Extension of retrospective datasets using multiple sensors. An approach to radiometric intercalibration of Landsat TM and MSS data

Abstract

The establishment of monitoring frameworks for environmental problems is frequently based on retrospective, multi-temporal series of satellite images. The derivation of concise conclusions from these series largely depends on their quantitative consistency; hence, a completely standardized analysis of multi-temporal time series is mandatory. In the context of the required radiometric rectification, sensor calibration is an essential component, the accuracy of which largely determines the overall result. While for newer sensor systems extensive documentation on the development of the sensor’s sensitivity exists, older systems often lack the corresponding information. A methodology has been developed, tested and validated to radiometrically intercalibrate different sensor systems based on the precondition of simultaneous image acquisition, which is for example provided by the Landsat TM and MSS sensor systems hosted on Landsat 5. Different interpolation and processing steps within the procedure have been analyzed, and an intercalibration scheme is proposed to derive Landsat MSS calibration factors from Landsat TM, which is used as a calibrated reference. It supports a full radiometric rectification of Landsat MSS data and enables their incorporation into satellite image time series, which can thus be significantly extended by a maximum of 12 years.

Publication
Remote Sensing of Environment, 95(2) 195-210
Tobias Kuemmerle
Tobias Kuemmerle
Professor & Head of the Conservation Biogeography Lab