Big Data Methods for Environmental Data

Authors

WU Bingfang, Institutes of Aerospace information, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China
ZHANG Xin, Institutes of Aerospace information, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
ZENG Hongwei, Institutes of Aerospace information, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
ZHANG Miao, Institutes of Aerospace information, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
TIAN Fuyou, Institutes of Aerospace information, Chinese Academy of Sciences, Beijing 100101, China; Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China

Keywords

resource environment; cloud computing; crowd sourcing geographic data; big data

Document Type

Article

Abstract

Resource and environmental monitoring have always been an important part of land sustainable management which ground survey and remote sensing monitoring are two fundamental ways. The crowd sourcing geographic data (CSGD) brought by smart phones provides new opportunity for the ground investigation of resources and environment. Meanwhile, the rapid development of cloud computing makes it possible to allow people to process massive remote sensing data much more efficient and accurate. Compared with traditional data acquisition methods, data in the cloud is easier to acquire and process. Based on this, a big data method for environment monitoring is introduced based on CSGD and cloud-based resource data. The large amount of human resources required for traditional resource environment monitoring are no longer needed as the professional services of cloud computing are proposed. It will gradually replace the traditional governmental business on resource survey. The participation of the public avoids a large amount of investment. This approach ultimately leads to efficient and crowdsourced resource management.

First page

804

Last Page

811

Language

Chinese

Publisher

Bulletin of Chinese Academy of Sciences

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Recommended Citation

Bingfang, WU; Xin, ZHANG; Hongwei, ZENG; Miao, ZHANG; and Fuyou, TIAN (2018) "Big Data Methods for Environmental Data," Bulletin of Chinese Academy of Sciences (Chinese Version): Vol. 33 : Iss. 8 , Article 6.
DOI: https://doi.org/10.16418/j.issn.1000-3045.2018.08.006
Available at: https://bulletinofcas.researchcommons.org/journal/vol33/iss8/6