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Geo-spatial Information Science is a peer-reviewed journal published by Taylor & Francis, covering Geographic Information Systems Studies, Remote Sensing in Agriculture, Data Management and Algorithms.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Geo-spatial Information Science 12 (3): 45–58.
Formats any DOI in Geo-spatial Information Science style. No sign-up. |
| Publishes research in | Geographic Information Systems Studies Remote Sensing in Agriculture Data Management and Algorithms Remote Sensing and LiDAR Applications Remote Sensing and Land Use |
| ISSN | 1009-5020 |
| Citation impact (2-yr) | 4.19 |
| h-index | 58 |
| i10-index | 510 |
| Total citations | 19,734 |
| Article processing charge | $1,993 |
| Open access | Yes |
| Top institutions publishing here | Wuhan University |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Research on unmanned aerial vehicles (UAV) has been increasingly popular in the past decades, and UAVs have been widely used in industrial inspection, remote sensing for mapping & surveying, rescuing, and so on. Nevertheless, the limited autonomous navigation capability severely hampers the application of UAVs in complex environments, such as GPS-denied areas. Previously, researchers mainly…
This paper reviews the key role that Earth Observations (EO) play in achieving the Sustainable Development Goals (SDGs) as articulated in the 2030 Agenda document and in monitoring, measuring, and reporting on progress towards the associated targets. This paper also highlights how the Group on Earth Observations (GEO) would contribute to ensure the actual use…
ABSTRACTA large number of publications have incorporated deep learning in the process of remote sensing change detection. In these Deep Learning Change Detection (DLCD) publications, deep learning methods have demonstrated their superiority over conventional change detection methods. However, the theoretical underpinnings of why deep learning improves the performance of change detection remain unresolved. As of…
In this study, we present a collection of local models, termed geographically weighted \n(GW) models, that can be found within the GWmodel R package. A GW model suits \nsituations when spatial data are poorly described by the global form, and for some \nregions the localised fit provides a better description. The approach uses a moving \nwindow weighting technique, where…
Urbanization is one of the most impactful human activities across the world today affecting the quality of urban life and its sustainable development. Urbanization in Africa is occurring at an unprecedented rate and it threatens the attainment of Sustainable Development Goals (SDGs). Urban sprawl has resulted in unsustainable urban development patterns from social, environmental, and…
