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Sensors and Materials, Volume 33, Number 10 (2021)
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Published in advance: July 15, 2021
Published: July 15, 2021

Tracking Long-term Phenological Shift in Response to Climatic Parameters in Chitwan National Park, Nepal [PDF]

Aman KC, Tri Dev Acharya, Nimisha Wagle, and Dong Ha Lee

(Received May 31, 2021; Accepted July 7, 2021)

Keywords: MODIS, phenology, shift, climate, precipitation, temperature, Chitwan National Park, Nepal

To understand the terrestrial ecosystem and track whether it is influenced by any external factors, an accurate assessment of vegetation phenology at the regional to global scale is needed. Because it has become crucial to monitor changes in green cover due to the impacts of climate change, phenology research is a crucial part of documenting life cycle patterns and the effects of climate change on ecosystems. However, ground observations can be a tedious, if not impossible, way of studying such broad-scale trends. Vegetation indices derived from satellite images provide the efficacy to study such trends over a large area and time span. Cloud computing platforms such as Google Earth Engine (GEE) facilitate the storage, manipulation, and accessibility of such large datasets. The satellite-remote-sensing-based normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to study the phenological shift in Chitwan National Park of Nepal, which is home to unique biological resources, in response to two major climatic drivers: temperature and precipitation. The four transition stages of greenness onset, maturity onset, senescence onset, and growing period were determined by fitting spatially averaged NDVI values using the phenofit package of R. It was found that the greenness and maturity onsets have been delayed over the years while the growing period has seen fluctuations due to variations in senescence onset. Precipitation was correlated positively with NDVI while temperature was negatively correlated with NDVI. Moreover, the rainfall one month earlier better explained the NDVI variability than the amount of rainfall in the same month because of the stronger correlation. Overall, this study indicates that climate variability is affecting the phenology of vegetation, and the results can help in performing suitable checks and assessments of the ecosystem in Nepal.

Corresponding author: Tri Dev Acharya, Dong Ha Lee

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