Total solution approach using IRS-1C and IRS-P3 data

High spectral(10 nm) and radiometric (16 bits) resolutions of IRS-P3:MOS-B coupled with moderate spatial resolution (188 m) of IRS-P3:WiFS provide uni que solutions to many problems related to sustainable management of ecosyst ems. While the high spatial resolutions of IRS-1C PAN and IRS-1C LISS-3 hel p in identifying the structural attributes of the biosphere, a synthetic pr oduct of MOS-B and WiFS offers immense potential to address several crucial issues including improved classification accuracy in heterogeneous land co vers, environmental stress, improved vegetation signal-to-noise ratio, etc, In this paper, the operational issues such as multisensor calibration and validation, registration and merging of multisensor data from different pla tforms, identification of red edge using IRS-P3:MOS-B data, resolving subpi xel heterogeneity, scale anomalies and uncertainty in spectral estimates of biophysical variables are discussed, With the integration of parameters se nsitive to atmospheric scattering and soil background reflectance into NDVI derived from the synthetic image, the spectral index called soil adjusted and atmospheric resistant vegetation index (SARVI) has been found to be mor e sensitive to biophysical variables such as leaf area index (LAI) and frac tion of absorbed photosynthetically active radiation (FPAR), It has also re duced, up to certain extent, the uncertainty related to the spectral measur ements of bio-physical variables, Further study, in this regard, aims at ev aluating the changes in entropy with the fusion of high spectral, radiometr ic, spatial, and temporal data.