By Topic

An investigation of cloud cover probability for the HyspIRI mission using MODIS cloud mask data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Gunderson, A. ; Montana State Univ., Bozeman, MT, USA ; Chodas, M.

Cloud cover has an overall negative impact on hyperspectral and multispectral Earth observing sensors; the Hyperspectral Infrared Imaging or HyspIRI mission carries such instruments. A key feature of HyspIRI is its ability to revisit the same point on the equator every 19 days. This allows for better knowledge of the planet's seasonal ecosystem changes. Understanding the likelihood and frequency in which clouds will cover the scenes imaged is necessary to better quantify the science return of HyspIRI and other related missions. Current cloud prediction models are too conservative and only sample small time frames of the available satellite data. This results in a low degree of accuracy with respect to cloud-sensor obscuration and predicts far less of a science return than actual. This study uses a 2007-2009 data set from the Moderate Resolution Imaging Spectrometer (MODIS) on-board the Terra satellite to produce a more accurate prediction of the effects cloud cover has on HyspIRI. The NASA Goddard Spaceflight Center developed Giovanni application was used to extract MODIS data at one-degree spatial resolution. This data created a monthly cloud mask that was averaged into three month blocks to represent seasons. Results show the seasonal data collection probability for HyspIRI's Visual Shortwave Infrared Imaging Spectrometer.

Published in:

Aerospace Conference, 2011 IEEE

Date of Conference:

5-12 March 2011