Stage 4 validation of the Satellite Image Automatic Mapper lightweight computer program for Earth observation Level 2 product generation, Part 2 Validation
This work addresses an information gap in Earth Observation for remote sensing applications, but it is incremental as it validates an existing program rather than introducing new methods.
The paper tackled the lack of systematically generated Earth Observation Level 2 products by validating the Satellite Image Automatic Mapper (SIAM) program using Web Enabled Landsat Data composites of the U.S., achieving results that instantiate a Level 2 scene classification map product with a legend based on the FAO Land Cover Classification System taxonomy.
The European Space Agency (ESA) defines an Earth Observation (EO) Level 2 product as a multispectral (MS) image corrected for geometric, atmospheric, adjacency and topographic effects, stacked with its scene classification map (SCM) whose legend includes quality layers such as cloud and cloud-shadow. No ESA EO Level 2 product has ever been systematically generated at the ground segment. To contribute toward filling an information gap from EO big sensory data to the ESA EO Level 2 product, a Stage 4 validation (Val) of an off the shelf Satellite Image Automatic Mapper (SIAM) lightweight computer program for prior knowledge based MS color naming was conducted by independent means. A time-series of annual Web Enabled Landsat Data (WELD) image composites of the conterminous U.S. (CONUS) was selected as input dataset. The annual SIAM WELD maps of the CONUS were validated in comparison with the U.S. National Land Cover Data (NLCD) 2006 map. These test and reference maps share the same spatial resolution and spatial extent, but their map legends are not the same and must be harmonized. For the sake of readability this paper is split into two. The previous Part 1 Theory provided the multidisciplinary background of a priori color naming. The present Part 2 Validation presents and discusses Stage 4 Val results collected from the test SIAM WELD map time series and the reference NLCD map by an original protocol for wall to wall thematic map quality assessment without sampling, where the test and reference map legends can differ in agreement with the Part 1. Conclusions are that the SIAM-WELD maps instantiate a Level 2 SCM product whose legend is the FAO Land Cover Classification System (LCCS) taxonomy at the Dichotomous Phase (DP) Level 1 vegetation/nonvegetation, Level 2 terrestrial/aquatic or superior LCCS level.