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• Preliminary analysis of red mud spill based on aerial imagery, Hungary

  47-57

  Péter Burai

  Amer Smailbegovic

  Csaba Lénárt

  József Berke

  Gábor Milics

  Tamás Tomor

  Tibor Bíró

  Views:

  128

  One of the largest industrial spills in Europe occurred in the village of Kolontár (Hungary) on October 4, 2010. The primary objective of the hyperspectral remote sensing mission was to monitor that is necessary in order to estimate the environmental damage, the precise size of the polluted area, the rating of substance concentration in the mud, and the overall condition of the flooded district as soon as possible. The secondary objective was to provide geodetic data necessary for the high-resolution visual information from the data of an additional Lidar survey, and for the coherent modeling of the event. For quick assessment and remediation purposes, it was deemed important to estimate the thickness of the red mud, particularly the areas where it was deposited in a thick layer. The results showed that some of the existing tools can be easily modified and implemented to get the most out of the available advanced remote sensing data.

• Land cover analysis based on descriptive statistics of Sentinel-2 time series data

  1-9

  Orsolya Varga

  Ildikó Gombosné Nagy

  Péter Burai

  Tamás Tomor

  Csaba Lénárt

  Szilárd Szabó

  Views:

  337

  In 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.