A Physical Explanation of the Variation in Threshold for Delineating Terrestrial Water Surfaces from Multi-Temporal Images: Effects of Radiometric Correction

Abstract

Multi-temporal satellite images are widely used to delineate objects of interest for monitoring surface changes. Threshold value(s) are often determined from a histogram of a delineation index. However, the threshold determined may vary and be case-dependent, with images taken at different times. Although the variation is well known, its cause remains unclear, and this raises doubts about the reliability of the classification results. This study selects three widely used indices, the near-infrared (NIR) band, the normalized difference vegetation index (NDVI) and the normalized difference water index (NDWI), all of which can be used to delineate water surfaces. Our theoretical analysis reveals that sensor calibration, the Sun?target?satellite geometry and the atmospheric optical properties create synthetic effects on the satellite’s digital number (DN) and, subsequently, on the thresholds for delineation. The DN-based threshold has a significant dependence on the reflectance-based counterpart, which has been proved with multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data for the Poyang Lake region of China. Our results show that a DN-based threshold is generally higher than a reflectance-based one, and ?90% of the difference is accounted for by temporal influences. A quantification of the temporal influences provides a physical explanation to the variation in thresholds, and the findings should be valuable for improving the reliability of long-term studies using multi-temporal images.

Publication
International Journal of Remote Sensing
Jian Peng
Jian Peng
Professor for Hydrology and Remote Sensing / Head of Remote Sensing Department (UFZ)

I am the head of the Department of Remote Sensing at the UFZ and a full professor for Hydrology and Remote Sensing at the University of Leipzig.