1. General Model Information

Name: SBFLEVO_OPT - Program to calibrate crop growth model SBFLEVO* for sugar beet in Flevoland on optical reflectance and/or radar backscatter data.

Acronym: SBFLEVO_OPT


Main medium: terrestrial
Main subject: agriculture, hydrology
Organization level: ecosystem, population
Type of model: static-algebraic equations
Main application: simulation/optimisation tool
Keywords: optimization algorithm, inverse problem methodology, parameter estimation,crop growth, sugar beet, remote sensing, photosynthesis, light interception, light reflection, radar backscatter, optical reflectance

Contact:

Dr.ir. B.A.M. Bouman.
Research Institute for Agrobiology and Soil Fertility (AB-DLO), Dept. Agrosystems Research, P.O.Box 14, 6700 AA Wageningen, THE NETHERLANDS.
Phone: +31.317.475972
Fax: +31.317.423110
email: b.a.m.bouman@ab.dlo.nl

Author(s):

Abstract:

This model parameterizes the combined 'remote sensing - crop model' for sugar beet on measured time series of optical reflectance (vegetation indices) and/or radar backscatter. The values of the crop parameters sow date, relative growth rate, light use efficiency and maximum leaf area are optimized in such a way that the difference between simulated and measured time courses of the remote sensing signals is minimal. [The optimization procedure can also be applied using measured values of crop parameters (e.g. leaf area index, biomass)]. The optimized values of the crop growth and final yield of the sugar beet crop from which the remote sensing observations have been taken.

Purpose of the model:

Model parentage: SBFLEVO and FSEOPT.

Source of the AbstractCAMASE Register of Agro-ecosystems Models


II. Technical Information

II.1 Executables:

Operating System(s): VAX computer, IBM compatible PC/AT >= 640 Kb RAM.
Contract necessary:
Costs: : Dfl. 270,=.
Comments:

II.2 Source-code:

Programming Language(s): Microsoft FORTRAN-77.

II.3 Manuals:



II.4 Data:



III. Mathematical Information


III.1 Mathematics


III.2 Quantities

Rate variables: Phenological development, leaf and canopy photosynthesis (gross, net), maintenance and growth respiration, crop growth, growth of plant organs.

State variables: Biomass (total, and per crop organ leaf, stem, root, tuber), leaf area index, soil cover, intercepted light. Auxiliary variables: reflected solar radiation, vegetation indices, radar backscatter.

III.2.1 Input

Geographical latitude and longitude, weather data (daily radiation, minimum and maximum temperature), top soil moisture content, crop specific physiological and morphological properties, canopy reflection characteristics, canopy and soil radar backscatter; crop management information. Input check in model: -

III.2.2 Output

Optimized values for the model parameters sow date, relative growth rate, light use efficiency, maximum leaf area. These data can be used in the model SBFLEVO* to simulate crop growth, yield, optical reflection and radar backscatter.
Basic spatial unit: Field level (some m2).
Time interval of simulation: 1 day.

IV. References


Bouman, B.A.M., 1992. Linking physical remote sensing models with crop growth simulation models, applied to sugar beet. International Journal of Remote Sensing vol 13 no. 14: 2565-2581
Clevers, J.G.P.W., C. Buker, H.J.C. van Leeuwen & B.A.M. Bouman, 1994. A framework for Monitoring crop growth by combining directional and spectral remote sensing information. Accepted for publication in Remote Sensing of Environment 1994.

Bouman, B.A.M., 1992. SBFLEVO_OPT, A program to calibrate the crop growth model SBFLEVO for sugar beet in Flevoland on optical reflectance and/or radar backscatter data. CABO-DLO report 164. CABO-DLO Wageningen, The Netherlands. 104 pp.


V. Further information in the World-Wide-Web

  • BAckscatter Modelling
  • 7. Appendix: PIK Available Model Toolbox 1996

    VI. Additional remarks

    Parentage: SBFLEVO and FSEOPT.
    Last review of this document by: T. Gabele: Dec 10 1997
    Status of the document:
    last modified by Joachim Benz Mon Jul 2 18:31:37 CEST 2007

    Go back to Register of Ecological Models (R E M)