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

Vanessa Heinzel; Björn Waske; Matthias Braun; Gunter Menz

doi:10.1117/12.627336

19 October 2005 The potential of multitemporal and multisensoral remote sensing data for the extraction of biophysical parameters of wheat

Vanessa Heinzel, Björn Waske, Matthias Braun, Gunter Menz

Author Affiliations +

Proceedings Volume 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII; 59761K (2005) https://doi.org/10.1117/12.627336
Event: SPIE Remote Sensing, 2005, Bruges, Belgium

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 r²=0.49 for ERS-2 and r²=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.

Citation Download Citation

Vanessa Heinzel, Björn Waske, Matthias Braun, and Gunter Menz "The potential of multitemporal and multisensoral remote sensing data for the extraction of biophysical parameters of wheat", Proc. SPIE 5976, Remote Sensing for Agriculture, Ecosystems, and Hydrology VII, 59761K (19 October 2005); https://doi.org/10.1117/12.627336

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