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20 December 2024 Analyzing recurrence patterns using normalized difference vegetation index (NDVI) of man-made forests in Balaoan, La Union
John Carlo Elmaguin, Jejomar Bulan, Jumar Cadondon, Mark Lester Cabaluna, Floro Junior Roque, Jazzie Jao, Edgar Vallar
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Proceedings Volume 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII; 1326605 (2024) https://doi.org/10.1117/12.3040419
Event: Asia-Pacific Remote Sensing, 2024, Kaohsiung, Taiwan
Abstract
Normalized Difference Vegetation Index (NDVI) is one of the common vegetation indices used to assess forest health. This includes the use of several wavelengths in the electromagnetic spectrum. Time Series analysis was the common process used in studying the temporal behavior of this remote sensing data. This process provides straightforward information about how NDVI changes over time and only provides minimal information. In this study, Recurrence Quantification Analysis (RQA) provides another approach to studying NDVI. Recurrence quantification analysis quantifies the number of recurrences of a state or data point in the time series using a Recurrence plot as a graphical representation. Based on the patterns of the recurrence plots, the NDVI on sites one to five are all deterministic periodic. The datasets manifest long diagonal lines, a distinctive feature of a periodic behavior. This recurrence quantification analysis method can assess other biogeophysical parameters that exhibit periodic behavior that depends on different weather parameters.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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John Carlo Elmaguin, Jejomar Bulan, Jumar Cadondon, Mark Lester Cabaluna, Floro Junior Roque, Jazzie Jao, and Edgar Vallar "Analyzing recurrence patterns using normalized difference vegetation index (NDVI) of man-made forests in Balaoan, La Union", Proc. SPIE 13266, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VIII, 1326605 (20 December 2024); https://doi.org/10.1117/12.3040419
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KEYWORDS
Vegetation
Ecosystems
Lanthanum
Biodiversity
Biological research
Data processing
Electromagnetism
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