Using Google's cloud-based platform for digital soil mapping. (October 2015)

• Record Type: Journal Article
• Authors: Padarian, J.; Minasny, B.; McBratney, A.B.
• Is Part Of: Computers & geosciences. Volume 83(2015)
• Page Start: 80
• Page End: 88
• Publication Date: 2015-10
• Subjects: Supercomputing -- DSM -- Cloud computing -- GlobalSoilMap -- Google Earth Engine; Environmental policy -- Periodicals; 550.5
• DOI: 10.1016/j.cageo.2015.06.023
• Languages: English
• ISSNs: 0098-3004

Abstract

Abstract: A digital soil mapping exercise over a large extent and at a high resolution is a computationally expensive procedure. It may take days or weeks to obtain the final maps and to visually evaluate the prediction models when using a desktop workstation. To increase the speed of time-consuming procedures, the use of supercomputers is a common practice. Google TM has developed a product specifically designed for mapping purposes (Earth Engine), allowing users to take advantage of its computing power and the mobility of a cloud-based solution. In this work, we explore the feasibility of using this platform for digital soil mapping by presenting two soil mapping examples over the contiguous United States. We also discuss the advantages and limitations of this platform at its current development stage, and potential improvements towards a fully functional cloud-based soil mapping platform. Abstract : Highlights: It is possible to include the platform as part of a digital soil mapping workflow. Map generation is 40–100 times faster compared with traditional digital soil mapping. To be a complete solution, implementation of geostatistical methodologies is needed. We encourage researches to participate during the beta-testing period to improve it.