Share Email Print

Journal of Applied Remote Sensing • Open Access

Methodology for geographical data evolution: three-dimensional particle-based real-time snow simulation with remote-sensing data
Author(s): Jian Tan; Xiangtao Fan; Yingchoa Ren

Paper Abstract

Even if current remote-sensing technology provides more spatial information, remote-sensing data with discontinuous spatial and temporal resolutions are still not adequate. To compensate for the missing data of remote sensing, we create a methodology for geographical data evolution from a snow simulation. Numerical algorithms based on snow simulation and environmental phenomenon interaction algorithms are presented to evolve remote-sensing data in a virtual environment. Specifically, the methodology involves the establishment of a suitable three-dimensional data model and the discrete numerical expressions of geological or geographical phenomena. The modeling solution of environmental phenomena reactions is based on remote-sensing data. This computational simulation does not merely generate new data and spatial resolutions at a given time, but it offers multiscale environmental characteristics of the Earth and presents reference for its future scene.

Paper Details

Date Published: 26 November 2013
PDF: 17 pages
J. Appl. Rem. Sens. 8(1) 084598 doi: 10.1117/1.JRS.8.084598
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Jian Tan, Institute of Remote Sensing and Digital Earth (China)
Xiangtao Fan, Institute of Remote Sensing and Digital Earth (China)
Yingchoa Ren, Institute of Remote Sensing and Digital Earth (China)

© SPIE. Terms of Use
Back to Top