Share Email Print
cover

Proceedings Paper

The analysis on parameters of the payload on hyperspectral satellite
Author(s): Daming Wang; Fang Hou; Zhizhong Li; Fuxing Dang; Rihong Yang; Zhenghao Xiao
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

This paper focuses on the analysis and selection of space-borne hyperspectral sensor parameters, through the simulation of the entire data acquisition process and the applications using simulated hyperspectral data. Aiming at the alteration mineral identification and mapping, we used the simulated space-borne hyperspectral data with different payload parameters including the spatial resolution, spectral resolution and Signal-to-Noise-Rate (SNR) from HyMAP air-borne hyperspectral data in Dongtianshan area in Xinjiang Province of China to identify and map the alteration minerals, so that we could analyze and compare these results to find the optimal combination of payload parameters. A combination of the parameters of 30m spatial resolution, 10 - 20nm spectral resolution and 200:1 (VNIR) / 150:1 (SWIR) SNR was evaluated to possess the strongest ability for the mineral identification and mapping. This technology can also be promoted by the other payload parameter analysis and selection.

Paper Details

Date Published: 15 August 2011
PDF: 7 pages
Proc. SPIE 8203, Remote Sensing of the Environment: The 17th China Conference on Remote Sensing, 820307 (15 August 2011); doi: 10.1117/12.910365
Show Author Affiliations
Daming Wang, China Aero Geophysical Survey & Remote Sensing Ctr. for Land and Resources (China)
Fang Hou, Capital Normal Univ. (China)
Zhizhong Li, China Geological Survey (China)
Fuxing Dang, China Aero Geophysical Survey & Remote Sensing Ctr. for Land and Resources (China)
Rihong Yang, China Aero Geophysical Survey & Remote Sensing Ctr. for Land and Resources (China)
Zhenghao Xiao, China Aero Geophysical Survey & Remote Sensing Ctr. for Land and Resources (China)


Published in SPIE Proceedings Vol. 8203:
Remote Sensing of the Environment: The 17th China Conference on Remote Sensing
Qingxi Tong; Xingfa Gu; Boqin Zhu, Editor(s)

© SPIE. Terms of Use
Back to Top