Scaling from instantaneous remote-sensing-based latent heat flux to daytime integrated value with the help of SiB2

Yi Song; Mingguo Ma; Xin Li; Xufeng Wang

doi:10.1117/12.897951

7 October 2011 Scaling from instantaneous remote-sensing-based latent heat flux to daytime integrated value with the help of SiB2

Yi Song, Mingguo Ma, Xin Li, Xufeng Wang

Author Affiliations +

Proceedings Volume 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII; 81741W (2011) https://doi.org/10.1117/12.897951
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

This research dealt with a daytime integration method with the help of Simple Biosphere Model, Version 2 (SiB2). The field observations employed in this study were obtained at the Yingke (YK) oasis super-station, which includes an Automatic Meteorological Station (AMS), an eddy covariance (EC) system and a Soil Moisture and Temperature Measuring System (SMTMS). This station is located in the Heihe River Basin, the second largest inland river basin in China. The remotely sensed data and field observations employed in this study were derived from Watershed Allied Telemetry Experimental Research (WATER). Daily variations of EF in temporal and spatial scale would be detected by using SiB2. An instantaneous midday EF was calculated based on a remote-sensing-based estimation of surface energy budget. The invariance of daytime EF was examined using the instantaneous midday EF calculated from a remote-sensing-based estimation. The integration was carried out using the constant EF method in the intervals with a steady EF. Intervals with an inconsistent EF were picked up and ET in these intervals was integrated separately. The truth validation of land Surface ET at satellite pixel scale was carried out using the measurement of eddy covariance (EC) system.

Citation Download Citation

Yi Song, Mingguo Ma, Xin Li, and Xufeng Wang "Scaling from instantaneous remote-sensing-based latent heat flux to daytime integrated value with the help of SiB2", Proc. SPIE 8174, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIII, 81741W (7 October 2011); https://doi.org/10.1117/12.897951

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available