Portal was established in the frames of EOPOWER project (Earth Observation for Economic Empowerment) under 7. Frame Programme of European Union. The main aim is to create conditions for sustainable economic development through the increased
Over the last years, many features describing satellite images have been proposed. In this paper we analyse and compare fractal and multifractal features in the context of the discrimination of the four most common
From 4th to 12th May two of our software developers, Adam Włodarkiewicz and Krzysztof Stopa together with two android developers, Danny Preussler (Grupon) and Johannes Orgis (6Wunderkinder) from Berlin, have been selected to participate
This project is dedicated to support European Space Agency and the Oil and Gas Producers EO(OGP EO) sub-committee establish the key geo-information requirement needs of the onshore oil and gas sector throughout the oil
The goal of the project is to perform feasibility study of land cover classification based on SAR Sentinel-1 images. Currently used algorithms dedicated to land cover classification on SAR images does not give the
The Project financed under ESA PECS contract (Plan for European Cooperating States). The main aim is to use satellite images (optical and radar) to determine the optimal location for energy crops, in terms of
Initiated in 2007, the Area Frame Sampling Europe subtask of the Seasonal and Annual Change Monitoring Service (SATChMo) Core Service in the geoland2 project delivered its final products in 2012. Three of these are
In the frames of the EOPOWER Project new platform for webinars has been created. It enables institutions from different regions to exchange knowledge and experience in fast and low cost way. First test webinars
The paper presents the results of the study of usefulness of selected textural features for describing the content of image chips (1024 by 1024 pixels) cut from WorldView-2 panchromatic images. Several texture analysis techniques
In our work we analyse fractal and multifractal characteristics for description and extraction of information from very high spatial resolution satellite images. In particular, we propose the degree of multifractality as a parameter for