Awesome

Chapter 2

15 years and to be prolonged 10-30 meters consistent uncertainty quantified global analysis ready dataset

Feng Yin
Department of Geography, UCL
ucfafyi@ucl.ac.uk

In this Chapter, I will introduce the SIAC (Sensor Invariant Atmospheric Correction) developed under the European Union’s Horizon 2020 MULTIPLY project can be used to generate global uncertainty quantified analysis ready datasets after 2003, which covered by NASA Landsat 5-8 missions and ESA Senitinel 2 mission.

First I will give a simple introductions of the SIAC method and then I will test SIAC method for several Landsat and Sentinel 2 images to illustrate its usage with various sensors. The validation of SIAC method are done for Sentinel 2 and Landsat 8 images and a map showing the AOT validation againsts the AERONET measurements across the worldm, also the top of atmosphere (TOA) reflectance and bottom of atmosphere (BOA) are displayed for each validation site. Further validation of other Landsat sensors AC will be done in the following studies, so in this chapter the major purpose is to demonstrate the applicability of SIAC method for different sensors.