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Accuracy assessment of different soil databases concerning WRB reference soil groups
1-12Views:193As a result of international cooperation, the conditions of data access and data usage have been significantly improved during the last two decades. Also, the establishment of web-based geoinformatic infrastructure allowed researchers to share their results with the scientific community more efficiently on the international level. The aim of this study is to investigate the accuracy of databases with different spatial resolutions, using the reference profiles of LUCAS topsoil database. In our study, we investigated the accuracy of World Reference Base for Soil Resources (WRB) Reference Soil Groups (RSG) groups stored in freely accessible soil databases (European Soil Database (ESDB), International Soil Reference and Information Centre (ISRIC)) in Hungary. The study concluded that the continental scale database tends to be more accurate. We used the Kappa Index of Agreement (KIA) statistical index to evaluate accuracy. The European and the international databases showed a value of 0.9643 and 0.3968, respectively. Considering the results, we can conclude that the spatial resolution has a relevant impact on the accuracy of databases, however, the study should be extended to the national level and the indices should be assessed together.
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Land cover analysis based on descriptive statistics of Sentinel-2 time series data
1-9Views:337In our paper we examined the opportunities of a classification based on descriptive statistics of NDVI throughout a year’s time series dataset. We used NDVI layers derived from cloud-free Sentinel-2 images in 2018. The NDVI layers were processed by object-based image analysis and classified into 5 classes, in accordance with Corine Land Cover (CLC) nomenclature. The result of classification had a 76.2% overall accuracy. We described the reasons for the disagreement in case of the most remarkable errors.