Using Google's cloud-based platform for digital soil mapping
作者： J. Padarian , B. Minasny , A.B. McBratney
DOI: 10.1016/J.CAGEO.2015.06.023
关键词:
摘要: A digital soil mapping exercise over a large extent and at high resolution is computationally expensive procedure. It may take days or weeks to obtain the final maps visually evaluate prediction models when using desktop workstation. To increase speed of time-consuming procedures, use supercomputers common practice. GoogleTM has developed product specifically designed for purposes (Earth Engine), allowing users advantage its computing power mobility cloud-based solution. In this work, we explore feasibility platform by presenting two examples contiguous United States. We also discuss advantages limitations current development stage, potential improvements towards fully functional platform. HighlightsIt possible include as part workflow.Map generation 40-100 times faster compared with traditional mapping.To be complete solution, implementation geostatistical methodologies needed.We encourage researches participate during beta-testing period improve it.
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sci-hub.se 参考文章(39)
Murat Kantarcioglu, Chris Clifton, Jaideep Vaidya, Defining Privacy for Data Mining ,(2002)
I. Rish, An empirical study of the naive Bayes classifier ,(2001)
Dankmar B�hning, Multinomial logistic regression algorithm Annals of the Institute of Statistical Mathematics. ,vol. 44, pp. 197- 200 ,(1992) , 10.1007/BF00048682
Richard A Olshen, Charles J Stone, Leo Breiman, Jerome H Friedman, Classification and regression trees ,(1983)
Susan K. Greenlee, Dean J. Tyler, Michael J. Oimoen, Charles A. Nelson, Dean B. Gesch, Michael J. Steuck, The National Elevation Dataset Photogrammetric Engineering and Remote Sensing. ,vol. 68, pp. 5- 11 ,(2002)
T. M. BURGESS, R. WEBSTER, Optimal interpolation and isarithmic mapping of soil properties. II. Block kriging. European Journal of Soil Science. ,vol. 31, pp. 333- 341 ,(1980) , 10.1111/J.1365-2389.1980.TB02085.X
M. C. Hansen, P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, J. R. G. Townshend, High-Resolution Global Maps of 21st-Century Forest Cover Change Science. ,vol. 342, pp. 850- 853 ,(2013) , 10.1126/SCIENCE.1244693
R. WEBSTER, T. M. BURGESS, Optimal interpolation and isarithmic mapping of soil properties. III. Changing drift and universal kriging. European Journal of Soil Science. ,vol. 31, pp. 505- 524 ,(1980) , 10.1111/J.1365-2389.1980.TB02100.X
B.L. Henderson, E.N. Bui, C.J. Moran, D.A.P. Simon, Australia-wide predictions of soil properties using decision trees Geoderma. ,vol. 124, pp. 383- 398 ,(2005) , 10.1016/J.GEODERMA.2004.06.007
T.F.A. Bishop, A.B. McBratney, G.M. Laslett, Modelling soil attribute depth functions with equal-area quadratic smoothing splines Geoderma. ,vol. 91, pp. 27- 45 ,(1999) , 10.1016/S0016-7061(99)00003-8