Revisit the performance of MODIS and VIIRS leaf area index products from the perspective of time-series stability
Zou, Dongxiao; Yan, Kai; Pu, Jiabin; Gao, Si; Li, Wenjuan; Mu, Xihan; Knyazikhin, Yuri; Myneni, Ranga B.
As an essential vegetation structural parameter, leaf
area index (LAI) is involved in many critical biochemical processes,
such as photosynthesis, respiration, and precipitation interception.
The MODerate resolution Imaging Spectroradiometer (MODIS)
and Visible Infrared Imager Radiometer Suite (VIIRS) LAI sequence
products have long supported various global climate, biogeochemistry,
and energy flux research. These applications all rely
on the accuracy of the product’s long time series. However, uncontrolled
interferences (e.g., adverse observation conditions and sensor
uncertainties) potentially introduce substantial uncertainties
to time series in product applications. As one of the most sensitive
areas in response to global climate change, the Tibet Plateau (TP)
has been treated as a crucial testing ground for thousands of studies
on vegetation. To ensure the credibility of the studies arising from
MODIS/VIIRSLAI products, the temporal quality uncertainties of
data need to be clarified. This article proposed a method to revisit
the temporal stability of the MODIS (MOD and MYD) and VIIRS
(VNP) LAI in the TP, expecting to provide useful information for
better accounting for the uncertainties in this area. Results show
that the MODIS and VIIRS LAI were relatively stable in time
series and available to be used continuously, among which the
temporal quality of the MODIS LAI was the most stable. Moreover,
the MODIS and VIIRS LAI products performed similarly in both
time-series stability and time-series anomaly distribution, magnitudes
and fluctuations. The time-series stability evaluation strategy
applied to the MODIS and VIIRS LAI can also be employed to other
remote sensing products.
↧