Applying Fuzzy Sets to Composite Algorithm for Remote Sensing Data

Abstract

Remote sensing of the earth surface using satellite mounted sensor data is a major method for global environmental monitoring today. However, when using satellite sensor data, clouds in the atmosphere can interfere with the readings, and specific land points may not be correctly monitored on a given day. In order to overcome this problem, multiple day composite data is frequently used. Multiple day composite data uses several consecutive days’ remote sensing data, and picks the most accurate data within the temporal dataset for the same land point. This allows creating a more complete dataset by patching together data not interfered by clouds during a specified time period, to create a clearer, more usable dataset. In this paper, we propose applying fuzzy set logic in order to select the clearest data in the temporal interval for the composite data. Moderate resolution remote sensing data of areas in Japan were used for evaluation.