Data

GeoAI Systematic Review Dataset: Remote Sensing, Vegetation and Hydrology Studies in Polar Regions (2005–2025)

Australian Antarctic Division

Amarasingam, N., Vomero, M., Platel, A., Newman, C., Robinson, S. and Bollard, B. ; AMARASINGAM, NARMILAN ; VOMERO, MARIAPINA ; PLATEL, ARTHUR ; NEWMAN, CASSANDRA ; ROBINSON, SHARON ; BOLLARD, BARBARA

Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]

ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26179/w4cn-xy95&rft.title=GeoAI Systematic Review Dataset: Remote Sensing, Vegetation and Hydrology Studies in Polar Regions (2005–2025)&rft.identifier=10.26179/w4cn-xy95&rft.publisher=Australian Antarctic Data Centre&rft.description=This dataset contains all materials generated during a systematic review of artificial intelligence and remote sensing research focused on vegetation and hydrology in the Arctic and Antarctic from 2005 to 2025. It includes the full set of screened records, documentation of inclusion and exclusion decisions, structured summaries of all eligible studies, bibliographic files, and thematic groupings used to classify research domains. Also provided are network-ready text files describing author collaborations, keyword co-occurrence patterns, and conceptual linkages within the literature. Each spreadsheet and text file includes clear explanations of column names, variable meanings, and dataset structure to ensure long-term usability.A repository containing workflow documentation, figures, and supporting materials is available at:https://github.com/Narmilan-A/Systematic-Review-ToolkitProgress Code: completed&rft.creator=Amarasingam, N., Vomero, M., Platel, A., Newman, C., Robinson, S. and Bollard, B. &rft.creator=AMARASINGAM, NARMILAN &rft.creator=VOMERO, MARIAPINA &rft.creator=PLATEL, ARTHUR &rft.creator=NEWMAN, CASSANDRA &rft.creator=ROBINSON, SHARON &rft.creator=BOLLARD, BARBARA &rft.date=2025&rft.coverage=westlimit=144.75586; southlimit=-43.2932; eastlimit=147.83203; northlimit=-37.64903&rft.coverage=westlimit=144.75586; southlimit=-43.2932; eastlimit=147.83203; northlimit=-37.64903&rft_rights=These data are publicly available for download from the provided URL.&rft_rights=Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/legalcode&rft_rights=This data set conforms to the CCBY Attribution License (http://creativecommons.org/licenses/by/4.0/). Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4628_Polar_GeoAI_Prisma_Review when using these data.&rft_rights=This metadata record is publicly available.&rft_subject=imageryBaseMapsEarthCover&rft_subject=EARTH SCIENCE > BIOSPHERE > VEGETATION&rft_subject=EARTH SCIENCE > MODELS > MACHINE LEARNING MODELS&rft_subject=EARTH SCIENCE > MODELS > MACHINE LEARNING MODELS > NEURAL NETWORKS&rft_subject=EARTH SCIENCE > CRYOSPHERE > SNOW/ICE > SNOW MELT&rft_subject=EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER&rft_subject=EARTH SCIENCE > DATA ANALYSIS AND VISUALIZATION > IMAGE PROCESSING&rft_subject=ANTARCTIC&rft_subject=LITERATURE DATABASE&rft_subject=SYSTEMATIC REVIEW&rft_subject=ARTIFICIAL INTELLIGENCE&rft_subject=BIBLIOMETRIC ANALYSIS&rft_subject=PRISMA 2020&rft_subject=GEOAI&rft_subject=MACHINE LEARNING&rft_subject=DEEP LEARNING&rft_subject=VEGETATION–HYDROLOGY INTERACTIONS&rft_subject=ARCTIC&rft_subject=DATA EXTRACTION&rft_subject=SCREENING DATASET&rft_subject=REMOTE SENSING&rft_subject=POLAR ECOSYSTEMS&rft_subject=NETWORK ANALYSIS&rft_subject=UAV–SATELLITE INTEGRATION&rft_subject=HYDROLOGY&rft_subject=MULTISENSOR FUSION&rft_subject=CLIMATE CHANGE IMPACTS&rft_subject=IMAGE ANALYSIS&rft_subject=RGB CAMERAS&rft_subject=MULTISPECTRAL REFLECTANCE&rft_subject=EARTH OBSERVATION SATELLITES&rft_subject=VEGETATION MAPPING&rft_subject=HYPERSPECTRAL REFLECTANCE&rft_subject=HIGH-RESOLUTION OPTICAL SATELLITES&rft_subject=MEDIUM-RESOLUTION OPTICAL SATELLITES&rft_subject=4628&rft_subject=AAS 4628&rft_subject=MSS_RS > Multispectral imaging system&rft_subject=GSA > Hyperspectral imaging equipment&rft_subject=CAMERAS&rft_subject=TIRS > Thermal Infrared Sensor&rft_subject=SATELLITES > SATELLITES&rft_subject=LANDSAT > LANDSAT&rft_subject=Sentinel-6A > Sentinel-6A&rft_subject=WORLDVIEW-4 > DigitalGlobe WORLDVIEW-4&rft_subject=UAV > Unmanned Aerial Vehicle&rft_subject=Airplane > Airplane&rft_subject=FIELD SURVEYS > FIELD SURVEYS&rft_subject=AMD/AU&rft_subject=CEOS&rft_subject=AMD&rft_subject=CONTINENT > ANTARCTICA&rft_subject=GEOGRAPHIC REGION > ARCTIC&rft_subject=GEOGRAPHIC REGION > POLAR&rft.type=dataset&rft.language=English Access the data

Access data via landing page
http://data.aad.gov.au...

Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Open Licence view details

Attribution 4.0 International (CC BY 4.0)
https://creativecommons.org/licenses/by/4.0/legalcode

These data are publicly available for download from the provided URL.

This data set conforms to the CCBY Attribution License (http://creativecommons.org/licenses/by/4.0/). Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4628_Polar_GeoAI_Prisma_Review when using these data.

This metadata record is publicly available.

Access:

Other

Full description

This dataset contains all materials generated during a systematic review of artificial intelligence and remote sensing research focused on vegetation and hydrology in the Arctic and Antarctic from 2005 to 2025. It includes the full set of screened records, documentation of inclusion and exclusion decisions, structured summaries of all eligible studies, bibliographic files, and thematic groupings used to classify research domains. Also provided are network-ready text files describing author collaborations, keyword co-occurrence patterns, and conceptual linkages within the literature. Each spreadsheet and text file includes clear explanations of column names, variable meanings, and dataset structure to ensure long-term usability.

A repository containing workflow documentation, figures, and supporting materials is available at:https://github.com/Narmilan-A/Systematic-Review-Toolkit

Lineage

Progress Code: completed

Notes

Purpose
The purpose of this dataset is to provide a transparent, reusable, and fully documented evidence base that supports the systematic review of GeoAI methods, applied to vegetation and hydrology in polar regions. The dataset enables: (i) reproducibility of the screening and selection process; (ii) re-analysis of bibliometric networks; (iii) comparison across remote sensing platforms, sensors, and AI approaches; and (iv) long-term availability of cleaned, structured metadata for researchers investigating Arctic and Antarctic environmental change. Future users can employ these files to update the review, build benchmark datasets, or examine methodological trends in polar ecosystem monitoring.

Data time period: 2005-01-01 to 2025-01-31