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ISPRS Journal of Photogrammetry

and Remote Sensing

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The P&RS objective is to publish high quality, peer-reviewed, preferably previously unpublished papers of a scientific/research, technological development or application/practical nature.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.

论文列表

ISPRS GEE 2020

A spatially explicit surface urban heat island database for the United States: Characterization, uncertainties, and possible applications.

Improved land cover map of Iran using Sentinel imagery within Google Earth Engine and a novel automatic workflow for land cover classification using migrated training samples.

Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine.

Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine.

Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping.

Google Earth Engine for geo-big data applications: A meta-analysis and systematic review.

Mapping coastal wetlands of China using time series Landsat images in 2018 and Google Earth Engine.

Global high-resolution mountain green cover index mapping based on Landsat images and Google Earth Engine.

The migration of training samples towards dynamic global land cover mapping.

Examining earliest identifiable timing of crops using all available Sentinel 1/2 imagery and Google Earth Engine.

Annual large-scale urban land mapping based on Landsat time series in Google Earth Engine and OpenStreetMap data: A case study in the middle Yangtze River basin.

ISPRS GEE 2019

Participatory mapping of forest plantations with Open Foris and Google Earth Engine.

Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine.

Automatic mapping of planting year for tree crops with Landsat satellite to time series stacks.

A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine.

ISPRS GEE 2018-2017

An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support.

A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform.

Automated cropland mapping of continental Africa using Google Earth Engine cloud computing.

A mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform.

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