HAL Id: hal-02828566
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Submitted on 7 Jun 2020
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Retrieval of biophysical variables from remote sensing data on a wheat field in the frame of precision farming
Sophie Moulin, Raúl Zurita Milla, Martine Guerif
To cite this version:
Sophie Moulin, Raúl Zurita Milla, Martine Guerif. Retrieval of biophysical variables from remote sensing data on a wheat field in the frame of precision farming. Information and Technologies for Sustainable Fruit and Vegetable Production, Sep 2005, Montpellier, France. 1 p. �hal-02828566�
Information and Technologies for Sustainable Fruit and Vegetable Production Montpellier, France
12-16 September 2005
Retrieval of biophysical variables from remote sensing data on a wheat field in the frame of precision farming.
Sophie MOULIN, Raùl ZURITA MILLA, Martine GUERIF INRA - Unité Climat, Sol, et Environnement (CSE)
Bât. Climat - Site Agroparc - Domaine Saint-Paul, 84 914 Avignon cedex 9 , FRANCE
Corresponding author : Sophie Moulin
e-mail : sophie.moulin@avignon.inra.fr tel: (+33) 4 32 72 24 13
fax: (+33) 4 32 72 23 62
Precision farming requires the characterization of within field crop growth. In the case of nitrogen fertilization, crop N status may be obtained through remote sensing data acquired in the optical domain, either by inverting radiative transfer models, provided that prior knowledge regarding the crop is available, or through empirical methods.
Biophysical variables such as green leaf area index (gLAI) and leaf chlorophyll content (Cab) which help in characterizing the crop N status were estimated.
The study was based on a ground campaign realized on 2 wheat fields. Biological and ground level radiometric measurements were performed. Moreover, hyperspectral and multispectral radiometric measurements were acquired from airborne and satellite platforms.
The robustness of the variable estimation depends on sensor spectral characteristics in terms of resolution, sampling and number of bands. In the case of variable estimation by inverting radiative transfer models, the estimation was improved by taking into account prior information on retrieved variables.
Results obtained using 3 different radiometric sensors were illustrated. XYBION 6-band camera gave estimation with a 0 .4 m².m-² accuracy for gLAI and 10µg.cm-² for Cab, however, the utilization of empirical methods makes it difficult to generalize the approach.
The SPOT/HRV satellite sensor provided the estimation of gLAI with a 0.4 m².m-² accuracy, nevertheless, due to its sprectral characteristics, leaf chlorophyll content could not be estimated. Finally CASI airborne hyperspectral sensor supplied numerous parameters with a 0 .4 m².m-² accuracy for gLAI and 10µg.cm-² for Cab. The combination of models with hyperspectral sensor makes this tool of investigation very interesting. Space and temporal variations of the estimated variables were finally analyzed.
