HyperStress - PIF - CSIC


New Methods for Vegetation Stress Detection with Hyperspectral Remote Sensing (HyperStress - PIF - CSIC)

(Nuevos Métodos de Detección de Estrés en Vegetación Mediante Sensores Remotos Hiperespectrales)  


Funding Institution:

Convocatoria de Proyectos Intramurales de Frontera (PIF), Consejo Superior de Investigaciones Científicas (CSIC). Ref. 200440F035.

Partners and Team Members:

•  Instituto de Agricultura Sostenible (IAS), Córdoba.

•  Estación Experimental Aula Dei (EEAD), Zaragoza.

•  Instituto Jaume Almera (IJA), Barcelona.

•  Estación Experimental de Zonas Áridas (EEZA), Almería.

•  Remote Sensing Image Data collection by Instituto Nacional de Técnica Aeroespacial (INTA), Madrid as part of the AGL2002-04407-C03 (Spain) and HyperPeach (Belgium) Projects.




(Principal Investigator)


Project Goals

This research project aims to develop new methods for vegetation stress detection based on airborne and satellite remote sensing hyperspectral and thermal imagery. Traditional remote sensing methods for vegetation monitoring rely on the calculation of normalized indices such as NDVI as indicators of LAI. However, it is well-known and documented that these vegetation indices saturate at high LAI values and are highly affected by canopy structure and BRDF. Furthermore, these vegetation indices are not sensitive to photosynthetic functioning, and only effective for long-term stress detection.

New narrow-band reflectance indices directly related to photosynthetic functioning, i.e. PRI, fluorescence indices calculated on PS-II and PS-I emission bands, and thermal information are potentially useful for monitoring pre-visual short-term stress condition and photosynthetic effects using remote sensing data. In addition, the application of physical modeling and radiative transfer approaches have been shown to have particular promise to accurately estimate canopy variables from remote sensing reflectance to account for canopy architecture and scene components. A narrow-band spectrometer will be tested for canopy reflectance detection of fluorescence in-filling effects in vegetation, linking chlorophyll fluorescence measures with thermal information as indicators of stress condition.