Combination of OpenLandUse Database and Sentinel Data for Agriculture Purposes

Abstract

Creating an Earth’s twin in sufficient detail and complex relations is a challenge for the future arising from strategies like DestinE or Green Deal. Enormous amount of geospatial data available these days leads to a necessity of a suitable data structure to provide understandable information to a general user. An OpenLandUse (OLU) database can serve as such a structure for integrating datasets of different themes, different spatial resolution, and different temporal validity. This paper shows an example of incorporating Earth observation data into the Open Land Use data model, to provide enhanced information about field blocks of a farm in Vyškov region in CZE with information about crop types planted in fields. The data for enhancing the OLU database were based on Sentinel-1 and Sentinel-2 images from 2020, analysed into the form of supervised classification of crop types and various indexes, especially Enhanced Vegetation Index (EVI) and Radar Vegetation Index for Sentinel-1 SAR data (RVI4S1).