Phenology analysis for detection of vegetation changes based on Landsat 8 images in Nature Park Kopački rit, Croatia

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...

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Bibliographic Details
Main Authors: Radočaj Dorijan, Plaščak Ivan, Jurišić Mladen, Majić Ivana, Ozimec Siniša, Sarajlić Ankica, Rožac Vlatko
Format: Article
Language:English
Published: University of Novi Sad, Department of Geography, Tourism and Hotel Management 2024-01-01
Series:Geographica Pannonica
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Online Access:https://scindeks-clanci.ceon.rs/data/pdf/0354-8724/2024/0354-87242404238R.pdf
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Summary: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.
ISSN:0354-8724
1820-7138