Adaptation of the MIMICS backscattering model to the agricultural context-wheat and canola at L and C bands

Presents the results obtained from the MIMICS (Michigan Microwave Canopy Scattering) forest backscattering model which was modified to accommodate agricultural parameters. In the MIMICS model, the forest canopy is divided into three regions: the crown layer, the trunk region, and the underlying rough ground. The crop cover situation is simulated by a rough ground and a crown layer composed of scatterers with different forms, distributions, and dielectric constants. The authors omit trunks from the final agricultural representation because these components are of the same order as the wavelength, contrary to the model's implicit assumptions. The simulation results are compared to ground based scatterometer data of wheat and canola. The paper describes the simulation results for the two crops at L and C bands and the two like polarizations. An analysis of the different backscattering mechanisms is also given for each crop. Good simulation results were obtained at L and C bands for HH polarization for both these crops throughout the growing season. An error analysis indicates that the soil moisture can be predicted with a precision better than 0.03 g/cm/sup 3/ for both crops, if all other model parameters are known. In addition, if the moisture is known, the height of the stems and the diameter of the leaves of the canola crop can be estimated with a precision better than /spl plusmn/5 cm and /spl plusmn/0.5 cm, respectively. >

[1]  Fawwaz T. Ulaby,et al.  A three-part geometric model to predict the radar backscatter from wheat, corn, and sorghum , 1982 .

[2]  E. Engman Progress in microwave remote sensing of soil moisture , 1990 .

[3]  Kamal Sarabandi,et al.  Preliminary analysis of ERS-1 SAR for forest ecosystem studies , 1992, IEEE Trans. Geosci. Remote. Sens..

[4]  M. A. Karam,et al.  Scattering from randomly oriented circular discs with application to vegetation , 1983 .

[5]  Kamal Sarabandi,et al.  Michigan microwave canopy scattering model , 1990 .

[6]  R. J. Brown,et al.  Land Applications Of Radarsat , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.

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

[8]  N. Goel,et al.  Simple Beta Distribution Representation of Leaf Orientation in Vegetation Canopies1 , 1984 .

[9]  A. Fung,et al.  Scattering from a Vegetation Layer , 1979, IEEE Transactions on Geoscience Electronics.

[10]  L. Tsang,et al.  Radiative transfer theory for active remote sensing of a layer of small ellipsoidal scatterers. [of vegetation] , 1981 .

[11]  R. Protz,et al.  Corn Field Identification Accuracy Using Airborne Radar Imagery , 1980 .

[12]  A. K. Fung,et al.  A scatter model for vegetation up to Ku-band , 1984 .

[13]  R. J. Brown,et al.  Applying the Mimics Backscattering Model in an Agricultural Context , 1991 .

[14]  Roger H. Lang,et al.  Electromagnetic backscattering from a sparse distribution of lossy dielectric scatterers , 1981 .

[15]  R. J. Brown,et al.  Temporal ground-based scatterometer observations of crops in Western Canada , 1992 .

[16]  T. Le Toan,et al.  Application Of Random Medium Model To Remote Sensing Of Vegetation , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[17]  Roger H. Lang,et al.  Electromagnetic Backscattering from a Layer of Vegetation: A Discrete Approach , 1983, IEEE Transactions on Geoscience and Remote Sensing.

[18]  A. P. Luscombe The Radarsat Synthetic Aperture Radar System , 1989, 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium,.

[19]  E. T. Engman Microwave remote sensing of soil moisture, progress, potential and problems , 1995, 1995 International Geoscience and Remote Sensing Symposium, IGARSS '95. Quantitative Remote Sensing for Science and Applications.

[20]  W. Kuhbauch,et al.  Capacity Of Multifrequency And Multipolarization Sar-systems In Remote Sensing Of Crop Species And Crop Yield , 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.

[21]  R. J. Brown,et al.  SAR applications in agriculture A comparison of steep and shallow mode (30° and 53° incidence angles) data , 1989 .

[22]  Fawwaz T. Ulaby,et al.  An evaluation of radar as a crop classifier , 1978 .