Analysis of Temporal Changes in the Floating Vegetation and Algae Surface of the Water Bodies of Kis-Balaton Based on Aerial Image Classification and Meteorological Data
Climate change and related weather extremes are increasingly having an impact on all aspects of life. The main objective of the research was to analyze the impact of the most important meteorological elements and the image data of various water bodies of the Kis-Balaton wetland, Hungary. The primary question was which meteorological elements have a positive or negative influence on vegetational surface cover. Drones have facilitated the visual surveying and monitoring of challenging-to-reach water bodies in the area, including a lake and multiple channels. The individual channels had different flow conditions. Aerial surveys were conducted monthly, based on pre-prepared flight plans. Images captured by a Mavic 3 drone flying at an altitude of 150 m and equipped with a multispectral sensor were processed. The time-series images were aligned and assembled into orthophotos. The image details relevant to the research were segregated and classified using Maximum Likelihood classification algorithm. The reliability of the image data used was checked by Shannon entropy and spectral fractal dimension measurements. The results of the classification were compared with the meteorological data collected by a QLC-50 automatic climate station of Keszthely. The investigations revealed that the surface cover of the examined water bodies was different in the two years but showed a kind of periodicity during the year. In those periods, where photosynthetic organisms multiplied in a higher proportion in the water body, higher monthly average air temperatures and higher monthly global solar radiation sums were observed.
Authors
- Ariel Tóth (ORCID: https://orcid.org/0000-0002-0355-9569)
- Veronika Kozma-Bognár
- József Berke (ORCID: https://orcid.org/0000-0002-0190-4197)
- Angéla Anda
- Kristóf Kozma-Bognár
Institutions
- University of Pannonia (HU)
- Dennis Gabor University (HU)
Publication Details
- Journal
- Geomatics
- Published
- 2026-01-03
- DOI
- https://doi.org/10.3390/geomatics6010003
- Citations
- 1
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 31.91
Funders
- Nemzeti Kutatási, Fejlesztési és Innovaciós Alap