Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 381-384, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-381-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 381-384, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-381-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

RESEARCH ON THE CONSTRUCTION OF REMOTE SENSING AUTOMATIC INTERPRETATION SYMBOL BIG DATA

Y. Gao, R. Liu, J. Liu, and T. Cheng Y. Gao et al.
  • National Geomatics Center of China, 28 Lianhuachi Wet Road, Haidian District, Beijing, China

Keywords: Remote Sensing, Automatic Interpretation Symbol, Big Data, Geographical Conditions Monitoring, Crowdsourcing Update Mode, Open Evaluation, National Wide Application, Database Construction

Abstract. Remote sensing automatic interpretation symbol (RSAIS) is an inexpensive and fast method in providing precise in-situ information for image interpretation and accuracy. This study designed a scientific and precise RSAIS data characterization method, as well as a distributed and cloud architecture massive data storage method. Additionally, it introduced an offline and online data update mode and a dynamic data evaluation mechanism, with the aim to create an efficient approach for RSAIS big data construction. Finally, a national RSAIS database with more than 3 million samples covering 86 land types was constructed during 2013–2015 based on the National Geographic Conditions Monitoring Project of China and then annually updated since the 2016 period. The RSAIS big data has proven to be a good method for large scale image interpretation and field validation. It is also notable that it has the potential to solve image automatic interpretation with the assistance of deep learning technology in the remote sensing big data era.