Remote sensing and modeling the dynamics of soil moisture and vegetative cover of arid and semiarid areas

Xiwu Zhan; Wei Gao; Jiaguo Qi; Paul R. Houser; James R. Slusser; Xiaoling Pan; Zhiqiang Gao; Yingjun Ma

doi:10.1117/12.505670

22 December 2003 Remote sensing and modeling the dynamics of soil moisture and vegetative cover of arid and semiarid areas

Xiwu Zhan, Wei Gao, Jiaguo Qi, Paul R. Houser, James R. Slusser, Xiaoling Pan, Zhiqiang Gao, Yingjun Ma

Author Affiliations +

Proceedings Volume 5153, Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture; (2003) https://doi.org/10.1117/12.505670
Event: Optical Science and Technology, SPIE's 48th Annual Meeting, 2003, San Diego, California, United States

Abstract

With the large volume of satellite remote sensing data of the earth terrestrial surface becoming available, precisely monitoring the dynamics of the land surface state variables for agricultural and land use management becomes possible. Currently, the moderate resolution imaging spectroradiometers on board NASA’s Earth Observing Satellites (EOS) Terra and Aqua make it possible to derive a global coverage of land surface vegetation indices, leaf area index, and surface temperature data products at 1 km spatial resolution every day. The advanced microwave scanning radiometers (AMSR) on board Aqua and Japan's ADEOS satellites start sending back a global coverage of rainfall and land surface soil moisture data products at up to 25km spatial resolution every two to three days. It is also well known that these land surface remote sensing products contain uncertainties due to imperfect instrumentation calibration and inversion algorithms, geophysical noise, representativeness error, communication breakdowns, and other sources while land surface model can continuously simulate these land surface state or storage variables for all time steps and all covered areas. Therefore a combination of satellite remote sensing products and land surface model simulations may provide more continuous, precise and comprehensive depiction of the dynamics of the land surface states. This paper introduces the state-of-the-arts technologies in the development of NASA's Land Data Assimilation System, and then proposes a procedure to combine the simulations of a simple land surface model and the remote sensing products from MODIS and AMSR. After the results of testing the procedure for an arid area in Southwest USA are presented, the application of the procedure for the oases in Fukang Count of Xinjiang Autonomous Region is proposed.

Citation Download Citation

Xiwu Zhan, Wei Gao, Jiaguo Qi, Paul R. Houser, James R. Slusser, Xiaoling Pan, Zhiqiang Gao, and Yingjun Ma "Remote sensing and modeling the dynamics of soil moisture and vegetative cover of arid and semiarid areas", Proc. SPIE 5153, Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture, (22 December 2003); https://doi.org/10.1117/12.505670

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