A simple approach to monitor crop biomass from C-band radar data

Abstract A simple two-term model of the radar backscattering coefficient of crops, designed for the retrieval of the amount of water in the canopy, is described and analyzed. The principle of the method is to calibrate the simple model from the simulations of a discrete first-order radiative transfer model during crop development. The canopy structure is taken into account in the discrete model to compute the relationships between a) the vegetation direct contribution to backscattering σ ° v and the optical depth τ and b) the optical depth τ and the amount of water in the canopy. The two-term model is tested against C-band radar data acquired over a soybean crop during the whole vegetation cycle. The simulations correlate well with the measurements and the retrieval of the amount of water in the canopy Wc (kg/m 2 ) can be carried out. Accurate temporal information on the crop growth could be derived from the radar data. Ancillary information about soil moisture are required, but it is found that rough estimates on a 4–5 day basis are sufficient.

[1]  G. Guyot,et al.  Estimating surface soil moisture and leaf area index of a wheat canopy using a dual-frequency (C and X bands) scatterometer , 1993 .

[2]  Fawwaz Ulaby,et al.  Microwave Dielectric Spectrum of Vegetation - Part II: Dual-Dispersion Model , 1987, IEEE Transactions on Geoscience and Remote Sensing.

[3]  David M. Le Vine,et al.  Discrete scatter model for microwave radar and radiometer response to corn: comparison of theory and data , 1994, IEEE Trans. Geosci. Remote. Sens..

[4]  A. Fung,et al.  Dependence of the surface backscattering coefficients on roughness, frequency and polarization states , 1992 .

[5]  Yann Kerr,et al.  Microwave emission of vegetation: sensitivity to leaf characteristics , 1993, IEEE Trans. Geosci. Remote. Sens..

[6]  K. Beven,et al.  Soil moisture estimation over grass-covered areas using AIRSAR. , 1994 .

[7]  B. Bouman,et al.  Crop classification possibilities with radar in ERS-1 and JERS-1 configuration , 1992 .

[8]  D. Vidal-Madjar,et al.  The use of a microwave backscatter model for retrieving soil moisture over bare soil , 1992 .

[9]  Richard K. Moore,et al.  Microwave Remote Sensing, Active and Passive , 1982 .

[10]  Y. Kerr,et al.  Use of passive microwave remote sensing to monitor soil moisture , 1998 .

[11]  Leila Guerriero,et al.  A fully polarimetric multiple scattering model for crops , 1995 .

[12]  Frédéric Baret,et al.  Contribution au suivi radiométrique de cultures de céréales , 1986 .

[13]  Adrian K. Fung,et al.  A microwave scattering model for layered vegetation , 1992, IEEE Trans. Geosci. Remote. Sens..

[14]  D. Vidal-Madjar,et al.  Estimation of soil and crop parameters for wheat from airborne radar backscattering data in C and X bands , 1994 .

[15]  F. Ulaby,et al.  Vegetation modeled as a water cloud , 1978 .

[16]  Simonetta Paloscia,et al.  The potential of multifrequency polarimetric SAR in assessing agricultural and arboreous biomass , 1997, IEEE Trans. Geosci. Remote. Sens..

[17]  F. Ulaby,et al.  Microwave Dielectric Behavior of Wet Soil-Part II: Dielectric Mixing Models , 1985, IEEE Transactions on Geoscience and Remote Sensing.

[18]  N. Bruguier,et al.  A simple algorithm to retrieve soil moisture and vegetation biomass using passive microwave measurements over crop fields , 1995 .

[19]  J. Noilhan,et al.  Assimilation of multi-sensor and multi-temporal remote sensing data to monitor vegetation and soil: the Alpilles-ReSeDA project , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[20]  J. Villasenor,et al.  On the use of multi-frequency and polarimetric radar backscatter features for classification of agricultural crops , 1994 .