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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorNijland, Wiebe
dc.contributor.authorSchouten, Bo-lan
dc.date.accessioned2023-09-06T09:40:16Z
dc.date.available2023-09-06T09:40:16Z
dc.date.issued2023
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/44948
dc.description.abstractThis master's thesis focuses on the blooming period of trees in the Gargano National Park in Italy. The research question addressed in this study is whether there has been a shift in the period of trees turning green and if this change can be detected using satellite imagery, specifically the Normalized Difference Vegetation Index (NDVI). The aim is to analyze NDVI scores derived from Landsat 5 and 7 satellite imagery in the period from 1985 to 2020. The data preparation involves masking non-forest areas, applying cloud, cloud shadow, and snow masks, and rescaling the surface reflectance bands as well as normalizing them. An exploratory analysis of the data reveals an increasing trend in NDVI values over time. To determine the presence of a statistical trend, the Seasonal Mann-Kendall test is applied. The results indicate significant relationships between NDVI and time, demonstrating the potential for detecting changes in vegetation dynamics. Ethical considerations are addressed, highlighting the accessibility of the data and its freely available nature. Future research directions are suggested, including the incorporation of additional climate variables, the utilization of Landsat 4 and 8 data, and the exploration of leaf senescence dynamics. Overall, this study contributes to the understanding of long-term vegetation changes and their association with climate variations in the Gargano National Park.
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectThe blooming period of trees in the Gargano National Park, Italy
dc.titleThe blooming period of trees in the Gargano National Park, Italy
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsTrees, blooming period, Google Earth engine, satellite imagery
dc.subject.courseuuApplied Data Science
dc.thesis.id23457


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