TY - JOUR
T1 - Impacts of Satellite Revisit Frequency on Spring Phenology Monitoring of Deciduous Broad-Leaved Forests Based on Vegetation Index Time Series
AU - Tian, Jiaqi
AU - Zhu, Xiaolin
AU - Wan, Luoma
AU - Collin, Melissa
N1 - Funding Information:
This work was supported in part by the National Science Foundation of China under Grant 42022060, in part by The Hong Kong Polytechnic University, under Grant ZVN6, and in part by the Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, under Grant BBWD.
Publisher Copyright:
© 2008-2012 IEEE.
PY - 2021/10
Y1 - 2021/10
N2 - Satellites have different revisit frequencies (i.e., temporal resolutions), ranging from daily to monthly. The satellite revisit frequencies suitable for accurately monitoring the phenology of deciduous broad-leaved forests (DBF) are not well-known. To fill this knowledge gap, this study used MODIS Daily Nadir BRDF-Adjusted images to simulate EVI time series with a wide range of temporal resolutions from daily to 52 days, to investigate the impacts of satellite revisit frequency on monitoring spatial and temporal patterns of spring phenology, i.e., the start of season (SOS), of DBF in North America. Then, these EVI time series were used to extract SOS by two common phenology extraction methods (i.e., relative threshold and curvature methods). Our results reveal that 1) low temporal resolutions cannot accurately reconstruct real vegetation growth profile, which generally causes a false early SOS detection, 2) the impact of temporal resolutions is nonlinear. The accuracy of SOS detection from data with relatively high frequencies (e.g., 7 days) is only slightly lower than that from daily time series but the accuracy decreases largely with low frequencies, and 3) validation with ground observations from PhenoCam Network stations and an experiment using three real satellite datasets (i.e., MODIS, Landsat 8, and Sentinel-2) confirm the findings from our simulation study. This study suggests that satellites with medium temporal resolutions, such as Sentinel-2 and Landsat 8, could extract reliable phenology metrics in non-cloudy regions.
AB - Satellites have different revisit frequencies (i.e., temporal resolutions), ranging from daily to monthly. The satellite revisit frequencies suitable for accurately monitoring the phenology of deciduous broad-leaved forests (DBF) are not well-known. To fill this knowledge gap, this study used MODIS Daily Nadir BRDF-Adjusted images to simulate EVI time series with a wide range of temporal resolutions from daily to 52 days, to investigate the impacts of satellite revisit frequency on monitoring spatial and temporal patterns of spring phenology, i.e., the start of season (SOS), of DBF in North America. Then, these EVI time series were used to extract SOS by two common phenology extraction methods (i.e., relative threshold and curvature methods). Our results reveal that 1) low temporal resolutions cannot accurately reconstruct real vegetation growth profile, which generally causes a false early SOS detection, 2) the impact of temporal resolutions is nonlinear. The accuracy of SOS detection from data with relatively high frequencies (e.g., 7 days) is only slightly lower than that from daily time series but the accuracy decreases largely with low frequencies, and 3) validation with ground observations from PhenoCam Network stations and an experiment using three real satellite datasets (i.e., MODIS, Landsat 8, and Sentinel-2) confirm the findings from our simulation study. This study suggests that satellites with medium temporal resolutions, such as Sentinel-2 and Landsat 8, could extract reliable phenology metrics in non-cloudy regions.
KW - EVI time series
KW - satellite revisit frequency
KW - start of season (SOS)
KW - temporal resolution
UR - http://www.scopus.com/inward/record.url?scp=85117767380&partnerID=8YFLogxK
U2 - 10.1109/JSTARS.2021.3120013
DO - 10.1109/JSTARS.2021.3120013
M3 - Journal article
AN - SCOPUS:85117767380
SN - 1939-1404
VL - 14
SP - 10500
EP - 10508
JO - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
JF - IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
ER -