International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 11–16, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-11-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 11–16, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-11-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  07 Feb 2020

07 Feb 2020

SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA

Y. Dang, J. X. Zhang, P. C. Zhang, F. J. Luo, and J. Bai Y. Dang et al.
  • National Quality Inspection and Testing Centre for Surveying and Mapping Products, P. R. China

Keywords: Natural Resources, Remote sensing, Big Data, Quality Evaluation, Sequential sampling

Abstract. Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a research hotspot when it comes to the natural resources results involving remote sensing big-data. A sequential quality evaluation model based on root mean square error (RMSprop) optimization algorithm is constructed by theoretical analysis with an numerical experiments to validate the effectiveness of this method.