Agrispectra

 

          Estimation of Leaf and Crop Biophysical Variables in Olive and Vineyard Canopies through Hyperspectral Remote Sensing Methods for Integration with Precision Agriculture (AgriSpectra). 

 

Funding Institution: Ministerio de Ciencia y Tecnología (MCyT), Ref. AGL2002-04407-C03, 2002-05.


Partners and Team Members:

•  José A. Gómez Calero (PI), Consejo Superior de Investigaciones Científicas (CSIC) - AGL2002-04407-C03-01.

•  Eduardo de Miguel Llanes (PI), Instituto Nacional de Técnica Aeroespacial (INTA) - AGL2002-04407-C03-02.

•  Pablo J. Zarco-Tejada (PI), Universidad de Valladolid (UVA) - AGL2002-04407-C03-03.

 

Contact:

E-mail:

(Coordinator)

 

Summary

Spanish agriculture requires research, development and adoption of precision agriculture methods for a sustainable management of crops and yield optimization (core research area of the 2000-2003 Spanish National Research Plan). Accurate estimation of crop biophysical, and soil parameters are considered a very promising input for a more effective deployment in precision agriculture for optimizing yields. Leaf chlorophyll a+b, leaf water content and leaf area index can be spatially and temporally estimated in the field by remote sensors placed on satellite and airborne platforms. These crop biophysical and soil parameters, which provide a critically needed quantiative measure of crop status and growth limiting factors, can be estimated by radiative transfer model inversion from hyperspectral remote sensing data collected in the visible and near infrared spectral region.

The purpose of this joint research between Universidad de Valladolid (GOA-UVA), Instituto de Agricultura Sostenible (IAS-CSIC) and Instituto Nacional de Técnica Aeroespacial (INTA) is to investigate radiative transfer methods for crop biophysical parameter estimation using hyperspectral remote sensing data in olive and vine canopies. Airborne sensors will be the hyperespectral CASI sensor provided by York University (Canada), and the new MIVIS-AHS sensor adquired by INTA, which will enable hyperspectral image data collection at 1 m spatial resolution in the 400-2500 nm and thermal regions.

Methods will be validated with ground truth leaf, plant and soil samples linked to differential GPS. The study of the leaf optical properties and canopy structure through radiative transfer will enable the estimation of crop biophysical variables with high spatial resolution imagery and new hyperspectral remote sensing techniques.