Temporal resolution of vegetation indices and solar-induced chlorophyll fluorescence data affects the accuracy of vegetation phenology estimation: A study using in-situ measurements

Zhao, Dayang; Hou, Yuqing; Zhang, Zhaoying; Zhang, Xiaokang; Wu, Lin‐Sheng; Zhu, Xiaolin; Zhang, Yongguang

doi:10.1016/j.ecolind.2022.108673

Cited by 14 publications

(7 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is worth noting that some errors might be introduced into data during the period of observing and processing data. During the observing period, some errors might be caused by environment condition, such as poor weather, unstable illumination, large solar zenith angle, which will influence the quality of observed data [63], [64]. As some research reported, variations of SIFyield (SIF/PAR/fPAR) were entirely overshadowed by the noise present in the spectral measurements and the retrieved values at canopy scale [65].…”

Section: Influence Of Random Error On Relative Importance Resultsmentioning

confidence: 99%

Roles of Physiological and Nonphysiological Information in Sun-Induced Chlorophyll Fluorescence Variations for Detecting Cotton Verticillium Wilt

Zhou,

Huang,

Gui

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

Sun-induced chlorophyll fluorescence (SIF) has been a promising indicator of plants' physiological status, but its response to physiological changes under Verticillium Wilt (VW) stress of cotton plants is complicated by concurrent nonphysiological changes. The relative contributions of the above two components to SIF variations are unclear at different VW stress severities, hindering the accurate diagnose of VW levels. Therefore, the objective of this study is to investigate the dynamic responses of SIF, physiological and non-physiological factors, and to evaluate the contributions of the two factors to SIF variations under different VW stress degrees of cotton. We continuously observed the diurnal variation of top-of-canopy reflectance and SIF on healthy and VW-infected cotton during the peak incidence period of VW disease. To accurately quantify the relative contribution of each component to SIF, we proposed a practical strategy to estimate unmeasurable parameter when using Lindeman, Merenda, and Gold (LMG) method. The results demonstrated the dominated role of physiological factors in SIF with an arch diurnal change pattern at early stages of VW development. As the VW severity increased, the contribution of physiological components declined, with the maximum contribution decreasing by 47.7%, and the diurnal pattern was disrupted, with the diurnal variation amplitude of the parameter Manuscript

show abstract

Section: Influence Of Random Error On Relative Importance Resultsmentioning

confidence: 99%

Roles of Physiological and Nonphysiological Information in Sun-Induced Chlorophyll Fluorescence Variations for Detecting Cotton Verticillium Wilt

Zhou,

Huang,

Gui

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Opportunities are emerging with new spatial data and technologies to monitor spatiotemporal patterns of phenology and environmental factors within and across cities. Phenology indicators based on suninduced chlorophyll fluorescence are better proxies of photosynthetic activities compared to traditional greenness phenology data [62,63], while urban phenology indicators derived from high spatial resolution satellite observations such as Landsat can better capture heterogeneous information in complex urban environments [64]. The recently developed Black Marble night-time lights product [65] and gridded air temperature dataset [66] provide novel data to study the impact of artificial light and temperature on phenology.…”

Section: Discussionmentioning

confidence: 99%

Study on the Spatial and Temporal Distribution of Urban Vegetation Phenology by Local Climate Zone and Urban–Rural Gradient Approach

Liu

Zhang

et al. 2023

Remote Sensing

View full text Add to dashboard Cite

Understanding variations in the temporal and spatial distribution of vegetation phenology is essential for adapting to and mitigating future climate change and urbanization. However, there have been limited vegetation phenology studies within small-scale areas such as urban environments over the past decades. Therefore, the present study focuses on Jinan city, Shandong Province, China as the study area and employs a more refined local climate zone (LCZ) approach to investigate spatial and temporal variations in vegetation phenology. The three phenological indicators used in this study from 2007 to 2018, namely, the start of growing season (SOS), the end of growing season (EOS), and the length of growing season (LOS), were provided by MODIS satellite data. The SOS, EOS, and LOS were superimposed on the LCZ and urban–rural gradient to analyze the changes in vegetation phenology, and the applicability of these two analysis methods in the study of urban vegetation phenology was compared by the honest significant difference test. We found that the SOS, EOS, and LOS of vegetation in the study area generally showed an advance, delay, and extension trend, respectively. The means of the SOS and EOS along different LCZ types varied noticeably more than those along urban–rural gradients. In 2016, 77.5%, 80.0%, and 75.8% of LCZ pairs indicated statistically significant differences for SOS, EOS, and LOS, respectively. This study provides a new perspective for the study of urban vegetation phenology which can help in management of urban-scale environments, identification of areas rich in biodiversity, and conservation and restoration of biodiversity in urban areas.

show abstract

“…This study analyzed the correlation between seasonal GPP and phenological factors, but the separate contributions of the changes of phenology factors and GPP max to seasonal and annual GPP were not quantified. In recent years, global scale solar-induced chlorophyll fluorescence (SIF) provides a better surrogate for studies of large-scale vegetation phenology and GPP [81,82]. The study of phenology monitoring by SIF remote sensing may lead to further discoveries on the influence of phenology on vegetation photosynthesis and carbon sequestration in the source region of the Yellow River.…”

Section: Uncertaintymentioning

confidence: 99%

Earlier Spring-Summer Phenology and Higher Photosynthetic Peak Altered the Seasonal Patterns of Vegetation Productivity in Alpine Ecosystems

Yang,

Liu,

Chen

et al. 2024

Remote Sensing

View full text Add to dashboard Cite

Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPPmax) affected seasonal GPP over the region. Our results showed that the SRYR experienced significantly advanced trends (p < 0.05) for both start (SOS) and peak (POS) of the growing season from 2001 to 2019. Spring GPP (GPPspr) had a significantly increasing trend (p < 0.01), and the earlier SOS had obvious positive effects on GPPspr. Summer GPP (GPPsum) was significantly and negatively correlated to POS (p < 0.05). In addition, GPPmax had a significant and positive correlation with GPPsum and GPPann (p < 0.01), respectively. It was found that an earlier spring-summer phenology and higher photosynthetic peak enhanced the photosynthetic efficiency of vegetation in spring and summer and altered the seasonal patterns of vegetation productivity in the SRYR under warming and wetting climates. This study indicated that not only spring and autumn phenology but also summer phenology and maximum carbon uptake capacity should be regarded as crucial indicators regulating the carbon uptake process in alpine ecosystems. This research provides important information about how changes in phenology affect vegetation productivity in alpine ecosystems under global climate warming.

show abstract

Temporal resolution of vegetation indices and solar-induced chlorophyll fluorescence data affects the accuracy of vegetation phenology estimation: A study using in-situ measurements

Cited by 14 publications

References 51 publications

Roles of Physiological and Nonphysiological Information in Sun-Induced Chlorophyll Fluorescence Variations for Detecting Cotton Verticillium Wilt

Roles of Physiological and Nonphysiological Information in Sun-Induced Chlorophyll Fluorescence Variations for Detecting Cotton Verticillium Wilt

Study on the Spatial and Temporal Distribution of Urban Vegetation Phenology by Local Climate Zone and Urban–Rural Gradient Approach

Earlier Spring-Summer Phenology and Higher Photosynthetic Peak Altered the Seasonal Patterns of Vegetation Productivity in Alpine Ecosystems

Contact Info

Product

Resources

About