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Application of a Quantitative Approach Through Mathematical Inversion of a Vegetation Canopy Reflectance Model for Crop Monitoring Using Satellite Remote Sensing

Hafizur Rahman
Bangladesh Space Research and Remote Sensing Organization (SPARRSO) Agargaon, Shere Bangla Nagar Dhaka-1207, BANGLADESH

Md. Nur Hossain Sharifee
Bangladesh Space Research and Remote Sensing Organization (SPARRSO) Agargaon, Shere Bangla Nagar Dhaka-1207, BANGLADESH

Sukumar Dutta
Bangladesh Space Research and Remote Sensing Organization (SPARRSO) Agargaon, Shere Bangla Nagar Dhaka-1207, BANGLADESH

Abstract/ Executive Summary:

A quantitative approach has been made to retrieve biophysical information of an agricultural crop using multidirectional remote sensing data. The approach consists of retrieving the parameters of the surface bidirectional reflectance model through model inversion against directional data generated by a directional radiative transfer model. Model inversion has been performed applying a non-linear optimization scheme against the simulated directional vegetation reflectance data. The technique provides a reasonably good estimation of the canopy biophysical parameters. Remote sensing data are usually contaminated by different atmospheric effects. As a remedial, standard data correction procedure is available that requires a precise estimation of intervening atmospheric parameters. In this connection, estimation accuracies of biophysical parameters of vegetation have been analyzed with simulated satellite data corrected with improper values of atmospheric aerosol contents. The study reveals that estimation can be significantly influenced by the use of improper values of aerosol content during data correction. Estimation accuracy is higher in the near-infrared as compared to that in the visible for both high and low density canopies. Moreover, accuracy is higher for a low density canopy in comparison to that for a dense vegetation canopy.

Keywords: Vegetation canopy, Optimization, Biophysical parameter, LAI, Reflectance

Location: Dhaka, Bangladesh

Start Date:

End Date:

Program Area: Crop-Soil-Water Management

Non-commodity: Remote sensing

Objectives:

To determine an Application of a Quantitative Approach through Mathematical Inversion of a Vegetation Canopy Reflectance Model for Crop Monitoring Using Satellite Remote Sensing

Methodology:

The SAIL (Scattering by Arbitrary Inclined Leaves) canopy reflectance model (Verhoef, 1984) has been employed in the present work. The model expresses the reflectance of a vegetation canopy as a function of the viewing and solar zenith and azimuth angles. Model inputs are solar and viewing zenith and azimuth angles, leaf transmittance and reflectance, soil reflectance, diffuse sky radiances, leaf area index and the leaf angle distribution (LAD). Reflectance data have been generated at the top of the atmosphere (TOA) applying the Coupled Surface Atmosphere Reflectance (CSAR) model developed by Rahman et al. (1993). The model expresses, the reflectance at the top of the atmosphere ρTOA. TOA reflectances ρTOA are generated in the visible and NIR region of the solar spectrum corresponding to channel 1 and channel 2 of NOAA AVHRR, using equation 1 from each of the above data set under an atmospheric aerosol loading of 0.2 at 550 nm. The simulated data are then corrected from atmospheric scattering effect by using different aerosol optical depth at 550 nm, δ550, from 0.17 to 0.24 by step of 0.1, which resulted in improperly corrected (with under estimation and over estimation in aerosol content) and properly corrected data. These corrected data are then used to estimate different biophysical parameters of the canopy reflectance model through the optimization of the model (equation 1) using a non-linear optimization technique (Rahman, 2011). An average continental model of aerosol has been considered throughout the study. The values of the canopy parameters namely leaf transmittance and reflectance, soil reflectance, leaf area index (LAI) and diffuse sky light are retrieved through application of the inversion procedure against the simulated data. Values of leaf angle distribution (LAD) were introduced directly during inversion to minimize the total number of parameters to be estimated. The accuracy of the retrieved canopy parameters is evaluated in terms of percent relative error (RE) as calculated from Pt and Pe (true and estimated values respectively). RE = 100 x ( P_t-P_e)/p_t.

Source of Information: Dhaka University Journal of Earth and Environmental Sciences, Vol. 4, December 2015

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Recent development of satellite borne sensors like POLDER, MISR, MODIS etc., have opened a new avenue for space technology-based geoinformation acquisition. In the present study, crop biophysical parameters have been quantitatively estimated through application of inversion scheme using directional remote sensing data. The study reveals that such a numerical approach provides reasonably accurate estimation of different parameters of the canopy reflectance model for contamination free data. The effect of improper atmospheric correction of satellite data on the accuracy of the retrieved parameter values has been investigated. Retrieval accuracy of different crop biophysical parameters is not equally affected by the same atmospheric perturbations. Atmospheric correction of data with improper values of atmospheric aerosol content plays a major role on the accuracy of the retrieved parameter values, The study also reveals that estimation of different vegetation parameters for a low density canopy is more accurate than that for a dense vegetation canopy.

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