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Terrestrial laser scanning (TLS) can be used to characterize a woodland site by measuring structural attributes of the vegetation community. In Australia, government funded programs monitor vegetation structure using manual field surveys to assess change and ecological condition. In this study, we examined whether structural attributes commonly assessed in woodland ecology surveys can be extracted from a single TLS scan. Attributes of the ground, shrub and overstory vegetation layers were evaluated at nine open woodland sites in central Western Queensland. We used 0.1 m voxels to aggregate returns. Our results show that, compared with field assessment by highly experienced ecologists, TLS can rapidly characterize structural attributes for tree canopy cover, maximum tree height, average tree height (R > 0.9) and average diameter at breast height (R = 0.77). However, we could not accurately determine shrub height, shrub canopy cover, shrub average height, ground cover (grass, litter and coarse woody debris) or the number of trees per hectare (R < 0.45). By analysing local minima in the histogram of the maximum height, we determined height thresholds for canopy strata, and applied these to determine the canopy layer with the most biomass – the ecologically dominant layer (EDL). While these results are promising for overstory assessment and defining canopy strata heights using TLS, they suggest that future research should focus on investigating improved classification methods to separate laser returns into shrub and tree objects for structural assessment at the plot scale.

Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) technologies capture spatially detailed estimates of surface topography and when collected multi-temporally can be used to assess geomorphic change. The sensitivity and repeatability of ALS measurements to characterise geomorphic change in topographically complex environments such as gullies; however, remains an area lacking quantitative research. In this study, we captured coincident ALS and TLS datasets to assess their ability and synergies to detect geomorphic change for a gully located in Aratula, southeast Queensland, Australia. We initially used the higher spatial density and ranging accuracy of TLS to provide an assessment of the Digital Elevation Models (DEM) derived from ALS within a gully environment. Results indicated mean residual errors of 0.13 and 0.09 m along with standard deviation (SD) of residual errors of 0.20 and 0.16 m using pixel sizes of 0.5 and 1.0 m, respectively. The positive mean residual errors confirm that TLS data consistently detected deeper sections of the gully than ALS. We also compared the repeatability of ALS and TLS for characterising gully morphology. This indicated that the sensitivity to detect change using ALS is substantially lower than TLS, as expected, and that the ALS survey characteristics influence the ability to detect change. Notably, we found that using one ALS transect (mean density of 5 points / m2) as opposed to three transects increased the SD of residual error by approximately 30%. The supplied classification of ALS ground points was also demonstrated to misclassify gully features as non-ground, with minimum elevation filtering found to provide a more accurate DEM of the gully. The number and placement of terrestrial laser scans were also found to influence the derived DEMs. Furthermore, we applied change detection using two ALS data captures over a four year period and four TLS field surveys over an eight month period. This demonstrated that ALS can detect large scale erosional changes with head cutting of gully branches migrating approximately 10 m upslope. In comparison, TLS captured smaller scale intra-annual erosional patterns largely undetectable by the ALS dataset with a large rainfall event coinciding with the highest volumetric change (net change > 46 m3). Overall, these findings reaffirm the importance of quantifying DEM errors and demonstrate that ALS is unlikely to detect subtle geomorphic changes (

Terrestrial laser scanning (TLS) technology is a powerful tool for quantifying gully morphology and monitoring change over time. This is due to the high sampling density, sub-centimetre positional accuracies (x, y, z), flexibility of survey configurations and ability to link multiple TLS scans together. However, to ensure correct interpretation of results, research is needed to test the repeatability of TLS derived products to quantify the accuracy and separate ‘false’ from ‘true’ geomorphic change. In this study, we use the RIEGL VZ400 scanner to test the repeatability of TLS datasets for mapping gully morphology. We then quantify change following a rainfall event of approximately 100 mm. Our study site, located in south-east Queensland, Australia was chosen to be challenging from a repeatability perspective with high topographic variability. The TLS data capture involved three sets of linked scans: one survey pre-rainfall, to be compared to two surveys post-rainfall acquired on consecutive days. Change is considered negligible in the two post-rainfall scans to test survey repeatability. To verify TLS accuracy, an independent dataset of gully extent and spot heights were acquired using traditional total station techniques. Results confirm that the TLS datasets can be registered multi-temporally at sub-centimetre levels of accuracy in three dimensions. Total station and TLS elevation samples showed strong agreement with a mean error and standard deviation (SD) of residuals equal to 0.052 and 0.047 m, respectively (n = 889). Significantly, our repeatability tests found that return type and pulse deviation influence the accuracy and repeatability of DEMs in gully environments. Analysis of consecutive day datasets showed that DEMs derived from first return data recorded 40% higher SD of residual error than DEMs using multiple return data. A significant empirical relationship between pulse deviation and the variance of residuals for repeat DEMs is also shown (r2 = 0.95). By accounting for pulse deviation, we demonstrate that a spatially variable change detection threshold increased the geomorphic change detected following the rainfall event. Overall, this work supports TLS as a tool for monitoring change in gully morphology; however, consideration of the survey configuration is needed to maximise the change detected and ensure repeatability of results.

Vegetation condition is a measure of the health, function and long-term viability of an ecosystem and can be described in terms of structure, function and composition of the community. In Australia, government funded programs monitor vegetation structure using manual field surveys to assess change and ecological condition.Terrestrial laser scanning (TLS) is a ground-based form of lidar (light detection and ranging) that generates highly accurate three-dimensional point clouds of positional coordinates. Although TLS has been used to measure vegetation structure for a number of years, to date there has been limited research published using it to assess vegetation condition for biodiversity values. This thesis investigated the use of TLS for measuring site-based vegetation structural attributes in Australian vegetation communities, as a surrogate measure for vegetation condition and biodiversity. It compares the structure estimates derived from TLS to the Queensland Government BioCondition protocol for assessing vegetation condition.The research completed in Chapter 2 shows that accurately defining the ground surface is an important first step in measuring vegetation structure with TLS. Field work to gather co-incident TLS and total station survey points was completed in November 2015, at a single site in an open eucalypt forest at D’Aguilar National Park (GOLD0101), near Brisbane, Queensland, Australia. A new method to produce a very fine resolution (2cm) Digital Elevation Model (DEM) from TLS was outlined and its accuracy assessed against airborne lidar (acquired by a commercial provider in October 2014) and the total station survey points. By using the DEM production method described in Chapter 2, height errors associated with the DEM were minimised for the measurement of tree and shrub height in the following chapters.Chapter 3 showed that both TLS and a low-cost photogrammetry method can accurately measure diameter at breast height (DBH), stem density and basal area. During July/August 2013 coincident TLS and photogrammetry panorama photos were collected at the GOLD0101 site and an additional open eucalypt woodland site at Karawatha Forest Park, near Brisbane, Queensland, Australia. The findings showed that DBH could be measured within 2 cm for both TLS and the photo panoramas and that basal area was closer to field measurements with photo panoramas. TLS had a closer stem count to field measurements, but still underestimated the number of stems at a plot, due to occlusion occurring within the single scan. The use of a low-cost camera, field equipment and software, such as those used to produce photo panoramas, allows for uptake of this technology to automatically measure vegetation structure attributes, and does not require a large capital outlay to purchase a TLS instrument.The TLS and field data used in both Chapters 4 and 5, was collected during March 2014 in the poplar box (Eucalyptus populnea) and brigalow (Acacia harpophylla) woodlands of western Queensland. In Chapter 4 it was determined that TLS could accurately measure the vegetation structure of the overstorey. However, the method used for measuring understory structure needs further work to separate and classify the canopy strata into shrubs, trees and understory. Chapter 5 revealed that compared to field measurements, TLS estimates of vegetation structure can be used to accurately assign a site to a vegetation condition class, in the poplar box and brigalow vegetation communities of western Queensland.The research presented in this thesis demonstrated the ability of TLS to provide a fast and efficient method for the characterisation of vegetation condition in an open woodland environment. By capturing a permanent site record, the repeatability of vegetation condition assessment is improved, while also minimising operator bias. Future directions of this research are suggested including: improved methods for classification of the understory and overstory from TLS, use of multiple TLS scan positions to reduce errors caused by occlusion with a single TLS scan position, and using TLS for vegetation species classification. It is also suggested that by combining TLS with unmanned aerial vehicles and airborne lidar, TLS has the capacity to improve and extend the broad scale application of site based condition assessment. This will have important applications in the future direction of land management policy and assessment of native vegetation, allowing for better management of natural ecosystems.

Vegetation metrics, such as leaf area (LA), leaf area density (LAD), and vertical leaf area profile, are essential measures of tree-scale biophysical processes associated with photosynthetic capacity, and canopy geometry. However, there are limited published investigations of their use for horticultural tree crops. This study evaluated the ability of light detection and ranging (LiDAR) for measuring LA, LAD, and vertical leaf area profile across two mango, macadamia and avocado trees using discrete return data from a RIEGL VZ-400 Terrestrial Laser Scanning (TLS) system. These data were collected multiple times for individual trees to align with key growth stages, essential management practices, and following a severe storm. The first return of each laser pulse was extracted for each individual tree and classified as foliage or wood based on TLS point cloud geometry. LAD at a side length of 25 cm voxels, LA at the canopy level and vertical leaf area profile were calculated to analyse tree crown changes. These changes included: (1) pre-pruning vs. post-pruning for mango trees; (2) pre-pruning vs. post-pruning for macadamia trees; (3) pre-storm vs. post-storm for macadamia trees; and (4) tree leaf growth over a year for two young avocado trees. Decreases of 34.13 m2 and 8.34 m2 in LA of mango tree crowns occurred due to pruning. Pruning for the high vigour mango tree was mostly identified between 1.25 m and 3 m. Decreases of 38.03 m2 and 16.91 m2 in LA of a healthy and unhealthy macadamia tree occurred due to pruning. After flowering and spring flush of the same macadamia trees, storm effects caused a 9.65 m2 decrease in LA for the unhealthy tree, while an increase of 34.19 m2 occurred for the healthy tree. The tree height increased from 11.13 m to 11.66 m, and leaf loss was mainly observed between 1.5 m and 4.5 m for the unhealthy macadamia tree. Annual increases in LA of 82.59 m2 and 59.97 m2 were observed for two three-year-old avocado trees. Our results show that TLS is a useful tool to quantify changes in the LA, LAD, and vertical leaf area profiles of horticultural trees over time, which can be used as a general indicator of tree health, as well as assist growers with improved pruning, irrigation, and fertilisation application decisions.

State Government agencies in northern and eastern Australia and the University of Queensland, Brisbane, have been collaborating through the Joint Remote Sensing Research Program (JRSRP). This has resulted in a significant acceleration in the development and successful operational application of remote sensing methods for the JRSRP members and the various state and national programs and policies which they support. The JRSRP provides an open and collaborative mechanism and governance structure to successfully bring together a unique combination of expertise in image processing, field data collection, and data integration approaches to deliver accurate, repeatable and robust methods for mapping and monitoring Australia’s unique ecosystems. Remote sensing provides spatially- and temporally-comprehensive information about land cover features at a range of scales and often for minimal cost compared to traditional mapping and monitoring approaches. This makes remote sensing a very useful operational mapping and monitoring tool for land managers, particularly in the vast rangelands of Australia. This paper outlines recent developments in remote sensing and modelling products that are being used operationally by JRSRP members to address large area landcover understanding.

Terrestrial laser scanning (TLS) data provide 3-D measurements of vegetation structure and have the potential to support the calibration and validation of satellite and airborne sensors. The increasing range of different commercial and scientific TLS instruments holds challenges for data and instrument interoperability. Using data from various TLS sources will be critical to upscale study areas or compare data. In this paper, we provide a general framework to compare the interoperability of TLS instruments. We compare three TLS instruments that are the same make and model, the RIEGL VZ-400. We compare the range accuracy and evaluate the manufacturer’s radiometric calibration for the uncalibrated return intensities. Our results show that the range accuracy between instruments is comparable and within the manufacturer’s specifications. This means that the spatial XYZ data of different instruments can be combined into a single data set. Our findings demonstrate that radiometric calibration is instrument specific and needs to be carried out for each instrument individually before including reflectance information in TLS analysis. We show that the residuals between the calibrated reflectance panels and the apparent reflectance measured by the instrument are greatest for highest reflectance panels (residuals ranging from 0.058 to 0.312).

A new wave of terrestrial lidar scanners, optimized for rapid scanning and portability, such as the Compact Biomass Lidar (CBL), enable and improve observations of structure across a range of important ecosystems. We performed studies with the CBL in temperate and tropical forests, caves, salt marshes and coastal areas subject to erosion. By facilitating additional scanning points, and therefore view angles, this new class of terrestrial lidar alters observation coverage within samples, potentially reducing uncertainty in estimates of ecosystem properties. The CBL has proved competent at reconstructing trees and mangrove roots using the same cylinder-based Quantitative Structure Models commonly utilized for data from more capable instruments (Raumonen et al. 2013). For tropical trees with morphologies that challenge standard reconstruction techniques, such as the buttressed roots of Ceiba trees and the multiple stems of strangler figs, the CBL was able to provide the versatility and the speed of deployment needed to fully characterize their unique features. For geomorphological features, the deployment flexibility of the CBL enabled sampling from optimal view-angles, including from a novel suspension system for sampling salt marsh creeks. Overall, the practical aspects of these instruments, which improve deployment logistics, and therefore data acquisition rate, are shown to be emerging capabilities, greatly increasing the potential for observation, particularly in highly temporally dynamic, inaccessible and geometrically complex ecosystems. In order to better analyze information quality across these diverse and challenging ecosystems, we also provide a novel and much-needed conceptual framework, the microstate model, to characterize and mitigate uncertainties in terrestrial lidar observations. publishedVersion

The scan-line corrector (SLC) for the Enhanced Thematic Mapper Plus (ETM+) sensor, on board the Landsat 7 satellite, failed permanently in 2003. The consequence of the SLC failure (or SLC-off ) is that about 20% of the pixels in an ETM+ image are not scanned. We aim to develop a geostatistical method that estimates the missing values. Our rationale is to collect three cloud-free images for a particular Landsat scene, taken within a few weeks of each other: the middle image is the target whose un-scanned locations we wish to estimate; the earlier and later images are used as secondary information. We visit each un-scanned location in the target image and, for each reflectance band in turn, predict the missing value with cokriging (resorting to kriging when there is not enough local secondary information to justify cokriging). For three Landsat scenes in different bio-regions of Queensland, Australia, we compared the performance of geostatistical interpolation with image compositing. Geostatistics was a generally superior estimator. In contrast to compositing, geostatistics was able to estimate accurately values at all un-scanned locations, and was able to quantify the variance associated with each prediction. SLC-off images interpolated with geostatistics were visually sensible, although changes in land-use from pixel to pixel affected adversely the accuracy of prediction. The primary disadvantage of geostatistics was its relatively slow computing speed. We recommend the geostatistical method over compositing, but, if speed takes priority over statistical rigour, a hybrid technique–whereby composites are corrected to the local means and variances of the bands in the target image, and any un-estimable locations are interpolated geostatistically–is an adequate compromise.

This paper evaluates the potential of very high resolution multispectral (Worldview-3) satellite imagery for mapping yield parameters in avocado and macadamia orchards. An evaluation of 18 structural and pigment based vegetation indices (VIs) derived from Worldview-3 imagery identified a positive relationship to nut/ fruit weight (kg/tree) R2>0.69 for macadamia and R2>0.68 for avocado; and nut/ fruit number (per tree) R2>0.6 for macadamia and R2>0.61 for avocado. Using the algorithms derived between the optimal VI and the measured parameter, yield and nut/ fruit number maps were derived for each block. In the absence of a commercial yield monitor, the resulting yield maps offer significant benefit to growers for improving orchard management, harvest scheduling, and forward selling decisions.