Journal Information
ISPRS Journal of Photogrammetry and Remote Sensing
https://www.sciencedirect.com/journal/isprs-journal-of-photogrammetry-and-remote-sensingImpact Factor: |
12.2 |
Publisher: |
Elsevier |
ISSN: |
0924-2716 |
Viewed: |
13954 |
Tracked: |
4 |
Call For Papers
Official Publication of the International Society for Photogrammetry and Remote Sensing (ISPRS) The ISPRS Journal of Photogrammetry and Remote Sensing (P&RS) is the official journal of the International Society for Photogrammetry and Remote Sensing (ISPRS). The Journal provides a channel of communication for scientists and professionals in all countries working in the many disciplines that employ photogrammetry, remote sensing, spatial information systems, computer vision, and related fields. The Journal is designed to serve as a source reference and archive of advancements in these disciplines. The P&RS objective is to publish high quality, peer-reviewed, preferably previously unpublished papers of a scientific/research, technological development or application/practical nature. P&RS will publish papers, including those based on ISPRS meeting presentations*, which are regarded as significant contributions in the above-mentioned fields. We especially encourage papers: of broad scientific interest; on innovative applications, particularly in new fields; of an interdisciplinary nature; on topics that have not been dealt with (or to a small degree) by P&RS or related journals; and on topics related to new possible scientific/professional directions. Preferably, theoretical papers should include applications, and papers dealing with systems and applications should include theoretical background. The scope of the journal is extensive and covers sensors, theory and algorithms, systems, experiments, developments and applications. Topics of interest include but are not limited to: Sensors • Airborne and spaceborne multispectral and hyperspectral imaging systems • Airborne and terrestrial cameras • Airborne, terrestrial and mobile laser scanning • Range imaging • Active and passive imaging sensor characterisation • Sensor calibration and standardisation • Geosensor networks • Internet of Things Methods and procedures • Spatial data handling technologies • Integrated sensor calibration and orientation • Surface and object reconstruction, modelling and interpretation • GIS data modelling, representation and structures • Database systems • Mapping from imagery • Visualisation, animation and virtual reality • Physical measurements and spectral signatures • Point cloud processing • Extraction of geometric and semantic information from SAR • SAR Interferometry • Image classification algorithms • Image segmentation and GEOBIA • Image time series analysis • Hyperspectral data analysis • Big image data analysis • Crowd sourcing • Feature extraction Applications and products • 3D urban GIS • Close-range imaging and metrology • Architectural & archaeological photogrammetry • Determination of forest metrics • Medical image analysis and biometry • Resource and environmental modelling • Global monitoring and assessment • Thematic applications • DTM and orthoimage generation • Location based services Submitted articles may be: • Papers (detailed discussions involving new research, technological developments or applications); • Review Papers (extensive state-of-the-art surveys of established or emerging topics or application areas); or • Contributions for special Journal columns (letters to the Editor about the journal or to authors commenting on previously published papers; new useful ideas and brief pertinent comments of a technical nature; editorials, mainly after an invitation by the Editorial Advisory Board). NOTE: All articles, except correspondence, will be peer-reviewed and should be of high scientific level. * Journal paper submissions based on past conference publications are only allowed if the submitted manuscript is significantly extended or otherwise enhanced. That is, the journal article will only be considered if more extensive experiments and discussion are presented (even if the same methods are used) and/or the methods have been significantly improved and/or advanced (even if the same datasets have been used). The burden of explicitly describing the differences between these publications rests with the author(s). In case of a strong overlap with another publication, the manuscript should be rejected. P&RS issues may be devoted to specific scientific topics of high or increasing importance (Theme Issues), especially in relation to one or more ISPRS Working Groups, as well as to special events, geographic regions, professional activities etc. The number and topics of Theme Issues will be such that the P&RS still remains of interest to the majority of its subscribers. For more details on the International Society for Photogrammetry and Remote Sensing, visit http://www.isprs.org.
Last updated by Dou Sun in 2025-08-02
Special Issues
Special Issue on Digital Construction: Geospatial Science and Computer Vision Transforming the Construction IndustrySubmission Date: 2025-12-31This special issue aims to promote interdisciplinary research and enhance interaction and collaboration in various areas of digital construction including photogrammetry, sensor systems, surveying engineering, computer vision, robotics, and the application of geospatial technologies in the AEC sector. Guest editors: Kourosh Khoshelham Infrastructure Engineering, The University of Melbourne, Swanston St Carlton, Australia k.khoshelham@unimelb.edu.au Mehdi Maboudi Institute of Geodesy and Photogrammetry, TU Braunschweig, Braunschweig, Germany m.maboudi@tu-bs.de Yelda Turkan Civil & Construction Engineering, Oregon State University, Corvallis, OR, USA yelda.turkan@oregonstate.edu Jónatas Valença LNEC - Laboratório Nacional de Engenharia Civil, Structural Monitoring Unit, Lisbon, Portugal jvalenca@lnec.pt Special issue information: The Architecture, Engineering, and Construction (AEC) industry is undergoing significant transformation with the integration of digital technologies. Within this interdisciplinary environment, geospatial science and computer vision play a crucial role. This transformation necessitates the development of new approaches and strategies in areas such as spatial data acquisition and reality capture (e.g., various sensors, algorithms, and technologies such as drones, robotic platforms, SLAMalgorithms, positioning, imaging, and laser scanning), data processing and 3D modeling (e.g., automated registration, assembly, scan-to-BIM, change detection, object localization, detection and tracking), and specific applications in construction engineering (e.g., automated inspection, digital twins, additive manufacturing in construction, progress monitoring, and safety hazard identification). This context motivated the establishment of a new working group within the ISPRS (ICWG II/I b) in 2022. The first biannual workshop on “Digital Construction” was held successfully at ISPRS GSW2023 in Cairo, Egypt. The second workshop is scheduled to take place at GSW2025 in Dubai, UAE. The purpose of this special issue is to promote interdisciplinary research and enhance interaction and collaboration in digital construction among researchers working in photogrammetry, sensor systems, surveying engineering, computer vision, robotics and the AEC sector. The relevant topics include but are not limited to: Opportunities and challenges that digital construction and various 3D printing methods (contour crafting, shotcrete, particle-bed, etc.) bring to the current data capturing and inspection methodologies Analysis and selection of sensors and systems for the purpose of reality capture and automated inspection in digital construction (from component to building scale) Building Information Modelling (BIM) and Digital Twins Progress monitoring for large construction projects (buildings, bridges, etc.) Data exchange between inspection systems and BIM/FIM Augmented Reality and Mixed Reality in digital construction• As-built vs. as-designed and evaluation of geometric conformity in 3D printing (co-registration, inspection metrics, etc.) Computer vision in digital construction: Co-registration, detection, localization, and tracking of the moving robots and sensors Automated risk assessment and safety hazard identification Increasing automation (IoT, Industry 4.0, etc.) and remote inspection Manuscript submission information: To submit your manuscript please go to https://www.editorialmanager.com/photo/default.aspx and follow the procedures for manuscript submission by selecting our Special Issue Article type as "VSI: Digital Construction”. Submission Deadline: 31 December 2025 Author Guidelines and Manuscript Submission can be found at: https://www.sciencedirect.com/journal/isprs-journal-of-photogrammetry-and-remote-sensing/publish/guide-for-authors Keywords: Reality capture, Building Information Modelling, BIM, Digital Twin, Automation
Last updated by Dou Sun in 2025-08-02
Special Issue on Interpretability and explainability in GeoAI for Geospatial Science and Earth ObservationsSubmission Date: 2026-05-31In recent years, Geospatial Artificial Intelligence (GeoAI), has demonstrated significant value in social, urban, environmental and Earth sciences. GeoAI integrates AI with geospatial science and technology, uniquely modeling spatial effects to solve complex geographical problems, revealing hidden patterns, and advancing theories. Its dual role bridges scientific discovery and real-world impact. However, the "black-box" nature and inherent complexity of GeoAI models present substantial challenges. In GeoAI for science, interpretability is not merely desirable but indispensable. The task of facilitating scientific discovery and advancing knowledge in this field directly relies on the ability to understand and interpret model decisions and behaviors. To meet this demand, GeoAI models must either be designed with inherent interpretability—achieved by explicitly embedding spatial effects, mechanism, and rules into their design—or be supported by a robust suite of explainability methods capable of explaining model behaviors and outputs. Meanwhile, we have seen significant developments in XAI methods. For instance, integrating physical models or empirical laws directly into the model design to make them inherently interpretable; and also, employing post-hoc explainability methods to interpret the behavior of complex models. Notable XAI techniques, such as LIME, SHAP, Grad-CAM, Integrated Gradients, and GNN Explainer, have been developed and applied to various data types—including images, text, graphs, and tabular data—and have seen exponential growth in geospatial applications. However, current applications of XAI in geospatial science and earth observations are still primarily centered on post-hoc explainability methods. While these approaches can faithfully reflect model behavior, they often fall short in uncovering the internal mechanisms of models or the underlying spatial data-generating processes. Although some efforts have been made toward enhancing model interpretability, particularly by integrating location information or domain knowledge, such approaches remain scarce and underdeveloped. These limitations underscore the urgent need for further innovation to advance both the explainability and interpretability of GeoAI models, thereby fully realizing their potential for scientific discovery and practical applications. Advancing explainable GeoAI (XGeoAI) methods is thus critical for enhancing the quality, transparency, and scientific value of research in geospatial science and earth observations. We invite contributions that address these challenges, including but not limited to the following areas: Explainability and interpretability in geospatial foundation models Spatially explicit XAI methods for GeoAI Intrinsically interpretable GeoAI model design Physics-aware machine learning in GeoAI Causal inference and discovery in GeoAI Ethical concerns, fairness, bias detection and uncertainty quantification in GeoAI XAI for earth observation imagery and spatial big data XAI applications in urban, environmental and ecosystems Scalability and computational efficiency of XAI in geospatial contexts Geovisual analytics, people sensors, and human-centered XGeoAI Large language models (LLMs) and vision language models (VLMs) in XGeoAI Evaluation frameworks for XGeoAI This special issue aims to advance the application of XGeoAI in geospatial science and earth observations, fostering cross-disciplinary innovation and knowledge exchange, and enhancing the interpretability and societal impact of research outcomes. Papers must be original contributions, not previously published or submitted to other journals. Conference papers may be considered provided that they are considerably extended and improved. Substantive research and relevant-for-practice papers will be preferred. Review articles around the topics are also encouraged. Papers must follow the instructions for authors at http://www.elsevier.com/journals/isprs-journal-of-photogrammetry-and-remote-sensing/0924-2716/guide-for-authors. For any inquiry, please contact Dr. Fan Zhang (fanzhanggis@pku.edu.cn). Guest editors: Dr. Fan Zhang Peking University, Beijing, China fanzhanggis@pku.edu.cn Dr. Ziqi Li Florida State University, Tallahassee, FL, USA ziqi.li@fsu.edu Dr. Xiao Huang Emory University, Atlanta, GA, USA xiao.huang2@emory.edu Dr. Xiaoxiang Zhu Technical University of Munich, Munich, Germany xiaoxiang.zhu@tum.de Manuscript submission information: To submit your manuscript please go to https://www.editorialmanager.com/photo/default.aspx and follow the procedures for manuscript submission by selecting our Special Issue Article type as "VSI: XGeoAI”. Submission Deadline: 31 May 2026 Author Guidelines and Manuscript Submission can be found at: https://www.sciencedirect.com/journal/isprs-journal-of-photogrammetry-and-remote-sensing/publish/guide-for-authors Keywords: GeoAI; XAI; Interpretable Models; AI for Geosciences; AI Explainability
Last updated by Dou Sun in 2025-08-02
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