期刊
SENSORS AND MATERIALS
卷 33, 期 11, 页码 3787-3799出版社
MYU, SCIENTIFIC PUBLISHING DIVISION
DOI: 10.18494/SAM.2021.3449
关键词
MODIS; phenology; shift; climate; precipitation; temperature; Chitwan National Park; Nepal
资金
- Kangwon National University
This study explores the impact of climate variability on the phenology of vegetation in Chitwan National Park of Nepal using satellite remote sensing data and ground observations. The onset of greenness and maturity has been delayed over the years, while the growing season has fluctuated due to variations in senescence onset. Precipitation is positively correlated with NDVI, while temperature shows a negative correlation with NDVI, with rainfall one month earlier being a better predictor of NDVI variability.
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.
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