Sentinel-1 data are an alternative for monitoring flooded inland surfaces during cloudy periods. Supervised classification approaches with a single-trained model for the entire image demonstrate poor accuracy due to confusing backscatter conditions of the inundated areas in relation with the prevailing land cover features. This study follows instead a pixel-centric approach, which exploits the varying backscatter values of each pixel through a time series of Sentinel-1 images to train local Random Forest classification models per 3×3 pixels, and classifies each pixel in the target Sentinel-1 image, accordingly. Reference training data is retrieved from the timely close Sentinel-2-derived inundation maps. This study aims to identify the furthest mean day difference between the target Sentinel-1 image and available Sentinel-2 high accurate inundation maps (kappa coefficient-k > 0.9) that allows for the estimation of credible inundation maps for the Sentinel-1 target date. Various combinations of Sentinel-2 and Sentinel-1 training datasets are examined. The evaluation for eight target dates confirms that a Sentinel-1 inundation map with a k of 0.75 on average can be generated, when mean day difference is less than 30 days. The increment of the considered Sentinel-2 maps allows for the estimation of Sentinel-1 inundation maps with higher accuracy.

This article provides an overview of worldwide web and e-Learning resources for Earth Observation (EO) education for secondary schools. The main EO education initiatives supported by international, EU and national organizations. The article elaborates on future prospects of EO education in the education system its relevance for the society and its connection with STEM subjects.

This article is a continuation of an overview of the contemporary resources for Earth Observation (EO) education for secondary schools. The themes covered by the sequel are the main EO education initiatives supported by international, EU and national organizations, outreach activities, citizen scientists’ projects and free and open source software (FOSS) EO tools. The article elaborates on future prospects of EO resources developments in the education system its relevance for the society and its connection with STEM subjects.