Global relationships between satellite-derived solar-induced fluorescence (SIF), traditional reflectance vegetation indices (NDVI and NDII), evapotranspiration (ET), and soil moisture anomalies

Authors: JOINER, J. - Goddard Space Flight Center; YOSHIDA, Y. - Science Systems And Applications, Inc; Anderson, Martha; HOLMES, T. - Goddard Space Flight Center; HAIN, C. - Goddard Space Flight Center; RIECHLE, R. - Goddard Space Flight Center; KOSTER, R. - Goddard Space Flight Center; MIDDLETON, E.M - Goddard Space Flight Center; ZENG, FAN-WEI - Science Systems And Applications, Inc

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/14/2018
Publication Date: 12/15/2018
Citation: Joiner, J., Yoshida, Y., Anderson, M.C., Holmes, T., Hain, C., Riechle, R., Koster, R., Middleton, E., Zeng, F. 2018. Global relationships between satellite-derived solar-induced fluorescence (SIF), traditional reflectance vegetation indices (NDVI and NDII), evapotranspiration (ET), and soil moisture anomalies. Remote Sensing of Environment. 219:339-352. https://doi.org/10.1016/j.rse.2018.10.020.
DOI: https://doi.org/10.1016/j.rse.2018.10.020

Interpretive Summary: Building capacity for realtime monitoring of agricultural yield and yield limiting factors is the key for strengthening global food security and facilitating timely famine response. This paper explores the response of several global remote sensing-based indicators to changes in soil moisture, as simulated by a land-surface modeling system. The question we explore is which satellite indicators are best correlated with root-zone soil moisture changes, and what the relative response times are. In principle, in response to rainfall or extended drought, we might first see changes in surface moisture content, followed by modified crop water use or evapotranspiration (ET), and ending in a signal reflecting green vegetation cover fraction and photosynthetic capacity. This hypothesis was tested globally using a suite of satellite indices sensitive to these various surface states and conditions. The ET and vegetation indices tested showed good response to modeled soil moisture variations. An index based on solar-induced fluorescence, a by-product of the photosynthetic process, also showed reasonable response time but exhibited higher levels of noise. These results will be useful for integrating new types of satellite remote sensing data into global yield monitoring and famine early warning systems.

Technical Abstract: Monitoring the effects of water availability on vegetation globally using satellites is important for applications such as precision agriculture and food security as well as for more broadly understanding relationships between the water and carbon cycles. In this study we examine how quickly several satellite-based drought indicators respond to anomalies root-zone soil moisture (RZM) simulated within a data assimilation system that extends to about 1m depth. The satellite indicators considered are 1) the normalized difference vegetation and infrared indices (NDVI and NDII, respectively) derived from MODIS reflectances obtained with moderately wide (20-40 nm) spectral bands in the visible and near-infrared (NIR), 2) solar-induced fluorescence (SIF) from NIR hyper-spectral measurements, and 3) evapotranspiration (ET) estimated from thermal infrared observations and normalized by a reference ET. NDVI is primarily sensitive to chlorophyll amounts and thus vegetation structure. SIF is sensitive to structure as well as physiology and owing to the latter may have a faster response to water availability as compared with NDVI or NDII. We find that anomalies of normalized ET, NDVI, and NDII have the highest correlations with RZM and show less noise as compared with SIF. NDVI, NDII, and SIF anomalies have similar lags with respect to RZM. The long term record of satellite SIF data is available only from morning polar-orbiting satellites. This may not be an optimal orbit to detect physiological water stress effects in addition to the structural effects seen also in NDVI and NDII. Normalized ET anomalies show somewhat shorter lags as compared with NDVI, NDII, and SIF anomalies with respect to RZM, particularly in sparsely vegetated regions. In these areas, evaporation from bare soil dominates over transpiration and reductions in ET are more strongly coupled with reductions in near-surface moisture than in the RZM. Consequently, a precipitation deficit (enhancement), with corresponding changes in ET, will dry (moisten) the top few centimeters of soil earlier than the top full meter, and this may explain observed negative time lags of normalized ET anomalies with respect to RZM.