The Effect of Radiometric Resolution on the Retrieval of Leaf Area Index from Agricultural Crops

Motivated by the increasing availability of remote sensing data of high radiometric resolution, a study was conducted to determine whether high-resolution data (10 bits or more) yielded more accurate vegetation leaf area index (LAI) information than low-radiometric-resolution multispectral data (7-bit or less). The study evaluated the performance of simulated 12-bit LISS-III sensor data (derived from EO-1 hyperspectral Hyperion data) with original 7-bit LISS-III sensor data for the estimation of LAI of major agricultural crops (e.g., cotton, sugar cane, and rice). There was no significant improvement in the correlation coefficient encountered when using the high-radiometric-resolution (12-bit) LISS-III data versus the low-radiometric-resolution (7-bit) LISS-III data for the retrieval of LAI. The retrieval of LAI of agricultural crops met with moderate success, with overall correlation coefficients of around 0.55. These results suggest that satellite data of very high radiometric resolution may not be a required for remote measurement of LAI. Spectral bandwidth, band placement, and the method of retrieving biophysical parameters may be more important.