Remote Sensing in Earth Systems Sciences is a quarterly scientific journal that publishes articles featuring the use of remote sensing data to study Earth processes. The journal’s interdisciplinary approach aims to include all aspects of the Earth Sciences including Atmospheric Sciences, Biogeosciences, Climate/Climate Change, Hydrology, the Cryosphere and Oceans, while placing great emphasis on articles that exist on the border of, or even transcend subfields.
In addition, the journal’s scope encompasses everything from drone research to the latest governmental satellite missions. Articles that demonstrate uses and techniques for managing the “big data” generated are welcome.
To remain on the cutting edge of the field, Remote Sensing in Earth Systems Sciences prefers medium-length articles that can be written and reviewed in a timely manner but retain a high level of detail and depth, although longer articles, as well as letters, are also considered.
Information on Open Research Funding and Support may be found here: https://www.springernature.com/gp/open-research/institutional-agreements
If you are a corresponding author affiliated with a German university or research institution, you are entitled to publish open access in our journals with fees covered by the German DEAL agreement.
More than 900 German institutions are eligible to participate in the agreement between Springer Nature and Projekt DEAL, meaning that corresponding authors affiliated with these institutions are eligible to publish their articles open access without being invoiced by Springer Nature. The agreement includes more than 2,000 hybrid journals across the Springer Nature portfolio (from January 2020) and more than 500 fully OA journals (from August 2020).
- Venkat Lakshmi
- Publishing model
- Hybrid (Transformative Journal). Learn about publishing Open Access with us
- 118 days
- Submission to first decision
- 216 days
- Submission to acceptance
- 14,968 (2019)
Authors (first, second and last of 5)
Classification of Synthetic Aperture Radar-Ground Range Detected Image Using Advanced Convolution Neural Networks
Comparative Assessment of Vegetation Indices in Downscaling of MODIS Satellite Land Surface Temperature
Attribute Profiles of Different Attributes for Spectral-Spatial Classification of Hyperspectral Imagery
Authors (first, second and last of 4)
About this journal
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- Institute of Scientific and Technical Information of China
- Japanese Science and Technology Agency (JST)
- OCLC WorldCat Discovery Service
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