Using remote sensing data to model water, carbon, and nitrogen fluxes with PROMET-V

Karl Schneider; Wolfram Mauser

doi:10.1117/12.413930

23 January 2001 Using remote sensing data to model water, carbon, and nitrogen fluxes with PROMET-V

Karl Schneider, Wolfram Mauser

Proceedings Volume 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II; (2001) https://doi.org/10.1117/12.413930
Event: Europto Remote Sensing, 2000, Barcelona, Spain

Abstract

The spatially distributed PROcess oriented Modular Environment and Vegetation model (PROMET-V) is presented. PROMET-V models water, carbon and nitrogen fluxes, their interactions and feedback. The model is based on physical and plant physiological equations. Remote sensing data are used to provide spatially distributed model inputs, to update model parameters and to validate model results. Dedicated interfaces were developed to use remote sensing data and to estimate key model parameters. Using LANDSAT TM data, model parameters such as plant density and frequency and date of cutting of meadows were estimated. Comparisons with ground truth measurement showed a significant improvement of the model results by using remote sensing data. Within-field biomass and LAI heterogeneities could be successfully detected. Through interactions and feedback mechanisms, the spatial patterns detected by the TM images also affect model parameters and fluxes which cannot be measured directly. The combined analysis of remotely measured and modeled parameters bears the potential to determine parameters which cannot be derived directly with either method alone, such as weed infestation or soil texture. Remote sensing data are also used to provide independent validation data. Examples are shown using soil moisture maps derived from ERS SAR data.

Citation Download Citation

Karl Schneider and Wolfram Mauser "Using remote sensing data to model water, carbon, and nitrogen fluxes with PROMET-V", Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); https://doi.org/10.1117/12.413930

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