Advancing new and emerging techniques to facilitate routine quality assessment of satellite-derived vegetation products

Abstract

Accurate and timely information on vegetation status, in the form of biophysical and biochemical variables, is key to the effective management of vegetated environments. Using optical instruments capable of resolving the spectral characteristics of vegetation, satellite-derived vegetation products now provide users routine estimates of these variables at the regional and global scale. However, to ensure their fitness-for-purpose, quality assessment is required.
Unfortunately, progress in the validation of these products has been restricted by temporally limited reference data, with periodic field campaigns providing few in situ reference measurements throughout the growing season or over multiple years. Information on how product performance varies over time is, therefore, scarce (resulting in uncertainty in models of crop yield, carbon exchange, and the weather and climate systems, for which vegetation seasonality is an important driver). In recent years, several techniques have emerged with the
potential to provide temporally continuous in situ reference data, automating the data collection process and overcoming the logistical issues associated with periodic field campaigns. This thesis focuses on addressing challenges associated with these techniques, including those related to data processing methods, measurement assumptions, spatial representativeness, and upscaling
approaches (which are a necessity for validating moderate spatial resolution products). Of various emerging techniques, above-canopy digital repeat photography was identified as being of particular interest due to its maturity and degree of spatial integration. However, a critical appraisal of the approach revealed that due to non-linear and seasonal effects, the resulting timeseries
of colour indices were prone to asymptotic saturation and could not be easily linked to any one biophysical property. To overcome these limitations, a new technique based on automated below-canopy digital hemispherical photography was proposed and evaluated. Benchmarking against manually collected data provided confidence that the approach could deliver leaf area index measurements of comparable quality to traditional in situ measurement techniques (but with substantially improved temporal characterisation). Upscaling methods were then investigated, as existing approaches are not well-suited to dense temporal characterisation of a limited number of locations. It was concluded that radiative transfer model-based approaches, which incorporate physical knowledge and enable seasonal variations in sun-sensor geometry to be accounted for, were more robust than vegetation index-based multitemporal transfer functions. Overall, the thesis provides a framework for routine quality assessment of satellitederived vegetation products, from a cost-effective automated in situ measurement technique, through to an upscaling approach capable of deriving time-series of high spatial resolution reference maps suitable for product validation. By facilitating a temporally explicit quantification of product performance in future work, the framework will enable targeted product improvements to be made, ultimately reducing uncertainties in downstream applications.

More information

Identifiers

ORCID for Luke Brown: orcid.org/0000-0003-4807-9056

ORCID for Jadunandan Dash: orcid.org/0000-0002-5444-2109

ORCID for Booker Ogutu: orcid.org/0000-0002-1804-6205

Catalogue record

Export record