The potential of multitemporal and multisensoral remote sensing data for the extraction of biophysical parameters of wheat

Braun M (2005)


Publication Type: Book chapter / Article in edited volumes

Publication year: 2005

Journal

Publisher: International Society for Optical Engineering; 1999

Edited Volumes: Proceedings of SPIE - The International Society for Optical Engineering

City/Town: Bruges

Book Volume: 5976

Pages Range: 404-412

DOI: 10.1117/12.627336

Abstract

Satellite based monitoring of agricultural activities requires a very high temporal resolution, due to the highly dynamic processes on viewed surfaces. The solitary use of optical data is restricted by its dependency on weather conditions. Hence, the synergetic use of SAR and optical data has a very high potential for agricultural applications such as biomass monitoring or yield estimation. Synthetic Aperture Radar data of the ERS-2 offer the chance of bi-weekly data acquisitions. Additionally, Landsat-5 Thematic Mapper (TM) and high-resolution optical data from the Quickbird satellite shall help to verify the derived information. The Advanced Synthetic Aperture Radar (ASAR) of the European environmental satellite (ENVISAT) enables several acquisitions per week, due to the availability of different incidence angles. Moreover, the ASAR sensor offers the possibility to acquire alternating polarization data, providing HH/HV and VV/VH images. This will help to fill time gaps and bring an additional information gain in further studies. In the present study the temporal development of biomass from two winter wheat fields is modeled based on multitemporal and multisensoral satellite data. For this purpose comprehensive ground truth information (e.g. biomass, LAI, vegetation height) was recorded in weekly intervals for the vegetation period of 2005. A positive relationship between the normalized difference vegetation index (NDVI) of optical data and biomass could be shown. The backscatter of SAR data is negatively related to the biomass. Regression coefficients of models for biomass based on satellite data and the collected biomass vary between f2=0.49 for ERS-2 and r 2=0.86 for Quickbird. The study is a first step in the synergetic use of optical and SAR data for biomass modeling and yield estimation over agricultural sites in Central Europe.

Authors with CRIS profile

How to cite

APA:

Braun, M. (2005). The potential of multitemporal and multisensoral remote sensing data for the extraction of biophysical parameters of wheat. In Proceedings of SPIE - The International Society for Optical Engineering. (pp. 404-412). Bruges: International Society for Optical Engineering; 1999.

MLA:

Braun, Matthias. "The potential of multitemporal and multisensoral remote sensing data for the extraction of biophysical parameters of wheat." Proceedings of SPIE - The International Society for Optical Engineering. Bruges: International Society for Optical Engineering; 1999, 2005. 404-412.

BibTeX: Download