Mobile Mapping Systems in Environmental Remote Sensing: Advances for Urban and Forest Applications

Dear Colleagues,

Mobile mapping systems (MMS) have rapidly evolved as powerful platforms for acquiring high-resolution geospatial data in urban and forested environments. By integrating technologies such as LiDAR, GNSS/INS and high-resolution imaging sensors, MMS enables the efficient, accurate and scalable mapping of complex terrains. Increasingly, MMS is being recognized as a complementary component of the remote sensing ecosystem, bridging the gap between close-range measurements and airborne or satellite-based Earth observation. Its adoption has transformed applications ranging from urban infrastructure monitoring to forest structure analysis and ecological research.

Recent advancements have focused on improved sensor integration, robust data processing algorithms and real-time capabilities, addressing challenges such as noise, occlusions and environmental variability. At the same time, emerging approaches—particularly those based on artificial intelligence, machine learning, and multi-source data fusion—are expanding the role of MMS in multi-scale and multi-platform remote sensing frameworks. These developments enable the integration of MMS data with airborne and satellite observations, enhancing the accuracy and completeness of environmental monitoring.

This Special Issue aims to bring together cutting-edge research on MMS within the broader context of remote sensing. By highlighting recent technological developments and application-driven studies, it seeks to provide a comprehensive reference for researchers and practitioners working on high-resolution Earth observation, sustainable urban development and environmental monitoring.

The aim of this Special Issue is to highlight recent advancements in mobile mapping systems (MMS) and their role in remote sensing applications for urban and forest environments. It focuses on both technological innovations—such as sensor integration, real-time data acquisition and advanced processing algorithms—and application domains including urban monitoring, infrastructure assessment, forest inventory and environmental analysis.

This topic aligns closely with the scope of Remote Sensing, particularly in the context of high-resolution Earth observation and multi-platform data integration. MMS provides unique, ground-level perspectives that complement airborne and satellite remote sensing, enabling a more detailed and accurate characterization of natural and built environments.

By combining methodological developments with applied case studies, this Special Issue emphasizes the contribution of MMS to integrated remote sensing workflows, supporting improved geospatial data acquisition, environmental monitoring and decision-making processes. It aims to offer a comprehensive overview of the current trends, challenges and future directions in this rapidly evolving field.

Suggested Themes:

This Special Issue welcomes original research articles, review papers and short communications addressing recent advancements in mobile mapping systems (MMS) within the context of remote sensing and Earth observation.

• Development and integration of mobile mapping sensors (LiDAR, GNSS/INS, photogrammetry, multispectral/hyperspectral imaging)
• Data processing, fusion and visualization techniques for MMS and multi-source remote sensing data
• Integration of MMS with airborne and satellite remote sensing platforms
• Accuracy assessment, calibration and uncertainty modeling of MMS data
• Real-time data acquisition and processing in dynamic urban and forest environments
• Applications in urban monitoring, infrastructure assessment, smart cities and navigation
• Applications in forest inventory, biomass estimation and ecological monitoring
• Machine learning and AI-driven analysis of MMS and multi-platform datasets
• Comparative studies across mobile, airborne and satellite mapping systems
• Challenges and solutions for large-scale mapping and complex environments

Article Types:

• Original research articles presenting novel methodologies, experimental results or application-driven studies
• Review articles synthesizing recent developments, trends and challenges in MMS and related remote sensing technologies

Submissions that explicitly link mobile mapping technologies with remote sensing applications—particularly through multi-platform integration and environmental analysis—are especially encouraged, aligning closely with the journal’s focus on advancing Earth observation science and applications.

Dr. Ehsan Khoramshahi
Guest Editor

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.

• mobile mapping systems (MMS)
• LiDAR
• GNSS/INS integration
• photogrammetry
• urban remote sensing
• forest remote sensing
• multi-source data fusion
• geospatial data processing
• artificial intelligence (AI) and machine learning
• environmental monitoring