Special Issues

Progress, Challenges, and Opportunities in GIS 3D Modeling and UAV Remote Sensing

Submission Deadline: 31 March 2025 (closed) View: 1558 Submit to Journal

Guest Editors

Prof. Dr. Ling Jiang, Chuzhou University, CHINA
Ling Jiang received the Ph.D. degree of cartography and geographic information system from Nanjing Normal University. He is a professor of geographic information science at Chuzhou University, Chuzhou, China. His major research interests include 3D modeling, terrain analysis, and high-performance geo-computing.

Dr. Wen Dai, Nanjing University of Information Science & Technology, CHINA
Wen Dai is a researcher and lecturer at Nanjing University of Information Science and Technology. He received the Ph.D. degree of cartography and geographic information system from Nanjing Normal University. His current research interests include UAV photogrammetry, GeoAI, and terrain analysis.


Summary

Geographic Information Systems (GIS) have undergone a transformative evolution with the integration of 3D modeling and Unmanned Aerial Vehicles (UAVs) for remote sensing. The use of UAVs for data collection has enabled high-resolution, timely, and cost-effective spatial data acquisition, while 3D modeling techniques have enriched our ability to visualize and analyze complex geospatial data in three dimensions. This special issue seeks to bring together research contributions that highlight the progress made, address the challenges faced, and explore the numerous opportunities in the field of GIS 3D modeling and UAV remote sensing.

 

Topics of Interest:

This special issue welcomes original research, review articles, case studies, and technical notes related, but are not limited, to the following topics:

1. UAV Technology Advancements: Advances in UAV platforms, sensors, data collection, and data processing techniques.

2. 3D Data Modeling and Visualization: Techniques and tools for 3D modeling, rendering, and visualization of geospatial data.

3. Data Integration and Fusion: Strategies for integrating UAV-collected data with existing GIS databases and satellite imagery.

4. Environmental Monitoring: Applications of UAVs and 3D GIS in environmental monitoring, including climate change studies and disaster response.

5. Urban Planning and Development: The use of UAVs and 3D GIS in urban planning, infrastructure design, and smart city development.

6. Natural Resource Management: Assessments of natural resources, including forestry, agriculture, and mining, using UAV and 3D modeling techniques.

7. Cultural Heritage and Archaeology: Preservation and documentation of cultural heritage sites and archaeological discoveries.

8. Geographic computing and related algorithms: 3D spatial data processing algorithms, High performance geographic computing method and algorithms.

9. Applications of GIS 3D modeling and UAV remote sensing in Land remediation, land spatial planning, and other related applications.


Keywords

GIS 3D modeling, UAV remote sensing, Photogrammetry, 3D Data Modeling and Visualization, Data Integration and Fusion, Natural Resource Monitoring and Management, Applications of GIS and UAV 3D Data

Published Papers


  • Open Access

    REVIEW

    3D LiDAR-Based Techniques and Cost-Effective Measures for Precision Agriculture: A Review

    Mukesh Kumar Verma, Manohar Yadav
    Revue Internationale de Géomatique, Vol.34, pp. 855-879, 2025, DOI:10.32604/rig.2025.069914
    (This article belongs to the Special Issue: Progress, Challenges, and Opportunities in GIS 3D Modeling and UAV Remote Sensing)
    Abstract Precision Agriculture (PA) is revolutionizing modern farming by leveraging remote sensing (RS) technologies for continuous, non-destructive crop monitoring. This review comprehensively explores RS systems categorized by platform—terrestrial, airborne, and space-borne—and evaluates the role of multi-sensor fusion in addressing the spatial and temporal complexity of agricultural environments. Emphasis is placed on data from LiDAR, GNSS, cameras, and radar, alongside derived metrics such as plant height, projected leaf area, and biomass. The study also highlights the significance of data processing methods, particularly machine learning (ML) and deep learning (DL), in extracting actionable insights from large datasets. By More >

  • Open Access

    ARTICLE

    Dynamic Coefficient Triangular Greenness Index for Aerial Phenotyping in a Liberica Coffee Farm

    Anton Louise P. De Ocampo
    Revue Internationale de Géomatique, Vol.34, pp. 731-749, 2025, DOI:10.32604/rig.2025.066185
    (This article belongs to the Special Issue: Progress, Challenges, and Opportunities in GIS 3D Modeling and UAV Remote Sensing)
    Abstract The effects of climate change are becoming more evident nowadays, and the environmental stress imposed on crops has become more severe. Farmers around the globe continually seek ways to gain insights into crop health and provide mitigation as early as possible. Phenotyping is a non-destructive method for assessing crop responses to environmental stresses and can be performed using airborne systems. Unmanned Aerial Systems (UAS) have significantly contributed to high-throughput phenotyping and made the process rapid, efficient, and non-invasive for collecting large-scale agronomic data. Because of the high complexity and cost of specialized equipment used in… More >

  • Open Access

    ARTICLE

    Analysis of Color Landscape Characteristics in “Beautiful Village” of China Based on 3D Real Scene Models

    Yiyi Cen, Wenzheng Jia, Wen Dai, Chun Wang, He Wu
    Revue Internationale de Géomatique, Vol.33, pp. 93-109, 2024, DOI:10.32604/rig.2024.050273
    (This article belongs to the Special Issue: Progress, Challenges, and Opportunities in GIS 3D Modeling and UAV Remote Sensing)
    Abstract Color, as a significant element of village landscapes, serves various functions such as enhancing aesthetic appeal and attractiveness, conveying emotions and cultural values. To explore the three-dimensional spatial characteristics of color landscapes in beautiful villages, this study conducted a comparative experiment involving eight provincial-level beautiful villages and eight ordinary villages in Jinzhai County. Landscape pattern indices were used to analyze the color landscape patterns on the facades of these villages, complemented by a quantitative analysis of color attributes using the Munsell color system. The results indicate that (1) Natural landscape colors in beautiful villages are… More >

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