Behavior of multitemporal and multisensor passive microwave indices in Southern Hemisphere ecosystems

Abstract

This study focused on the time series analysis of passive microwave and optical satellite data collected from six Southern Hemisphere ecosystems in Australia and Argentina. The selected ecosystems represent a wide range of land cover types, including deciduous open forest, temperate forest, tropical and semiarid savannas, and grasslands. We used two microwave indices, the frequency index (FI) and polarization index (PI), to assess the relative contributions of soil and vegetation properties (moisture and structure) to the observations. Optical-based satellite vegetation products from the Moderate Resolution Imaging Spectroradiometer were also included to aid in the analysis. We studied the X and Ka bands of the Advanced Microwave Scanning Radiometer-EOS and Wind Satellite, resulting in up to four observations per day (1:30, 6:00, 13:30, and 18:00 h). Both the seasonal and hourly variations of each of the indices were examined. Environmental drivers (precipitation and temperature) and eddy covariance measurements (gross ecosystem productivity and latent energy) were also analyzed. It was found that in moderately dense forests, FI was dependent on canopy properties (leaf area index and vegetation moisture). In tropical woody savannas, a significant regression (R 2 ) was found between FI and PI with precipitation (R 2 > 0.5) and soil moisture (R 2 > 0.6). In the areas of semiarid savanna and grassland ecosystems, FI variations found to be significantly related to soil moisture (R 2 > 0.7) and evapotranspiration (R 2 > 0.5), while PI varied with vegetation phenology. Significant differences (p < 0.01) were found among FI values calculated at the four local times.

TERN, Australia’s land observatory: addressing the global challenge of forecasting ecosystem responses to climate variability and change

“…Integration across TERN's three scales of observation began in the research community (Ma et al 2013, Barraza et al 2014, Bradford et al 2014, Joiner et al 2014, Mitchell et al 2014, Barraza et al 2015, Broich et al 2015. Examples of multiscale integration across TERN RI include: through remote-sensing calibration/validation activities (e.g.…”

An introduction to the Australian and New Zealand flux tower network – OzFlux

“…To address global concern over rising atmospheric CO 2 concentrations and global climate change, there has been a growing need for studies of terrestrial ecosystems (Peters and Loescher, 2014). Studies using the eddy covariance technique from micrometeorological flux towers (Baldocchi, 2003) can contribute significantly to our understanding of ecological, biogeochemical, and hydrological processes by, amongst others, 1. providing accurate, continuous half-hourly to annual estimates of sinks and sources of greenhouse gases and water from ecosystems for carbon accounting and water management that is particularly important in such an arid country as Australia (Hutley et al, 2005;Raupach et al, 2013);…”

“…MODIS GPP and ET; Kanniah et al, 2009b;Restrepo-Coupe et al, 2016) and to assist in the parameterization of models that rely on remotely sensed data (e.g. GPP, ET, canopy conductance, and light-use efficiency (LUE)) ( Barraza et al, 2014Barraza et al, , 2015Glenn et al, 2011;Goerner et al, 2011). Given the challenge of managing water in the dry Australian continent, remote sensing of actual ET is a crucial task, and Glenn et al (2011) provide an overview of the Australian experience in this task.…”

“…The OzFlux network has been highly successful in generating standardized measurements and protocols, as well as in providing advanced QA/QC data compatible with international databases (FLUXNET) (Papale et al, 2006) under an open-access data policy. OzFlux has contributed to the FLUXNET community efforts to improve data processing algorithms to minimize potential errors associated with nighttime bias, gap filling, and a lack of energy balance closure (Baldocchi, 2003;. This has enabled a significant uptake of the eddy covariance data for application to a range of research questions as exemplified above.…”

Technical note: Dynamic INtegrated Gap-filling and partitioning for OzFlux (DINGO)

“…GPP and ET, Kanniah et al, 2009;Restrepo-Coupe et al, 2016) and to aid the parameterisation of models that rely on remotely sensed data (e.g. GPP, ET, canopy conductance, and light use efficiency (LUE), Barraza et al, 2014Barraza et al, , 2015Glenn et al, 2011;Goerner et al, 2011). In addition, OzFlux data have been instrumental in constraining a continent-wide assessment of terrestrial carbon and water cycles (Haverd et al, 2013) and featured in the development of new models (Haverd et al, 2007(Haverd et al, , 2009.…”