3D City Modeling and Sensing Using High-Resolution and Multi-Sensor Remote Sensing Data

Dear Colleagues,

With the rapid acceleration of urbanization, 3D city modeling has become a core technology in modern urban planning, infrastructure management, environmental monitoring, and disaster management. High-resolution remote sensing data, especially LiDAR (Light Detection and Ranging) point cloud data and remote sensing imagery (such as optical imagery, Synthetic Aperture Radar (SAR), etc.), play a vital role in the accurate modeling and dynamic monitoring of urban environments. These data sources provide crucial 3D spatial information about urban features and enable the monitoring of changes in the urban environment over time, supporting urban planning, environmental protection, and other critical applications.

LiDAR and remote sensing images are two representative types of remote sensing data used in 3D city modeling and sensing. LiDAR data provide high-density point cloud information that accurately captures the spatial details of urban objects, such as buildings, roads, and trees, forming the basis for 3D city model construction and precise object extraction. Remote sensing images, on the other hand, offer rich optical, infrared, or SAR data, which can complement the surface details that LiDAR data might miss and play an essential role in dynamic monitoring and change detection.

However, these high-resolution data often face challenges such as noise interference, data gaps, and the need for multi-source data fusion. Efficiently processing these data and improving the accuracy of 3D city models, along with realizing the real-time dynamic monitoring of urban environments, remains a critical issue in this field.

This Special Issue aims to explore how to enhance 3D city modeling and sensing through the processing and fusion of LiDAR point cloud data and remote sensing imagery. The focus will be on improving the accuracy and efficiency of these technologies, as well as fostering innovation and development in this field.

This Special Issue will showcase the potential benefits and challenges of using LiDAR point cloud data and remote sensing image for 3D city modeling and sensing. It will focus on leveraging high-resolution remote sensing data, particularly in areas such as data fusion, deep learning, and dynamic monitoring, to improve the accuracy and automation of 3D city modeling and urban sensing.

This Special Issue is closely aligned with the scope of Remote Sensing, especially in areas such as remote sensing data processing, city modeling, environmental monitoring, and urban planning. Through this Special Issue, we will provide a platform for scholars, researchers, and industry professionals to exchange ideas and advance the application of high-resolution remote sensing data and multi-sensor technologies in urban modeling and sensing.

We invite submissions on the following topics, including but not limited to:

• 3D city modeling methods and technologies based on high-resolution remote sensing data (e.g., LiDAR point clouds, optical imagery, SAR, etc.);
• Fusion and analysis of multi-sensor data for 3D city modeling and sensing applications;
• Object detection, classification, and segmentation techniques in urban environments;
• Dynamic monitoring and change detection in urban environments using remote sensing data;
• Automation of urban environmental sensing using deep learning techniques;
• Applications of 3D city models in smart cities, including digital twins, urban planning, and city management;
• Processing and analysis of LiDAR point cloud data and remote sensing images, including point cloud classification, building reconstruction, and image registration;
• Fusion of LiDAR data with remote sensing images to enhance 3D city modeling and sensing;
• Applications of remote sensing data in urban disaster management, traffic management, and environmental monitoring;
• Real-time updates and dynamic monitoring of urban space using remote sensing and sensor networks.

Dr. Yu Zang
Dr. Weiquan Liu
Dr. Yan Xia
Dr. Ziyi Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the Special Issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.