Phenology Analysis for Detection of Vegetation Changes Based on Landsat 8 Images in Nature Park Kopački rit, Croatia

  • Dorijan Radočaj Faculty of Agrobiotechnical Sciences Osijek, Croatia
  • Ivan Plaščak Faculty of Agrobiotechnical Sciences Osijek, Croatia
  • Mladen Jurišić Faculty of Agrobiotechnical Sciences Osijek, Croatia
  • Ivana Majić Faculty of Agrobiotechnical Sciences Osijek, Croatia
  • Siniša Ozimec Faculty of Agrobiotechnical Sciences Osijek, Croatia
  • Ankica Sarajlić Faculty of Agrobiotechnical Sciences Osijek, Croatia
  • Vlatko Rožac Public Institution Nature Park Kopački Rit, Croatia
Keywords: vegetation activity, “npphen” package, management zones, phenology analysis, normalized difference vegetation index (NDVI), k-means classification

Abstract


This study proposed a method for detecting vegetation changes and establishing geospatial management zones based on the 10-year phenology analysis using normalized difference vegetation index (NDVI) long-term trends from Landsat 8 multispectral imagery in Nature Park Kopački rit. The main components of the proposed method include phenology analysis and NDVI anomaly detection supported by unsupervised k-means classification of vegetation management zones. The reference monthly NDVI values (2013–2019) with three test years (2020–2022) strongly indicated very high heterogeneity in vegetation activity. A 100 m spatial resolution and a monthly temporal resolution were used. The results of unsupervised k-means classification in five vegetation activity classes indicated that three of these classes have considerably high negative NDVI anomalies, covering 64.1% of the study area. While the proposed method ensures the detection of vegetation changes and vegetation activity zones, a comprehensive field observation is required to determine the potential environmental and/or anthropogenic causes. However, the proposed approach significantly reduces the need for extensive fieldwork, allowing biologists to focus their efforts on areas with detected abnormal vegetation activity.

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Published
2024/12/31
Section
Original Research