest scenes.
Keyword ：
3D reconstruction 3D reconstruction 3D tree modeling 3D tree modeling deep learning deep learning individual tree individual tree lidar lidar neural radiance field (NeRF) neural radiance field (NeRF) photogrammetry photogrammetry terrestrial laser scanning terrestrial laser scanning
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| GB/T 7714 | Huang, Hongyu , Tian, Guoji , Chen, Chongcheng . Evaluating the Point Cloud of Individual Trees Generated from Images Based on Neural Radiance Fields (NeRF) Method [J]. | REMOTE SENSING , 2024 , 16 (6) . |
| MLA | Huang, Hongyu 等. "Evaluating the Point Cloud of Individual Trees Generated from Images Based on Neural Radiance Fields (NeRF) Method" . | REMOTE SENSING 16 . 6 (2024) . |
| APA | Huang, Hongyu , Tian, Guoji , Chen, Chongcheng . Evaluating the Point Cloud of Individual Trees Generated from Images Based on Neural Radiance Fields (NeRF) Method . | REMOTE SENSING , 2024 , 16 (6) . |
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Accurate and continuous maps of maize distribution are essential for food security and sustainable agricultural development. However, there are no continuous national-scale and fine-resolution maize maps and explicit updated information on the spatiotemporal dynamics of maize for most countries. Maize mapping at the national scale is challenging due to the spectral heterogeneity caused by crop growth conditions, cropping patterns, and inter-annual variations. To this end, this study developed a novel crop index-based algorithm for national-scale maize mapping. Compared to other crops, maize is characterized by large-leaf-dominated canopies and high photosynthetic efficiency. Maize shows significant changes in chlorophyll and anthocyanin content. Therefore, a robust maize index was established by exploring the temporal Variation of the Vegetation-Pigment index (VVP) during the growing period. A simple decision rule was coded on the Google Earth Engine (GEE) platform, which was used for maize mapping based on the Sentinel-2 time series in China and the contiguous United States (US) from 2018 to 2022. The national-scale 10 m annual maize maps for China and the contiguous US were developed and in good agreement with the corresponding agricultural statistics data for many years (R-2 > 0.94) and 9,412 reference points (overall accuracy of 90.09 %). Compared with simply applying the vegetation index, the VVP index took account of spectral heterogeneity caused by variations in crop growth conditions, cropping patterns, and inter-annual, and the omission error of maize was reduced by over 20 %. Moreover, the VVP index can significantly improve the spatial transferability of the Random Forest (RF) classifier. The first 10 m annual maize maps for China revealed that the planted area trend decreased and then increased from 2018 to 2022. The year 2020 was the turning point. The maize planted area consisted of 68 % single maize and 32 % double cropping with maize in 2020, with the northern boundary for double cropping with maize in the Yanshan Mountains. The maize planted area in China consistently decreased by 39,352 km(2) (about 9 %) from 2018 to 2020. This is mainly due to the adjustment of the maize-planted structure in the "Sickle Bend" region of China (the "Sickle Bend" policy). However, the maize planted area gradually recovered from 2020 to 2022, primarily concentrated in regions with ever-planted. This study will provide essential information for cropping structure adjustment and related agricultural policy formulation and contribute to sustainable agricultural development by mapping maize from a national to a global scale.
Keyword ：
Crop mapping Crop mapping Cross -region Cross -region Maize index Maize index National -scale National -scale Spatiotemporal variations Spatiotemporal variations
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| GB/T 7714 | Huang, Yingze , Qiu, Bingwen , Yang, Peng et al. National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series [J]. | COMPUTERS AND ELECTRONICS IN AGRICULTURE , 2024 , 221 . |
| MLA | Huang, Yingze et al. "National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series" . | COMPUTERS AND ELECTRONICS IN AGRICULTURE 221 (2024) . |
| APA | Huang, Yingze , Qiu, Bingwen , Yang, Peng , Wu, Wenbin , Chen, Xuehong , Zhu, Xiaolin et al. National-scale 10 m annual maize maps for China and the contiguous United States using a robust index from Sentinel-2 time series . | COMPUTERS AND ELECTRONICS IN AGRICULTURE , 2024 , 221 . |
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Tourism knowledge graphs lack cultural content, limiting their usefulness for cultural tourists. This paper presents the development of a cultural perspective-based knowledge graph (CuPe-KG). We evaluated fine-tuning ERNIE 3.0 (FT-ERNIE) and ChatGPT for cultural type recognition to strengthen the relationship between tourism resources and cultures. Our investigation used an annotated cultural tourism resource dataset containing 2,745 items across 16 cultural types. The results showed accuracy scores for FT-ERNIE and ChatGPT of 0.81 and 0.12, respectively, with FT-ERNIE achieving a micro-F1 score of 0.93, a 26 percentage point lead over ChatGPT's score of 0.67. These underscore FT-ERNIE's superior performance (the shortcoming is the need to annotate data) while highlighting ChatGPT's limitations because of insufficient Chinese training data and lower identification accuracy in professional knowledge. A novel ontology was designed to facilitate the construction of CuPe-KG, including elements such as cultural types, historical figures, events, and intangible cultural heritage. CuPe-KG effectively addresses cultural tourism visitors' information retrieval needs.
Keyword ：
ChatGPT ChatGPT Cultural tourism Cultural tourism Cultural type Cultural type Knowledge graph Knowledge graph Pretrained language models Pretrained language models Travel intelligence Travel intelligence
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| GB/T 7714 | Fan, Zhanling , Chen, Chongcheng . CuPe-KG: Cultural perspective-based knowledge graph construction of tourism resources via pretrained language models [J]. | INFORMATION PROCESSING & MANAGEMENT , 2024 , 61 (3) . |
| MLA | Fan, Zhanling et al. "CuPe-KG: Cultural perspective-based knowledge graph construction of tourism resources via pretrained language models" . | INFORMATION PROCESSING & MANAGEMENT 61 . 3 (2024) . |
| APA | Fan, Zhanling , Chen, Chongcheng . CuPe-KG: Cultural perspective-based knowledge graph construction of tourism resources via pretrained language models . | INFORMATION PROCESSING & MANAGEMENT , 2024 , 61 (3) . |
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Indoor point clouds often present significant challenges due to the complexity and variety of structures and high object similarity. The local geometric structure helps the model learn the shape features of objects at the detail level, while the global context provides overall scene semantics and spatial relationship information between objects. To address these challenges, we propose a novel network architecture, PointMSGT, which includes a multi-scale geometric feature extraction (MSGFE) module and a global Transformer (GT) module. The MSGFE module consists of a geometric feature extraction (GFE) module and a multi-scale attention (MSA) module. The GFE module reconstructs triangles through each point's two neighbors and extracts detailed local geometric relationships by the triangle's centroid, normal vector, and plane constant. The MSA module extracts features through multi-scale convolutions and adaptively aggregates features, focusing on both local geometric details and global semantic information at different scale levels, enhancing the understanding of complex scenes. The global Transformer employs a self-attention mechanism to capture long-range dependencies across the entire point cloud. The proposed method demonstrates competitive performance in real-world indoor scenarios, with a mIoU of 68.6% in semantic segmentation on S3DIS and OA of 86.4% in classification on ScanObjectNN.
Keyword ：
geometric feature geometric feature multi-scale attention multi-scale attention point cloud analysis point cloud analysis real-world indoor scenario real-world indoor scenario transformer transformer
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| GB/T 7714 | Chen, Yisheng , Xiao, Yu , Wu, Hui et al. Multi-Scale Geometric Feature Extraction and Global Transformer for Real-World Indoor Point Cloud Analysis [J]. | MATHEMATICS , 2024 , 12 (23) . |
| MLA | Chen, Yisheng et al. "Multi-Scale Geometric Feature Extraction and Global Transformer for Real-World Indoor Point Cloud Analysis" . | MATHEMATICS 12 . 23 (2024) . |
| APA | Chen, Yisheng , Xiao, Yu , Wu, Hui , Chen, Chongcheng , Lin, Ding . Multi-Scale Geometric Feature Extraction and Global Transformer for Real-World Indoor Point Cloud Analysis . | MATHEMATICS , 2024 , 12 (23) . |
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Point clouds are essential 3D data representations utilized across various disciplines, often requiring point cloud completion methods to address inherent incompleteness. Existing completion methods like SnowflakeNet only consider local attention, lacking global information of the complete shape, and tend to suffer from overfitting as the model depth increases. To address these issues, we introduced self-positioning point-based attention to better capture complete global contextual features and designed a Channel Attention module for adaptive feature adjustment within the global vector. Additionally, we implemented a vector attention grouping strategy in both the skip-transformer and self-positioning point-based attention to mitigate overfitting, improving parameter efficiency and generalization. We evaluated our method on the PCN dataset as well as the ShapeNet55/34 datasets. The experimental results show that our method achieved an average CD-L1 of 7.09 and average CD-L2 scores of 8.0, 7.8, and 14.4 on the PCN, ShapeNet55, ShapeNet34, and ShapeNet-unseen21 benchmarks, respectively. Compared to SnowflakeNet, we improved the average CD by 1.6%, 3.6%, 3.7%, and 4.6% on the corresponding benchmarks, while also reducing complexity and computational costs and accelerating training and inference speeds. Compared to other existing point cloud completion networks, our method also achieves competitive results.
Keyword ：
3D point cloud 3D point cloud attention mechanism attention mechanism deep learning deep learning point cloud completion point cloud completion
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| GB/T 7714 | Xiao, Yu , Chen, Yisheng , Chen, Chongcheng et al. GSSnowflake: Point Cloud Completion by Snowflake with Grouped Vector and Self-Positioning Point Attention [J]. | REMOTE SENSING , 2024 , 16 (17) . |
| MLA | Xiao, Yu et al. "GSSnowflake: Point Cloud Completion by Snowflake with Grouped Vector and Self-Positioning Point Attention" . | REMOTE SENSING 16 . 17 (2024) . |
| APA | Xiao, Yu , Chen, Yisheng , Chen, Chongcheng , Lin, Ding . GSSnowflake: Point Cloud Completion by Snowflake with Grouped Vector and Self-Positioning Point Attention . | REMOTE SENSING , 2024 , 16 (17) . |
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The cultural tourism industry emphasizes creativity and scene experience, which is highly compatible with the metaverse. The research of the cultural tourism metaverse is in the infancy stage. The concept, key technologies, and application scenarios are still being explored. First, the paper reviews the evolutionary process of the metaverse. The paper proposes the basic definition, conceptual model, and key features of the cultural tourism metaverse. The paper considers the cultural tourism metaverse as a subsystem of the metaverse. It is a cultural tourism Internet form formed by existing information technology in the cultural tourism industry. It is a reconfiguration and virtual symbiosis of cultural tourism activities in a 3D digital world. It provides an immersive experience of cultural tourism scenes based on extended reality technology. Based on the digital twin technology, it generates a mirror image of the real-world cultural tourism scene. It relies on the political, economic, and cultural systems under the unified architecture of the metaverse and realizes the all-around integration of the virtual world and the real world of the cultural tourism industry. The conceptual model of the cultural tourism metaverse consists of key technologies, guarantee systems, participating subjects, and product services. The development of the cultural tourism metaverse cannot be achieved without the support of key technologies. As an industry metaverse application, it does not exist in isolation. Its smooth, reliable operation is closely related to the social, political, economic, cultural, legal, and moral system established by the future holistic metaverse. The participating subjects of the cultural tourism metaverse include suppliers, consumers, developers, governors, and researchers. It is immersive, interactive, customized, cultural, educational, connected, and interdisciplinary. Second, the paper summarizes the research progress and application of key technologies in the field of cultural tourism. These key technologies include basic support technologies (such as intelligent communication, Internet of things perception, artificial intelligence, positioning and navigation, and big data computing and storage), virtual-real connection technologies (such as virtual geographic environment, digital twin, virtual digital human, and decentralization) and virtual-real interaction technologies (such as extended reality, brain-computer interface, and video games). The cultural tourism metaverse involves much more information technologies than what is mentioned in the paper. Moreover, all information technologies developed so far in the real world will be reflected in future metaverse scenarios or continuously upgraded and improved. Lastly, the authors look forward to the application scenarios of the cultural tourism metaverse such as cultural heritage digitization and protection, scenic spot (hotel) development and management, guided tour service, cultural tourism marketing, and industry supervision. The paper argues that the future research directions of the cultural tourism metaverse include personalized construction of cultural tourism virtual scenes, rapid migration of existing virtual reality cultural tourism scenes, integration of virtual and real cultural tourism scenes, seamless positioning and navigation of the cultural tourism metaverse, visitor experience and interaction, business models and monetization, and interoperability standards for virtual and real cultural tourism scenes. Metaverse development also faces issues such as ethics, security and privacy, technology, and the challenge of realistic national sovereignty. While technology is always hovering, these technologies will eventually reshape the future shape of society and human life. © 2024 Science Press. All rights reserved.
Keyword ：
cultural tourism cultural tourism extended reality extended reality metaverse metaverse remote sensing remote sensing virtual and reality integration virtual and reality integration virtual geographic environment virtual geographic environment virtual world virtual world
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| GB/T 7714 | Fan, Z. , Chen, C. . Cultural tourism metaverse：Concept，key technologies，and application scenarios; [文旅元宇宙：概念、关键技术及应用场景] [J]. | National Remote Sensing Bulletin , 2024 , 28 (5) : 1161-1176 . |
| MLA | Fan, Z. et al. "Cultural tourism metaverse：Concept，key technologies，and application scenarios; [文旅元宇宙：概念、关键技术及应用场景]" . | National Remote Sensing Bulletin 28 . 5 (2024) : 1161-1176 . |
| APA | Fan, Z. , Chen, C. . Cultural tourism metaverse：Concept，key technologies，and application scenarios; [文旅元宇宙：概念、关键技术及应用场景] . | National Remote Sensing Bulletin , 2024 , 28 (5) , 1161-1176 . |
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元宇宙快速发展正在影响着文旅行业的变革。文旅行业强调创意与场景体验，文旅产品具有重内容、重体验、重参与及重个性化的特点，这与元宇宙的发展高度契合。现阶段，文旅元宇宙的研究还处于襁褓阶段，对文旅元宇宙的概念、核心技术和应用场景还处于探索中。首先，本文回顾了元宇宙的演化进程，并基于文旅行业特征，提出了文旅元宇宙的基本定义、概念模型及主要特征，认为文旅元宇宙是元宇宙的一个子系统，是现有信息技术在文旅行业深度融合形成的文旅互联网形态，是文旅活动在三维数字世界的一种重构和虚拟共生。其基于扩展现实技术提供文旅场景的沉浸式体验，基于数字孪生技术生成现实世界文旅场景的镜像，并依托元宇宙统一架构下的政治、经济、文化等体系，实现文旅行业虚拟世界和现实世界的全方位融合；然后，对文旅元宇宙相关关键技术在文旅行业应用的研究进展和应用进行了详细的描述；最后，展望了文旅元宇宙在文化遗产数字化与保护、景区（酒店）开发与管理、导游导览服务、文旅营销、行业监管与市场治理等方面可能的应用场景，提出了文旅元宇宙未来重点的研究方向。虽然文旅元宇宙的发展还面临着诸多的挑战，技术的发展还要不断地经历螺旋式的上升，但是元宇宙终会重塑未来的社会形态和人类的生活方式。
Keyword ：
元宇宙 元宇宙 扩展现实 扩展现实 文化旅游 文化旅游 虚实融合 虚实融合 虚拟世界 虚拟世界 虚拟地理环境 虚拟地理环境 遥感 遥感
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| GB/T 7714 | 范占领 , 陈崇成 . 文旅元宇宙：概念、关键技术及应用场景 [J]. | 遥感学报 , 2024 , 28 (05) : 1161-1176 . |
| MLA | 范占领 et al. "文旅元宇宙：概念、关键技术及应用场景" . | 遥感学报 28 . 05 (2024) : 1161-1176 . |
| APA | 范占领 , 陈崇成 . 文旅元宇宙：概念、关键技术及应用场景 . | 遥感学报 , 2024 , 28 (05) , 1161-1176 . |
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针对实时视频与实景三维模型融合时视频纹理存在割裂感、融合边界差异感明显、视频流实时性差等问题，本文提出了一种改进的实景三维模型和实时视频图像融合方法。首先利用倾斜摄影测量技术构建实景三维模型，搭建流媒体实现视频图像向三维场景的实时传输，匹配视频像素与实景模型片元顶点的对应关系；然后引入顾及场景深度的展平映射策略，以消除视频画面融入模型时的纹理割裂感；最后基于距离掩膜使融合接缝处过渡更加平滑。试验结果表明，本文所提映射策略融合效果优异，可消除融合画面的割裂现象和融合边界的突兀感，且在融合多路视频情形下场景帧率保持在50帧/s以上，系统承载力良好，实时性效果好，成果能应用于构建实时虚实融合的数字孪生场景。
Keyword ：
增强虚拟环境 增强虚拟环境 数字孪生 数字孪生 虚实融合 虚实融合 视频纹理 视频纹理 透视投影 透视投影
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| GB/T 7714 | 杨松 , 陈崇成 . 面向实景三维模型和实时视频图像融合的纹理映射 [J]. | 测绘通报 , 2023 , 6 (10) : 61-66 . |
| MLA | 杨松 et al. "面向实景三维模型和实时视频图像融合的纹理映射" . | 测绘通报 6 . 10 (2023) : 61-66 . |
| APA | 杨松 , 陈崇成 . 面向实景三维模型和实时视频图像融合的纹理映射 . | 测绘通报 , 2023 , 6 (10) , 61-66 . |
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Maize yield in China accounts for more than one-fourth of the global maize yield, but it is challenged by frequent extreme weather and increasing food demand. Accurate and timely estimation of maize yield is of great significance to crop management and food security. Commonly applied vegetation indexes (VIs) are mainly used in crop yield estimation as they can reflect the greenness of vegetation. However, the environmental pressures of crop growth and development are difficult to monitor and evaluate. Indexes for water content, pigment content, nutrient elements and biomass have been developed to indirectly explain the influencing factors of yield, with extant studies mainly assessing VIs, climate and water content factors. Only a few studies have attempted to systematically evaluate the sensitivity of these indexes. The sensitivity of the spectral indexes, combined indexes and climate factors and the effect of temporal aggregation data need to be evaluated. Thus, this study proposes a novel yield evaluation method for integrating multiple spectral indexes and temporal aggregation data. In particular, spectral indexes were calculated by integrating publicly available data (remote sensing images and climate data) from the Google Earth Engine platform, and county-level maize yields in China from 2015 to 2019 were estimated using a random forest model. Results showed that the normalized moisture difference index (NMDI) is the index most sensitive to yield estimation. Furthermore, the potential of adopting the combined indexes, especially NMDI_NDNI, was verified. Compared with the whole-growth period data and the eight-day time series, the vegetative growth period and the reproductive growth period data were more sensitive to yield estimation. The maize yield in China can be estimated by integrating multiple spectral indexes into the indexes for the vegetative and reproductive growth periods. The obtained R-2 of maize yield estimation reached 0.8. This study can provide feature knowledge and references for index assessments for yield estimation research.
Keyword ：
combined index combined index maize yield maize yield multiple spectral indexes multiple spectral indexes temporal aggregation temporal aggregation yield estimation yield estimation
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| GB/T 7714 | He, Yuhua , Qiu, Bingwen , Cheng, Feifei et al. National Scale Maize Yield Estimation by Integrating Multiple Spectral Indexes and Temporal Aggregation [J]. | REMOTE SENSING , 2023 , 15 (2) . |
| MLA | He, Yuhua et al. "National Scale Maize Yield Estimation by Integrating Multiple Spectral Indexes and Temporal Aggregation" . | REMOTE SENSING 15 . 2 (2023) . |
| APA | He, Yuhua , Qiu, Bingwen , Cheng, Feifei , Chen, Chongcheng , Sun, Yu , Zhang, Dongshui et al. National Scale Maize Yield Estimation by Integrating Multiple Spectral Indexes and Temporal Aggregation . | REMOTE SENSING , 2023 , 15 (2) . |
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