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• 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:

  385

  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. 

• Sentinel-2 satellite-based analysis of bark beetle damage in Sopron Mountains, Hungary

  33-40

  Tamás Molnár

  Géza Király

  Views:

  61

  Sopron mountains were affected by bark beetle (Ips typographus) damage between 2017 and 2020, which was surveyed on high-resolution ESA Sentinel-2 satellite images for the period 2017 and 2020 using Mosaic Hub, Anaconda, and Jupyter Notebook web-based computing environments. Biotic forest damage was detected based on vegetation (NDVI) and moisture (MSI, NDWI) indices derived from satellite images. The spatial and temporal change of damage was observed in the image series, resulting in information about the level of degradation and regeneration. In pursuance of GIS processing, 84 forest compartments were compared, which showed in most of the cases (97%) negative interannual change in the index mean values (MSI = - 0.14, NDWI = - 0.2, NDVI= - 0.19) when years compared to each other. The remote sensing-based survey was marked out and validated based on the forest database of the Hungarian Division of Forest of National Land Centre and forest protection damage reports of the Hungarian National Forest Damage Registration System.

• Assessment of spatio-temporal waterline changes of a reservoir: A case study of Ujjani wetland, Maharashtra, India

  1-13

  Pooja Ramanuj

  Shankar Laware

  Nitin Karmalkar

  Views:

  132

  The Ujjani reservoir is an artificial inland wetland and a potential Ramsar site in Maharashtra, India. The present study investigates the changes in the surface water area over time using remote sensing imageries (LANDSAT, LISS-III, Sentinel 2 series) for four decades (1981 to 2021) and the normalized difference water index (NDWI). The study reveals that the overall mean amount and rate of decrease in the surface water area are estimated at 20.50% (44.31 + 30.38 km²) and 0.75% year-1 (1.62 + 1.36 km²year-1), respectively. Furthermore, multiple correlation matrix analysis shows a strong positive correlation between surface water area and rainfall while a weak negative correlation with mean annual temperature (T_MAX). Thus, indicating rainfall as the principal factor in inducing changes to the surface water area of the Ujjani wetland. However, the study also finds that the impact of the dramatic rise in population growth and anthropogenic activities in the form of overexploitation and land encroachments for agriculture are gradual but significant cursors to wetland degradation. Hence, the study recommends periodic monitoring, management, and conservation of wetlands, by employing stringent policies and effective technological measures.