Lola Suárez

Spatial Resolution Effects on Chlorophyll Fluorescence Retrieval in a Heterogeneous Canopy Using Hyperspectral Imagery and Radiative Transfer Simulation

Increasing attention is being given to chlorophyll fluorescence (F) for global monitoring of vegetation due to its relationship with physiology. New progress has been made in the methodological and technical aspects of signal retrieval with the recently published low-resolution global maps of fluorescence. Nevertheless, little progress has been made in the interpretation of the F signal when quantified in large pixels, an important issue due to the effects of structure, percentage cover, shadows, and background. High-resolution (40 cm) airborne hyperspectral imagery is used in this letter to assess the retrieval of fluorescence by the Fraunhofer line depth method from pure tree crowns and aggregated pixels. Due to canopy heterogeneity, the F signal extracted from aggregated pixels is highly degraded. A poor relationship is obtained between fluorescence extracted from pure tree crowns (Fcrown) and that quantified from pixels aggregating pure tree crowns, shadows, and background (Faggregated) (R2 = 0.25; p <; 0.01). The relationship between F and stomatal conductance (used as a physiological indicator) decreases as a function of aggregation, yielding R2 = 0.69 (p <; 0.01) when calculated from pure tree crowns and R2 = 0.38 (p <; 0.05) from pixels containing crown, shadows, and soil. This letter demonstrates the need for methods to accurately retrieve a pure-vegetation fluorescence signal from aggregated pixels. The FluorMODleaf and FluorSAIL models were combined with the geometric forest light interaction model (FLIM) model and led to the “FluorFLIM” model developed for this letter. Simulations conducted with FluorFLIM obtain predictive relationships between Fcrown and Faggregated pixels as a function of percentage cover, enabling the estimation of pure-crown F from aggregated pixels (R2 = 0.72, p <; 0.01).

Understanding the Effects of ALS Pulse Density for Metric Retrieval across Diverse Forest Types

Pulse density, the number of laser pulses that intercept a surface per unit area, is a key consideration when acquiring an Airborne Laser Scanning (ALS) dataset. This study compares area-based vegetation structure metrics derived from multireturn ALS simulated at six pulse densities (0.05 to 4 pl m-2) across a range of forest types: from savannah woodlands to dense rainforests. Results suggest that accurate measurement of structure metrics (canopy height, canopy cover, and vertical canopy structure) can be achieved with a pulse density of 0.5 pl m-2 across all forest types when compared to a dataset of 10 pl m-2. For pulse densities <0.5 pl m-2, two main sources of error lead to inaccuracies in estimation: the poor identification of the ground surface and sparse vegetation cover leading to under sampling of the canopy profile. This analysis provides useful information for land managers determining capture specifications for large-area ALS acquisitions.

Using discrete-return airborne laser scanning to quantify number of canopy strata across diverse forest types

The vertical arrangement of forest canopies is a key descriptor of canopy structure, a driver of ecosystem function and indicative of forest successional stage. Yet techniques to attribute for canopy vertical structure across large and potentially heterogeneously forested areas remain elusive. This study introduces a new technique to estimate the Number of Strata (NoS) that comprise a canopy profile, using discrete-return Airborne Laser Scanning (ALS) data. Vertically resolved gap probability (P-gap) aggregated over a plot is generalized with a nonparametric cubic spline regression (P-s). Subsequently a count of the positive zero-crossings of second derivative of 1 - P-s is used to estimate NoS. Comparison with inventory derived estimates at 24 plots across three diverse study areas shows a good agreement between the two techniques (RMSE=041 strata). Furthermore, this is achieved without altering model parameters, indicating the transferability of the technique across diverse forest types. NoS values ranged from 0 to 4 at a further 239 plots, emphasizing the need for a method to quantify canopy vertical structure across forested landscapes. Comparison of NoS with other commonly derived ALS descriptors of canopy structure (canopy height, canopy cover and return height coefficient of determination) returned only a moderate correlation (r(2)<04). It is proposed the presented method provides a primary descriptor of canopy structure to complement canopy height and cover, as well as a candidate Ecological Biodiversity Variable for characterizing habitat structure.

Approaches to establishing a metadata standard for field spectroscopy datasets

There is an urgent need within the international remote sensing community to establish a metadata standard for field spectroscopy that ensures high quality, interoperable metadata sets that can be archived and shared efficiently within Earth observation data sharing systems. Careful examination of all stages of metadata collection and analysis can inform a robust standard that is applicable to a range of field campaigns. This paper presents approaches towards a standard that encompasses in situ metadata collection and initiatives towards sharing metadata within intelligent archiving systems.

A collaborative framework for vegetated systems research: A perspective from Victoria, Australia

Collaborative ventures in research infrastructure can allow multiple stakeholders to benefit from outcomes that may otherwise be cost prohibitive. In this study, we discuss how the investment in research infrastructure by various sectors of the academic, scientific, and land management community is promoting high end forest ecosystem research in Australia. Three 25km2 woodland and open canopy forests that are representative of Victorias 8 million hectares of public forests were incorporated into the Terrestrial Ecosystem Research Networks calibration/validation campaign. The sites are being used to develop algorithms that will assist land management agencies across various states to characterize fundamental forest attributes at a landscape level. Wireless technology (VegNet) is also being trialed at these sites to investigate forest condition over time. This study provides an example of how the establishment and co-investment in research infrastructure amongst different sectors of the scientific community promote data sharing and ultimately expand our understanding of forest ecosystems, which can in turn be used for monitoring and to inform policy and land management decision making.

Woody vegetation landscape feature generation from multispectral and LiDAR data (A CRCSI 2.07 woody attribution paper)

There is a need for accurate estimation of Australian woody vegetation parameters. State and Commonwealth land management agencies are mandated to report about forest condition every five years. The CRCSI 2.07 “Australian woody vegetation landscape feature generation from multi-source airborne and space-borne imaging and ranging data” aims at producing ready-to-use methods to report forest condition based on remote sensing data. The first efforts have focus on field data techniques and canopy structure characterization using LiDAR data. Results demonstrate canopy profile can be accurately estimated using Weibull probability density functions at 30×30m pixel size. Moreover different field techniques to measure vegetation fractional cover has been tested and compare finding differences up to 15%.

MAUP and LiDAR derived canopy structure (A CRCSI 2.07 woody attribution paper)

MAUP theory is applied to a LiDAR dataset acquired over a forested scene. The Weibull Probability Density Function (PDF) has been fit to LiDAR derived canopy height profiles for plots covering the complete 1 × 1 km scene. Ten plot sizes are tested from 10 - 300 m. Parameters describing the location and scale of the PDF are used as analogous of canopy height and canopy length respectively. Results suggest that, for a structurally homogenous forested scene, localised variance decreases for canopy height with increasing plot dimensions. The opposite is apparent for canopy length, it is suggested this is a result of a spatially heterogeneous understorey layer negatively skewing the distribution.

The impact of sensor characteristics for obtaining accurate ground-based measurements of LAI

Calibration and validation of LAI products require accurate ground-based measurements. Many indirect ground-based sensors such as digital hemispherical photography (DHP), ceptometers, and terrestrial laser scanners (TLS) are used interchangeably to estimate reference values. However these sensors have biases in regards to the true LAI value, which can never be known in the field. Results from three representative woody ecosystems in Eastern Australia are presented from real field measurements. Significant differences were found between methods at the individual measurement and plot scale. Furthermore, one of the sites in South East Australia was measured and modeled in a 3D deterministic model. In this digital environment where the truth is known, sensors can be simulated to determine their bias.

Spectral Response of Citrus and Their Application to Nutrient and Water Constraints Diagnosis

The early diagnosis of nutrient and water stress is a key issue for the proper management of orchards. Unfortunately, the measurement of indicators in the field to assess those deficiencies is expensive and time consuming. Remote sensing provides the possibility of assessing water and nutrient stress over every single stand on the whole area of interest. Leaf and canopy spectra are affected by every vegetation process or change in leaf pigments. However, the effect of each nutrient deficiency on the canopy spectrum is very subtle and the wavelength ranges affected by the different nutrients are generally overlapping. Then, an analysis in detail is needed in order to properly discriminate between the different stress causes. This chapter presents a review of previous studies dealing with remote sensing of nutrient and water stress, defining the spectral regions affected and the methodologies that have been applied for vegetation stress assessment. Specific multispectral indices related to leaf pigment content and physiological vegetation processes, thermal imagery, and fluorescence studies are presented. Finally, some results obtained from radiative transfer modeling simulations highlight the importance of the spatial resolution for precise agriculture purposes.