ACIX and CMIX are international collaborative initiatives to inter-compare a set of atmospheric correction (AC) and cloud masking (CM) algorithms for high-spatial resolution optical sensors. The exercises will focus on Sentinel-2 and Landsat-8 data over a set of test areas. The inter-comparison of the derived cloud masks is expected to contribute to a better understanding of strengths and weaknesses of different algorithms and ultimately to contribute to a reduction of a major error source for atmospheric correction and surface parameter retrievals. Similarly, the study of Bottom-of-Atmosphere (BOA) products will assist in understanding the different uncertainty contributors and improving the AC processors.

Introduction

The first ACIX experiment started in June 2016 with the aim to bring together the developers of the state-of-the-art atmospheric correction (AC) processors and to study the variations amongst the different approaches. The input data were Landsat-8 and Sentinel-2A products over various sites of different land cover types around the world, i.e. agricultural, deserts, urban, snow and coastal areas. The description and the conclusions of this first experiment are summarised in Doxani et al. (2018). All the inter-comparison results can be found in the dedicated to ACIX I web page in CEOS Cal/Val portal. The improved versions of the participating processors and the increasing interest from AC developers to be part of the experiment stimulated the continuation of ACIX and its second implementation (ACIX II).

Following the recommendations of ACIX participants and other Earth Observation data users, an additional inter-comparison of cloud masking assessment was decided to be performed in parallel with ACIX. Cloud masking is a crucial step of the radiometric pre-processing of optical remotely sensed data and an important contributor to the retrieval of accurate surface reflectance within an atmospheric correction process. Therefore, it was considered essential to analyse these two processing chains together.

The test sites of the exercises will be redefined and more representative cases concerning land surface and atmospheric conditions, e.g. land/water, land cover, aerosols. Particular attention will be given also to aquatic sites, i.e. coastal and inland waters, which will be analysed as a separate sub-category. The scheme below describes the implementation of CMIX and ACIX II, which will run in parallel and follow the same timeline:

Objectives and Expected Outcomes

The exercises brought together the developers of CM and AC algorithms and related software processors. The corresponding protocols were defined together by coordinators and participants and it was mandatory to be followed by all the participants of the exercises. The input data are Landsat-8, Sentinel-2A and -2B products of various test sites, covering various land cover types, i.e. agricultural, coastal, snow, water, deserts etc. The participants generate the corresponding CM and AC products, which are validated following the corresponding protocols.

Objectives of the 2^nd workshop

• To better understand surface and water reflectance uncertainty contributors by comparing the outputs of different AC schemes
• To identify and review the different uncertainty contributors in CM and AC
• To propose further improvements of the available CM and AC schemes

Expected Outcomes of the 2^nd workshop

• Assessment of the relative differences among the inter-compared CM and AC processors results
• Definition of key regions and key periods for validation and quality assessment
• Description of a coordinated plan for inter-comparison and validation activities

Schedule and Deadline