Cloud Data and Computing Services Allow Regional Environmental Assessment:A Case Study of Macquarie-Castlereagh Basin, Australia

被引:0
|
作者
WU Hantian [1 ]
ZHANG Lu [2 ]
ZHANG Xin [3 ]
机构
[1] Fenner School of Environment and Society, Australia National University
[2] Land and Water, The Commonwealth Scientific and Industrial Research Organization
[3] Institute of Remote Sensing and Digital Earth, Chinese Academy of Science
关键词
regional environment assessment; cloud platform; Google Earth Engine(GEE); land use; Macquarie-Castlereagh catchment;
D O I
暂无
中图分类号
X821 [区域环境质量评价];
学科分类号
083305 ;
摘要
Large amounts of data at various temporal and spatial scales require terabyte(TB) level storage and computation, both of which are not easy for researchers to access. Cloud data and computing services provide another solution to store, process, share and explore environmental data with low costs, stronger computation capacity and easy access. The purpose of this paper is to examine the benefits and challenges of using freely available satellite data products from Australian Geoscience DataCube and Google Earth Engine(GEE) online data with time series for integrative environmental analysis of the Macquarie-Castlereagh Basin in the last 15 years as a case study. Results revealed that the cloud platform simplifies the procedure of traditional catalog data processing and analysis. The integrated analysis based on the cloud computing and traditional methods represents a great potential as a low-cost, efficient and user-friendly method for global and regional environmental study. The user can save considerable time and cost on data integration. The research shows that there is an excellent promise in performing regional environmental analysis by using a cloud platform. The incoming challenge of the cloud platform is that not all kinds of data are available on the cloud platform. How data are integrated into a single platform while protecting or recognizing the data property, or how one portal can be used to explore data archived on different platforms represent considerable challenges.
引用
收藏
页码:394 / 404
页数:11
相关论文
共 22 条
  • [1] The Australian Geoscience Data Cube — Foundations and lessons learned[J] . Adam Lewis,Simon Oliver,Leo Lymburner,Ben Evans,Lesley Wyborn,Norman Mueller,Gregory Raevksi,Jeremy Hooke,Rob Woodcock,Joshua Sixsmith,Wenjun Wu,Peter Tan,Fuqin Li,Brian Killough,Stuart Minchin,Dale Roberts,Damien Ayers,Biswajit Bala,John Dwyer,Arnold Dekker,Trevor Dhu,Andrew Hicks,Alex Ip,Matt Purss,Clare Richards,Stephen Sagar,Claire Trenham,Peter Wang,Lan-Wei Wang.Remote Sensing of Environment . 2017
  • [2] Google Earth Engine: Planetary-scale geospatial analysis for everyone[J] . Noel Gorelick,Matt Hancher,Mike Dixon,Simon Ilyushchenko,David Thau,Rebecca Moore.Remote Sensing of Environment . 2017
  • [3] Automated cropland mapping of continental Africa using Google Earth Engine cloud computing[J] . Jun Xiong,Prasad S. Thenkabail,Murali K. Gumma,Pardhasaradhi Teluguntla,Justin Poehnelt,Russell G. Congalton,Kamini Yadav,David Thau.ISPRS Journal of Photogrammetry and Remote Sensin . 2017
  • [4] Seasonal vegetation response to climate change in the Northern Hemisphere (1982–2013)[J] . Dongdong Kong,Qiang Zhang,Vijay P. Singh,Peijun Shi.Global and Planetary Change . 2017
  • [5] Landsat 8: Providing continuity and increased precision for measuring multi-decadal time series of total suspended matter[J] . Leo Lymburner,Elizabeth Botha,Erin Hestir,Janet Anstee,Stephen Sagar,Arnold Dekker,Tim Malthus.Remote Sensing of Environment . 2016
  • [6] Detecting industrial oil palm plantations on Landsat images with Google Earth Engine[J] . Janice Ser Huay Lee,Serge Wich,Atiek Widayati,Lian Pin Koh.Remote Sensing Applications: Society and Environm . 2016
  • [7] Comparing Landsat water index methods for automated water classification in eastern Australia[J] . Adrian Fisher,Neil Flood,Tim Danaher.Remote Sensing of Environment . 2016
  • [8] Water observations from space: Mapping surface water from 25years of Landsat imagery across Australia[J] . N. Mueller,A. Lewis,D. Roberts,S. Ring,R. Melrose,J. Sixsmith,L. Lymburner,A. McIntyre,P. Tan,S. Curnow,A. Ip.Remote Sensing of Environment . 2015
  • [9] Using Google's cloud-based platform for digital soil mapping[J] . J. Padarian,B. Minasny,A.B. McBratney.Computers and Geosciences . 2015
  • [10] A scalable satellite-based crop yield mapper[J] . David B. Lobell,David Thau,Christopher Seifert,Eric Engle,Bertis Little.Remote Sensing of Environment . 2015