Write in a clean editor, then format for Big Earth Data in one click — DocuGuru applies the official Taylor & Francis template with author–year references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
Big Earth Data is a peer-reviewed journal published by Taylor & Francis, covering Remote Sensing in Agriculture, Geographic Information Systems Studies, Climate variability and models.
| 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." Big Earth Data 12 (3): 45–58.
Formats any DOI in Big Earth Data style. No sign-up. |
| Publishes research in | Remote Sensing in Agriculture Geographic Information Systems Studies Climate variability and models Land Use and Ecosystem Services Cryospheric studies and observations |
| ISSN | 2096-4471 |
| Citation impact (2-yr) | 2.68 |
| h-index | 38 |
| i10-index | 133 |
| Total citations | 6,181 |
| Article processing charge | $1,024 |
| Open access | Yes |
| Top institutions publishing here | Chinese Academy of Sciences |
| 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.
Multi-temporal, globally consistent, high-resolution human population datasets provide consistent and comparable population distributions in support of mapping sub-national heterogeneities in health, wealth, and resource access, and monitoring change in these over time. The production of more reliable and spatially detailed population datasets is increasingly necessary due to the importance of improving metrics at sub-national and…
Landslides are one of the most destructive natural hazards; they can drastically alter landscape morphology, destroy man-made structures, and endanger people’s life. Landslide susceptibility maps (LSMs), which show the spatial likelihood of landslide occurrence, are crucial for environmental management, urban planning, and minimizing economic losses. To date, the majority of research into data mining LSM…
With the development of earth observation technologies, the acquired remote sensing images are increasing dramatically, and a new era of big data in remote sensing is coming. How to effectively mine these massive volumes of remote sensing data are new challenges. Deep learning provides a new approach for analyzing these remote sensing data. As one…
Big data is a revolutionary innovation that has allowed the development of many new methods in scientific research. This new way of thinking has encouraged the pursuit of new discoveries. Big data occupies the strategic high ground in the era of knowledge economies and also constitutes a new national and global strategic resource. “Big Earth…
Pressures on natural resources are increasing and a number of challenges need to be overcome to meet the needs of a growing population in a period of environmental variability. Some of these environmental issues can be monitored using remotely sensed Earth Observations (EO) data that are increasingly available from a number of freely and openly…
