Journal Information
ISPRS Journal of Photogrammetry and Remote Sensing
Impact Factor:
Call For Papers
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The P&RS objective is to publish high quality, peer-reviewed, preferably previously unpublished papers of a scientific/research, technological development or application/practical nature.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:


• 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
Last updated by Dou Sun in 2021-03-07
Special Issues
Special Issue on New Generation of Hyperspectral Remote Sensing Data in the Study of Global Agriculture and Vegetation
Submission Date: 2021-10-31

Guest Editors: Dr. Prasad S. Thenkabail (United States Geological Survey, USA) Prof. Alfredo Huete (University of Technology Sydney, Australia) Prof. Eyal Ben-Dor (Tel Aviv University, Israel) Submission deadline: October 31, 2021 (Begin submissions anytime from November 1, 2020 through October 31, 2021). All papers will be published together in the July 2022 special issue. Planned publication date: July 31, 2022 special issue Great advances in remote sensing are taking place by coming together of: 1. increasingly sophisticated data acquired in H3-mode: hyperspectral (in hundreds of narrow registered bands gathered near-continuously over the electromagnetic spectrum), hyperspatial (<5m spatial resolution), and hyper-temporal (e.g., daily), 2. Machine learningdeep learningartificial intelligence, 3. Cloud computing and code sharing on the cloud, 4. Petabyte-scale big data analytics involving multi-satellite, multi-sensor remote sensing that is harmonized, normalized, and analyzed seamlessly on the cloud, 5. Large web-accessible training and validation data sourced from mobile Apps, very high resolution imagery (VHRI), and secondary sources, 6. Targeted data delivery, in near-real time, through mobile Apps, and 7. Multi domains (laboratory, field, low/ high air altitudes and orbital in both optical and thermal domains. In this regard several new generations of Earth Observing (EO) advanced spaceborne hyperspectral sensors were launched and others are in preparation. Recent launches include the German Aerospace Center’s (Deutsches Zentrum fur Luft- und Raumfahrt; DLR’s) Earth Sensing Imaging Spectrometer (DESIS) integrated into and onboard the International Space Station’s (ISS) Multi-integrated into User-System for Earth Sensing (MUSES) platform, the Italian Space Agency (Agenzia Spaziale Italiana, ASI’s) PRISMA (PRecursore IperSpettrale della Missione Applicativa), Japanese HISUI (Hyperspectral Imager Suite) onboard ISS, India’s HysIS (Hyperspectral Imaging Satellite), China’s Advanced Hyperspectral Imager (AHSI) aboard China's GaoFen-5 (GF-5) satellite, and China’s Jilin Hyperspectral Satellite constellation. These will be followed by several hyperspectral missions coming up for launch such as the German DLR’s the Environmental Mapping and Analysis Program (EnMAP) to be launched soon, NASA’s Surface Biology and Geology (SBG) mission (formerly HyspIRI mission), EMIT from NASA, CHIME from ESA FLEX of ESA, SHALOM from ASI-ISA and more others from private players. These sensors will collect data in hundreds of wavebands and, typically, across the entire visible near and short infrared spectral range (400 to 2500 nanometers ) or part of it, and in 30 m or better GDS. Such data captured as “spectral signatures” leading to spectral libraries will be (and is) a quantum leap in data of the Planet Earth relative to older generation multispectral sensors such as the Landsats and Sentinels which have provided great service in the study of the Planet Earth over last few decades. Nevertheless, such data also provides great challenges in terms of data analysis, algorithm development, and application development. Given the above context, this special issue proposes a comprehensive study of agricultural crops and vegetation based on the data gathered from new generation of hyperspectral data gathered from multiple sensors andor comparison with hyperspectral data from myriad sensors and all spectral and altitude domains. Specific topics of interest include, but not limited to: Quantitative analysis of agricultural crop biophysical, biochemical, and plant health parameters through hyperspectral narrow-bands (HNBs), hyperspectral vegetation indices (HVIs) and comparison with multispectral broadband derived vegetation indices; Crop type classifications using HNB data and comparison with multi-spectral broadband (MBB) data showing improvements in accuracies and reduction in uncertainties; Classification methods and techniques using hyperspectral data for agriculture or vegetation; Machine learningdeep learningartificial intelligence in hyperspectral data analysis; Cloud computing and algorithm development to analyse hyperspectral data for myriad applications in agriculture; Generating spectral libraries as a tool for training and validation of hyperspectral generated cropland products (e.g., crop types, irrigation versus rainfed, biophysical quantities, biochemical quantities, plant health quantities) through machine learning; Hyperspectral data assessment and management by addressing data redundancy and issues of Hughes’ phenomenon; Comparative studies of different generation of hyperspectral data, their inter-comparison and synergies; Florescence measurement of vegetation from air (ASIAIbis) and space (FLEX) missions. Multi and hyperspectral sensing in the thermal region of vegetation – current and feature missions as ECOSTRESS and LSTM missions respectively. The new HSR era from drones (UAV’s) to assess vegetation status Vicarious calibration of HSR sensors Articles must be original research, not published elsewhere. All papers must be comprehensive and thorough with adequate training and validation data, ability to apply the methods across sites, and with proper accuracy and uncertainty analysis. All articles will go through rigorous peer-review process as per the journal norms. Review articles around the topics are also encouraged. Papers must follow the instructions for authors at Please submit the full manuscript to by October 31, 2021. For any inquiry, please contact Dr. Prasad S. Thenkabail (
Last updated by Dou Sun in 2021-03-07
Special Issue on Street-level Imagery Analytics and Applications
Submission Date: 2021-12-31

Guest Editors: Fan Zhang (Massachusetts Institute of Technology, USA) ‪Jan Dirk Wegner (University of Zurich & ETH Zurich, Switzerland)‬‬‬ Bisheng Yang (Wuhan University, China) Yu Liu (Peking University, China) Submission deadline: 31 December 2021 Planned publication date: Summer 2022 Aims and Scope: Street-level imagery refers to the georeferenced photographs taken along street networks, depicting the side view of urban streetscape from a similar view of human vision. With the rapid development of web mapping services, social media platforms, and vehicle-mounted intelligent hardware, street-level imagery, such as Google Street View and social media photos, are growing and blanketing every corner of cities. Compared with satellite imagery, street-level imagery is an alternative imagery data source not only describing the fine-grained physical environment, but also implying socioeconomic status and human dynamics in cities. Compared with traditional data sources describing cities, street-level imagery has some inherent advantages: easy access, cost effective, high spatiotemporal coverage, human perspective, objective and standardized view. Benefited from the advances in deep learning and computer vision techniques, high-level semantic information can be now extracted from images automatically and efficiently. In the past few years, street-level imagery has been widely used in various fields, such as urban planning and design, autonomous vehicles, digital twins and city information modeling, public health, environmental criminology, tourism, real estate and energy consumption. It provides a new perspective to observe human settlement and to further understand the patterns of human-environment interactions. To summarize this trend, this special issue invites submissions broadly contributing to street-level imagery analytics (street view images, geo-tagged photos, camera videos, etc.) Submitted manuscripts could cover but not limited to the following themes: • Street-level imagery collection, mapping and visualization for built-environment auditing • Data fusion of street-level imagery and remote sensing imagery • Methods in image feature extraction, classification and object detection for urban landscape observation (deep learning, computer vision, photogrammetry, etc.) • Image spatial analyses and applications in urban studies and social sensing (built-environment auditing, emission & air pollution, energy consumption, urban planning & design, transportation, human perception & dynamics, etc.) • Image spatial analyses and applications related to the United Nations Sustainable Development Goals (SDGs) • 3D scene analysis and city information modeling • Approaches and applications of multi-source data fusion and integration in urban environments (Google Street Views, social media photos, LiDAR data, satellite imagery, night-time lights, points of interest, traditional survey data, etc.) The full paper should be submitted to ISPRS Journal of Photogrammetry and Remote Sensing via its online submission system at by December 31, 2021. When submitting, use “Street-level Imagery Analytics and Applications” to signify that the submission is part of this special issue. Papers must follow the instructions for authors to be found in the journal's guide for authors. For any inquiry, please contact Dr. Fan Zhang (email:
Last updated by Dou Sun in 2021-03-07
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