GIScience & Remote Sensing

VLM Driven Intelligent Interpretation of Remote Sensing Imagery

The rapid progress of vision-language models (VLMs) empowers intelligent remote sensing image interpretation, transforming traditional label-guided recognition into knowledge-driven scene understanding and reasoning to fuel industrial technical upgrades. Conventional remote sensing approaches constrained by limited semantic tags lack robust semantic expression, cross-region generalization, complex-scene reasoning ability and model interpretability. VLMs introduce rich prior knowledge through natural language, linking visual features with domain expertise, expanding semantic descriptions of land features, boosting cross-regional adaptation, analyzing inter-object relations and clarifying judgment logic to tackle persistent bottlenecks and elevate remote sensing intelligence.

VLMs are uniquely vital for remote sensing workflows, infusing broad linguistic world knowledge into remote sensing visual modelling to overcome traditional remote sensing limits of weak cross-region generalization and low model interpretability. They sharpen remote sensing analysis of surface features, spatial links and environmental shifts, enabling core remote sensing tasks such as land cover classification, disaster emergency monitoring and urban land planning.

This Article Collection seeks to bring together cutting-edge remote sensing methods and application outcomes focusing on VLM theories, core techniques for remote sensing image interpretation, scenario reasoning and field decision deployment. Articles aligning with the Journal's accepted article types  are encouraged to advance intelligent remote sensing toward language-guided, knowledge-boosted, reasoning-powered evolution. Relevant subtopics include, but are not limited to:

• Remote sensing multimodal representation learning and foundation model design (e.g., vision-language modeling, multimodal fusion, cross-modal alignment, domain-adaptive foundation models)
• Language-guided remote sensing perception and reasoning tasks (e.g., classification, detection, segmentation, change detection, spatial reasoning, spatiotemporal reasoning).
• Remote sensing data construction and model adaptation (e.g., image-text dataset construction, instruction tuning, reasoning data generation, domain knowledge-enhanced training, fine-tuning)
• The application of vision-language large models in remote sensing (e.g., precision agriculture, urban functional analysis, disaster monitoring, ecological assessment)

Article Collection Guest Advisors

Cuiping Shi is a Professor and Ph.D. Supervisor at the School of Information Engineering, Huzhou Normal University, China. He received his Ph.D. in Communication and Information System from Harbin Institute of Technology in 2016, China. Her  research focuses on intelligent interpretation of remote sensing images, multimodal information processing, and deep learning. She has published over 90 papers in remote sensing or artificial intelligence journals including IEEE TGRS, IEEE JSTARS, and KBS, etc.

Jiaxin Li received the B.E. degree in Surveying and Mapping Engineering from Chongqing University, in 2020 and the Ph.D. degree in Cartography and Geography Information System from Aerospace Information Research Institute, Chinese Academy of Sciences, in 2025. He is currently a Wenfeng associate professor and post-doctoral at the School of Computer Science and Technology, Chongqing University of Posts and Telecommunications.

Bobo Xi is an Associate Professor and Ph.D. Supervisor at the School of Telecommunication Engineering, Xidian University, China. He received his Ph.D. in Information and Communication Engineering from Xidian University in 2022. His research focuses on hyperspectral image processing, multimodal information processing, and deep learning. He has published over 30 papers in refereed journals including IEEE TIP, IEEE TNNLS, and IEEE TGRS.

Further Information

­­All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisors for this Collection will not be handling the manuscripts.

Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 31 May 2027.

Please contact Alex Johnson at alex.johnson@tandf.co.uk for more information about this Collection or to enquire about discount codes.

Please be sure to select the appropriate Article Collection from the drop-down menu in the submission system.