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Google Earth Engine for Geo-Big Data Applications

Special Issue Information

Dear Colleagues,

A multi-petabyte collection of geospatial datasets and satellite imagery are combined with planetary-scale analysis tools in a web platform called the Google Earth Engine (GEE). Today, the Earth Engine is extensively used for geospatial data processing by many scientists, researchers, and developers for several tasks, including Earth Observation (EO) data preparation, image classification, change detection, environmental applications, and even geospatial data visualization. This Special Issue provides an opportunity to bring together research in “Geo-Big Data Analysis using GEE” and highlights ongoing investigations and new applications of geo-big data. In particular, this issue is designed to highlight currently applied research using satellite and Geospatial data processing using GEE to better understand and solve environmental problems at regional, national, and global scales. As such, authors are encouraged to submit high-quality, original research that demonstrates new algorithms, methods, or applications implemented in GEE using geo-big data. We are interested in studies that introduce new techniques for geo-big data analysis, address the challenges of using time series of EO data, and share codes and examples. Furthermore, review papers on environmental monitoring using GEE and geo-big data, as well as case-specific studies that use GEE functions and tools for increasing the scientific understanding of environmental challenges are also welcome.

Potential topics for original research papers and review articles using GEE and geo-big data include, but are not limited to, the following:

  • Land Use and Land Cover (LULC) classification and change detection from a regional to a global scale;
  • Machine learning and deep learning for geo-big data analysis;
  • Crop mapping and yield estimation;
  • Wetland and water resource management from a regional to a global scale;
  • Forest monitoring and biomass estimation;
  • Multi-source and multi-resolution geo-big data analysis;
  • Climate change;
  • Green House Gas (GHG) emission monitoring from a regional to a global scale.

Dr. Masoud Mahdianpari
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • google earth engine
  • geo-big data
  • environmental monitoring
  • machine learning
  • cloud computing
  • satellite imagery

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Published Papers