Scale Correction of Two-Band Ratio of Red to Near-Infrared Using Imagery Histogram Approach: A Case Study on Indian Remote Sensing Satellite in Yellow River Estuary

Abstract

The imageries collected from two synchronous sensors, i.e., Advanced Wide-Field Sensor (AWiFS) and Linear Imaging Self-Scanner (LISS), on November 1, 2005, November 25, 2005, December 19, 2005, October 27, 2006 and April 13, 2007 in Yellow River Estuary, were used to study the scale error of TBRRN (two-band ratio of red to near-infrared) when scale changed from 24 m to 56 m. The model with a Gaussian plus a constant background was used to depict the distribution of scale error of TBRRN. The result showed that this model produced a good performance for describing the scale error of TBRRN caused by scale changing, whose regression coefficients were larger than 0.970. A scale correction algorithm based on imagery histogram (SCAIH) was constructed to compensate for scale changing from LISS sensor to AWiFS sensor. According to the study results carried out by this study, it was found that the systematical scale error could be greatly improved by SCAIH algorithm, and decreased uncertainty of scale from 5.488% to 3.144%. In water color remote sensing, the 5% uncertainty in TBRRN estimation may result in 35% water quality estimation uncertainty. Therefore, the 2.344% improvement of scale error was very important when we use the TBRRN to retrieval water quality from LISS and AWiFS imageries.