GEO-CEOS stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for ESA Earth...

Area of Science:

• Earth Observation (EO)
• Remote Sensing
• Geospatial Analysis

Background:

• ESA defines EO Level 2 products as atmospherically corrected multi-spectral images with scene classification maps (SCMs).
• Systematic generation of ESA EO Level 2 products has been lacking.
• A validation framework (GEO-CEOS stage 4) is required to bridge the gap between EO big data and Level 2 products.

Purpose of the Study:

• To validate the Satellite Image Automatic Mapper (SIAM) for generating ESA EO Level 2 SCMs.
• To assess SIAM's performance against independent reference data.
• To ensure SCM legend compliance with established land cover classification systems.

Main Methods:

• Validation of the SIAM program using annual 30m resolution Web-Enabled Landsat Data (WELD) composites for the conterminous U.S. (2006-2009).
• Comparison of SIAM-generated maps with the USGS National Land Cover Data (NLCD) 2006 map.
• Harmonization of differing map legends to facilitate comparison.

Main Results:

• SIAM systematically generates ESA EO Level 2 SCM product instantiations.
• The generated SCM legends comply with the 2-level, 4-class FAO Land Cover Classification System (LCCS) Dichotomous Phase (DP) taxonomy.
• Independent validation confirmed SIAM's capability to produce compliant SCMs.

Conclusions:

• SIAM is a validated tool for producing ESA EO Level 2 SCMs.
• The study successfully filled an information gap in EO data processing.
• SIAM's output aligns with international land cover classification standards.