scholarly journals Assessment of Regional Vegetation Response to Climate Anomalies: A Case Study for Australia Using GIMMS NDVI Time Series between 1982 and 2006

2017 ◽  
Vol 9 (1) ◽  
pp. 34 ◽  
Author(s):  
Wanda De Keersmaecker ◽  
Stef Lhermitte ◽  
Michael Hill ◽  
Laurent Tits ◽  
Pol Coppin ◽  
...  
Keyword(s):  
Time Series ◽  
Vegetation Response ◽  
Climate Anomalies ◽  
Ndvi Time Series ◽  
Gimms Ndvi

A rapid assessment method for forest disaster based on MODIS/NDVI time series: a case study from Guizhou Province

2012 ◽  
Vol 32 (11) ◽  
pp. 3359-3367 ◽  
Author(s):  
侍昊 SHI Hao ◽  
王笑 WANG Xiao ◽  
薛建辉 XUE Jianhui ◽  
李杨 LI Yang ◽  
徐雁南 XU Yannan ◽  
...  
Keyword(s):  
Time Series ◽  
Rapid Assessment ◽  
Assessment Method ◽  
Guizhou Province ◽  
Modis Ndvi ◽  
Rapid Assessment Method ◽  
Ndvi Time Series

scholarly journals Influence of Varying Solar Zenith Angles on Land Surface Phenology Derived from Vegetation Indices: A Case Study in the Harvard Forest

2021 ◽  
Vol 13 (20) ◽  
pp. 4126
Author(s):  
Yang Li ◽  
Ziti Jiao ◽  
Kaiguang Zhao ◽  
Yadong Dong ◽  
Yuyu Zhou ◽  
...  
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Mean Difference ◽  
Land Surface Phenology ◽  
Harvard Forest ◽  
Ndvi Time Series ◽  
Bidirectional Reflectance Distribution

Vegetation indices are widely used to derive land surface phenology (LSP). However, due to inconsistent illumination geometries, reflectance varies with solar zenith angles (SZA), which in turn affects the vegetation indices, and thus the derived LSP. To examine the SZA effect on LSP, the MODIS bidirectional reflectance distribution function (BRDF) product and a BRDF model were employed to derive LSPs under several constant SZAs (i.e., 0°, 15°, 30°, 45°, and 60°) in the Harvard Forest, Massachusetts, USA. The LSPs derived under varying SZAs from the MODIS nadir BRDF-adjusted reflectance (NBAR) and MODIS vegetation index products were used as baselines. The results show that with increasing SZA, NDVI increases but EVI decreases. The magnitude of SZA-induced NDVI/EVI changes suggests that EVI is more sensitive to varying SZAs than NDVI. NDVI and EVI are comparable in deriving the start of season (SOS), but EVI is more accurate when deriving the end of season (EOS). Specifically, NDVI/EVI-derived SOSs are relatively close to those derived from ground measurements, with an absolute mean difference of 8.01 days for NDVI-derived SOSs and 9.07 days for EVI-derived SOSs over ten years. However, a considerable lag exists for EOSs derived from vegetation indices, especially from the NDVI time series, with an absolute mean difference of 14.67 days relative to that derived from ground measurements. The SOSs derived from NDVI time series are generally earlier, while those from EVI time series are delayed. In contrast, the EOSs derived from NDVI time series are delayed; those derived from the simulated EVI time series under a fixed illumination geometry are also delayed, but those derived from the products with varying illumination geometries (i.e., MODIS NBAR product and MODIS vegetation index product) are advanced. LSPs derived from varying illumination geometries could lead to a difference spanning from a few days to a month in this case study, which highlights the importance of normalizing the illumination geometry when deriving LSP from NDVI/EVI time series.

Agriculture Phenology Monitoring Using NDVI Time Series Based on Remote Sensing Satellites: A Case Study of Guangdong, China

2019 ◽  
Vol 28 (3) ◽  
pp. 204-214 ◽  
Author(s):  
Komal Choudhary ◽  
Wenzhong Shi ◽  
Mukesh Singh Boori ◽  
Samuel Corgne
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Ndvi Time Series
Sign in / Sign up

Export Citation Format

Share Document