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Frontiers in Remote Sensing is a peer-reviewed journal published by Frontiers, covering Remote Sensing in Agriculture, Remote Sensing and LiDAR Applications, Atmospheric aerosols and clouds. Over its lifetime it has published 554 papers, which have received 6,211 citations.
| Publisher | Frontiers |
|---|---|
| Reference style | Author–year (Harvard) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Frontiers in Remote Sensing, 12(3), pp. 45–58.
Formats any DOI in Frontiers in Remote Sensing style. No sign-up. |
| Publishes research in | Remote Sensing in Agriculture Remote Sensing and LiDAR Applications Atmospheric aerosols and clouds Marine and coastal ecosystems Atmospheric Ozone and Climate |
| ISSN | 2673-6187 |
| Citation impact (2-yr) | 3.26 |
| h-index | 35 |
| i10-index | 152 |
| Article processing charge | $1,900 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Goddard Space Flight Center |
| Journal website | www.frontiersin.org |
| 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.
Recent advances in Landsat archive data processing and characterization enhanced our capacity to map land cover and land use globally with higher precision, temporal frequency, and thematic detail. Here, we present the first results from a project aimed at annual multidecadal land monitoring providing critical information for tracking global progress towards sustainable development. The global…
Forest fires contribute to global greenhouse gas emissions and can negatively affect public health, economic activity, and provision of ecosystem services. In boreal forests, fires are a part of the ecosystem dynamics, while in the humid tropics, fires are largely human-induced and lead to forest degradation. Studies have shown changing fire dynamics across the globe…
Advanced inversion Multi-term approach utilizing multiple a priori constraints is proposed. The approach is used as a base for the first unified algorithm GRASP that is applicable to diverse remote sensing observations and retrieving a variety of atmospheric properties. The utilization of GRASP for diverse remote sensing observations is demonstrated.
To support operational lidar applications, transferring research lidars into turnkey systems and reduce their costs are necessary steps. During the last 20 years, advances in industrial lasers improved
