Research of Remote Sensing Evaluation Model Library Platform of Ecological Environment
CSTR:
Author:
Affiliation:

Clc Number:

Fund Project:

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    In the process of constructing an ecological environment evaluation system of remote sensing, due to the business-core development mode, there is high degree of coupling between a variety of business models and the system, and the model reused could be a difficult problem. The development platform restriction of the API library itself leads to the lack of invoking ability for multi-platform.At the mean time, under the background of remote sensing of big data calculation, it is more difficult for the system to cope with the problem that multi-user concurrent requests, long time delay which is caused by wide area coverage calculation and the high system resources occupied. In the view of above problems, the paper puts forward an ecological environment evaluation model library that based on SOA and OpenStack. In terms of model reused and multi-platform invoking problem, 20 kinds of commonly used remote sensing thematic evaluation algorithm models were unified packaging, deployed and concurrent tuned as Web services. To solve the problem of model concurrent processing and large data computing, it utilized OpenStack to solve dynamic load balancing and task allocation for multiple services. On the other side, the paper analyzed the practical problems of core metadata interface design and encapsulates during the process of building a model library, and then provided new design idea. At the end, it developed ecological environment production evaluation that based on Three-river Head Source of Qinghai Province as example, which proved a stable system operation results.

    Reference
    Related
    Cited by
Get Citation
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
History
  • Received:October 28,2015
  • Revised:
  • Adopted:
  • Online: December 30,2015
  • Published: December 31,2015
Article QR Code