ORCID Profile
0000-0003-1203-6281
Current Organisation
University of Adelaide
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Land Capability And Soil Degradation | Photogrammetry And Remote Sensing | Soil Sciences | Environmental Science and Management | Vertebrate Biology | Spatial Information Systems | Environmental Technologies | Terrestrial Ecology | Zoology | Geomatic Engineering | Natural Resource Management |
ANZSRC Socio-Economic Objective (SEO)
Land and water management | Integrated (ecosystem) assessment and management | Land and water management | Expanding Knowledge in the Environmental Sciences | Flora, Fauna and Biodiversity at Regional or Larger Scales | Scientific instrumentation
Related Links
Publications
Mapping the long‐term influence of river discharge on coastal ocean chlorophyll‐a
Publisher: Wiley
Date: 07-06-2022
DOI: 10.1002/RSE2.266
Abstract: Although the potential of river discharge to support ocean productivity and marine ecosystems is known, the specifics of this relationship are poorly understood in many regions of the world. Global estimates of river flow indicate that river discharge is decreasing due to the increasing fragmentation, extraction and regulation of rivers. This likely means that the contribution of river flow to coastal productivity and water quality is changing, potentially leading to fewer and smaller magnitude ocean fertilisation events. We developed a simple analysis method, based on Earth observation data, to investigate where coastal ocean chlorophyll‐ a is most strongly influenced by river discharge. The per‐pixel spatiotemporal correlation technique (implemented using Python) correlates chlorophyll‐ a concentration (a proxy for phytoplankton biomass and indicator of primary productivity) from MODIS ocean colour data with river discharge data. The method was tested globally on 11 different rivers discharging into coastal ocean regions. Our findings suggest some of the world's largest river systems, such as the Amazon River, have zones of elevated coastal chl‐ a that extend hundreds to thousands of km from the river mouth. These findings suggest the influence of river discharge may have been underestimated in many coastal regions of the world. The method appears more effective for larger river systems discharging to ocean waters with less complex nutrient dynamics and weaker seasonal productivity patterns, most notably in temperate regions. Increasing our understanding of the specific areas influenced by river discharge, and the degree of influence over space and time, is an important step towards the improved river and coastal management. This method will increase the capacity of researchers to monitor how, when and where coastal waters are affected as river discharge continues to change into the future.
Corrigendum to 'A new approach to monitoring spatial distribution and dynamics of wetlands and associated flows of Australian Great Artesian Basin springs using QuickBird satellite imagery' [Hydrol 408 (2011) 140-152]
Publisher: Elsevier BV
Date: 11-2011
Phenologic metrics derived from MODIS NDVI as indicators for Plant Available Water-holding Capacity
Publisher: Elsevier BV
Date: 2016
Comparison of Hyperspectral Versus Traditional Field Measurements of Fractional Ground Cover in the Australian Arid Zone
Publisher: MDPI AG
Date: 28-11-2019
DOI: 10.3390/RS11232825
Abstract: The collection of high-quality field measurements of ground cover is critical for calibration and validation of fractional ground cover maps derived from satellite imagery. Field-based hyperspectral ground cover s ling is a potential alternative to traditional in situ techniques. This study aimed to develop an effective s ling design for spectral ground cover surveys in order to estimate fractional ground cover in the Australian arid zone. To meet this aim, we addressed two key objectives: (1) Determining how spectral surveys and traditional step-point s ling compare when conducted at the same spatial scale and (2) comparing these two methods to current Australian satellite-derived fractional cover products. Across seven arid, sparsely vegetated survey sites, six 500-m transects were established. Ground cover reflectance was recorded taking continuous hyperspectral readings along each transect while step-point surveys were conducted along the same transects. Both measures of ground cover were converted into proportions of photosynthetic vegetation, non-photosynthetic vegetation, and bare soil for each site. Comparisons were made of the proportions of photosynthetic vegetation, non-photosynthetic vegetation, and bare soil derived from both in situ methods as well as MODIS and Landsat fractional cover products. We found strong correlations between fractional cover derived from hyperspectral and step-point s ling conducted at the same spatial scale at our survey sites. Comparison of the in situ measurements and image-derived fractional cover products showed that overall, the Landsat product was strongly related to both in situ methods for non-photosynthetic vegetation and bare soil whereas the MODIS product was strongly correlated with both in situ methods for photosynthetic vegetation. This study demonstrates the potential of the spectral transect method, both in its ability to produce results comparable to the traditional transect measures, but also in its improved objectivity and relative logistic ease. Future efforts should be made to include spectral ground cover s ling as part of Australia’s plan to produce calibration and validation datasets for remotely sensed products.
Land capability of fukang county, xinjiang province, people’s republic of china
Publisher: Informa UK Limited
Date: 10-1994
Have droughts and increased water extraction from the Murray River (Australia) reduced coastal ocean productivity?
Publisher: CSIRO Publishing
Date: 2018
DOI: 10.1071/MF17226
Abstract: River discharges are decreasing in many regions of the world however, the consequences of this on water quality and primary productivity of receiving coastal oceans are largely unclear. We analysed satellite remote-sensing data (MODIS) of the coastal ocean zone that receives outflows from the Murray River, from 2002 to 2016. This system has experienced historical flow reductions and a recent extreme hydrological ‘Millennium’ drought. Remotely sensed chlorophyll-a and particulate organic carbon in the coastal ocean were strongly correlated with river outflows (R2 .6) in an 8-km radial buffer zone from the Murray Mouth, and the river influence extended up to ~60km from the Murray Mouth during high-flow periods. This distance was approximately three times greater than the freshwater plume extent during maximum flows in 2011, suggesting that new primary productivity was created. In contrast, there was no additional coastal ocean productivity above background levels from 2007 to 2010 when river outflows ceased. Hindcast calculations based on historical flows from 1962 to 2002 suggest that declining Murray River flows have greatly reduced primary productivity in adjacent coastal waters. This has potential consequences for higher trophic levels and should be considered in future management planning.
A review of methods for analysing spatial and temporal patterns in coastal water quality
Publisher: Elsevier BV
Date: 2011
Reflecting on siliceous rocks in central Australia: Using advanced remote sensing to map ancient “tool‐stone” resources
Publisher: Wiley
Date: 19-12-2020
DOI: 10.1002/GEA.21776
Site-based and remote sensing methods for monitoring indicators of vegetation condition: An Australian review
Publisher: Elsevier BV
Date: 2016
Additive partitioning of rarefaction curves: Removing the influence of sampling on species-diversity in vegetation surveys
Publisher: Elsevier BV
Date: 2011
Objective Regolith-Landform Mapping in a Regolith Dominated Terrain to Inform Mineral Exploration
Publisher: MDPI AG
Date: 24-08-2018
DOI: 10.3390/GEOSCIENCES8090318
Abstract: An objective method for generating statistically sound objective regolith-landform maps using widely accessible digital topographic and geophysical data without requiring specific regional knowledge is demonstrated and has application as a first pass tool for mineral exploration in regolith dominated terrains. This method differs from traditional regolith-landform mapping methods in that it is not subject to interpretation and bias of the mapper. This study was undertaken in a location where mineral exploration has occurred for over 20 years and traditional regolith mapping had recently been completed using a standardized subjective methodology. An unsupervised classification was performed using a Digital Elevation Model, Topographic Position Index, and airborne gamma-ray radiometrics as data inputs resulting in 30 classes that were clustered to eight groups representing regolith types. The association between objective and traditional mapping classes was tested using the ‘Mapcurves’ algorithm to determine the ‘Goodness-of-Fit’, resulting in a mean score of 26.4% between methods. This Goodness-of-Fit indicates that this objective map may be used for initial mineral exploration in regolith dominated terrains.
Understanding the Spatially Variable Effects of Climate Change on Rice Yield for Three Ecotypes in Bangladesh, 1981–2010
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/6287156
Abstract: Climate change will impact on rice food security in many parts of the world, including Bangladesh. Little attention has been given to understanding the impact of climate on rice yield for three main ecotypes (Aus, Aman, and Boro) in different areas of the country. The aim of this paper was to analyse the spatiotemporal dynamics of rice yield and climatic variables and the spatially variable climate effects on rice yield for these ecotypes in Bangladesh during 1981–2010 by employing linear mixed models and generalized linear models. The results demonstrated the substantial spatiotemporal variations of rice yield for all ecotypes across the country. Rice yield for ecotypes was more susceptible to temperature changes than rainfall effects. Modelling of a 1°C temperature increase in the country showed strong regional differences in rice yield for these ecotypes. The study concludes that future temperature changes are likely to change regional rice yield for all ecotypes and hence impact food security. The results have important consequences for food security by indicating the need for appropriate region-specific adaptation measures to reduce rice yield variability in the future. The results show the need to consider spatial differences for policy development to improve food security in Bangladesh.
Hyperspectral Classification of Plants: A Review of Waveband Selection Generalisability
Publisher: MDPI AG
Date: 2020
DOI: 10.3390/RS12010113
Abstract: Hyperspectral sensing, measuring reflectance over visible to shortwave infrared wavelengths, has enabled the classification and mapping of vegetation at a range of taxonomic scales, often down to the species level. Classification with hyperspectral measurements, acquired by narrow band spectroradiometers or imaging sensors, has generally required some form of spectral feature selection to reduce the dimensionality of the data to a level suitable for the construction of a classification model. Despite the large number of hyperspectral plant classification studies, an in-depth review of feature selection methods and resultant waveband selections has not yet been performed. Here, we present a review of the last 22 years of hyperspectral vegetation classification literature that evaluates the overall waveband selection frequency, waveband selection frequency variation by taxonomic, structural, or functional group, and the influence of feature selection choice by comparing such methods as stepwise discriminant analysis (SDA), support vector machines (SVM), and random forests (RF). This review determined that all characteristics of hyperspectral plant studies influence the wavebands selected for classification. This includes the taxonomic, structural, and functional groups of the target s les, the methods, and scale at which hyperspectral measurements are recorded, as well as the feature selection method used. Furthermore, these influences do not appear to be consistent. Moreover, the considerable variability in waveband selection caused by the feature selectors effectively masks the analysis of any variability between studies related to plant groupings. Additionally, questions are raised about the suitability of SDA as a feature selection method, with it producing waveband selections at odds with the other feature selectors. Caution is recommended when choosing a feature selector for hyperspectral plant classification: We recommend multiple methods being performed. The resultant sets of selected spectral features can either be evaluated in idually by multiple classification models or combined as an ensemble for evaluation by a single classifier. Additionally, we suggest caution when relying upon waveband recommendations from the literature to guide waveband selections or classifications for new plant discrimination applications, as such recommendations appear to be weakly generalizable between studies.
Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2001
DOI: 10.1109/36.934078
Numeric classification as an aid to spectral mapping of vegetation communities
Publisher: Springer Science and Business Media LLC
Date: 1998
Environmental zonation across the Australian arid region based on long-term vegetation dynamics
Publisher: Elsevier BV
Date: 06-2011
Using satellite imagery to assess the distribution and abundance of southern hairy-nosed wombats (Lasiorhinus latifrons)
Publisher: Elsevier BV
Date: 06-2018
A new approach to monitoring spatial distribution and dynamics of wetlands and associated flows of Australian Great Artesian Basin springs using QuickBird satellite imagery
Publisher: Elsevier BV
Date: 09-2011
The Development of Hyperspectral Distribution Maps to Predict the Content and Distribution of Nitrogen and Water in Wheat (Triticum aestivum)
Publisher: Frontiers Media SA
Date: 30-10-2019
Testing the Temporal Ability of Landsat Imagery and Precision Agriculture Technology to Provide High Resolution Historical Estimates of Wheat Yield at the Farm Scale
Publisher: MDPI AG
Date: 26-03-2013
DOI: 10.3390/RS5041549
Stormwater quality improvement potential of an urbanised catchment using water sensitive retrofits into public parks
Publisher: Elsevier BV
Date: 2014
Buffel grass (Cenchrus ciliaris) as an invader and threat to biodiversity in arid environments: A review
Publisher: Elsevier BV
Date: 03-2012
Understanding Phytoplankton Variability Throughout Spencer Gulf, South Australia, via Satellite Derived Chlorophyll-A
Publisher: IEEE
Date: 2008
Rapid identification of shallow inundation for mosquito disease mitigation using drone-derived multispectral imagery
Publisher: PAGEPress Publications
Date: 17-06-2020
DOI: 10.4081/GH.2020.851
Abstract: Mosquito breeding habitat identification often relies on slow, labour-intensive and expensive ground surveys. With advances in remote sensing and autonomous flight technologies, we endeavoured to accelerate this detection by assessing the effectiveness of a drone multispectral imaging system to determine areas of shallow inundation in an intertidal saltmarsh in South Australia. Through laboratory experiments, we characterised Near-Infrared (NIR) reflectance responses to water depth and vegetation cover, and established a reflectance threshold for mapping water sufficiently deep for potential mosquito breeding. We then applied this threshold to field-acquired drone imagery and used simultaneous in-situ observations to assess its mapping accuracy. A NIR reflectance threshold of 0.2 combined with a vegetation mask derived from Normalised Difference Vegetation Index (NDVI) resulted in a mapping accuracy of 80.3% with a Cohen’s Kappa of 0.5, with confusion between vegetation and shallow water depths ( 10 cm) appearing to be major causes of error. This high degree of mapping accuracy was achieved with affordable drone equipment, and commercially available sensors and Geographic Information Systems (GIS) software, demonstrating the efficiency of such an approach to identify shallow inundation likely to be suitable for mosquito breeding.
Monitoring temporal Vegetation changes in Lao tropical forests
Publisher: IOP Publishing
Date: 23-06-2014
Visible near-infrared reflectance spectroscopy as a predictive indicator of soil properties
Publisher: Elsevier BV
Date: 2011
Cross-fence comparisons: Theory for spatially comprehensive, controlled variable assessment of treatment effects in managed landscapes
Publisher: Elsevier BV
Date: 03-2011
Digital Terrain Analysis Reveals New Insights into the Topographic Context of Australian Aboriginal Stone Arrangements
Publisher: Wiley
Date: 16-02-2017
DOI: 10.1002/ARP.1567
A remote sensing spatio-temporal framework for interpreting sparse indicators in highly variable arid landscapes
Publisher: Elsevier BV
Date: 2016
Distinguishing Photosynthetic and Non-Photosynthetic Vegetation: How Do Traditional Observations and Spectral Classification Compare?
Publisher: MDPI AG
Date: 04-11-2019
DOI: 10.3390/RS11212589
Abstract: Remotely sensed ground cover maps are routinely validated using field data collected by observers who classify ground cover into defined categories such as photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare soil (BS), and rock. There is an element of subjectivity to the classification of PV and NPV, and classifications may differ between observers. An alternative is to estimate ground cover based on in situ hyperspectral reflectance measurements (HRM). This study examines observer consistency when classifying vegetation s les of wheat (Triticum aestivum var. Gladius) covering the full range of photosynthetic activity, from completely senesced (0% PV) to completely green (100% PV), as photosynthetic or non-photosynthetic. We also examine how the classification of spectra of the same vegetation s les compares to the observer results. We collected HRM and photographs, over two months, to capture the transition of wheat leaves from 100% PV to 100% NPV. To simulate typical field methodology, observers viewed the photographs and classified each leaf as either PV or NPV, while spectral unmixing was used to decompose the HRM of the leaves into proportions of PV and NPV. The results showed that when a leaf was ≤25% or ≥75% PV observers tended to agree, and assign the leaf to the expected category. However, as leaves transitioned from PV to NPV (i.e., PV ≥ 25% but ≤ 75%) observers’ decisions differed more widely and their classifications showed little agreement with the spectral proportions of PV and NPV. This has significant implications for the reliability of data collected using binary methods in areas containing a significant proportion of vegetation in this intermediate range such as the over/underestimation of PV and NPV vegetation and how reliably this data can then be used to validate remotely sensed products.
Evaluation and comparison of hyperspectral imagery for mapping surface symptoms of dryland salinity
Publisher: Informa UK Limited
Date: 02-2009
Unmixing of soil types and estimation of soil exposure with simulated hyperspectral imagery
Publisher: Informa UK Limited
Date: 22-07-2011
CropPhenology: An R package for extracting crop phenology from time series remotely sensed vegetation index imagery
Publisher: Elsevier BV
Date: 07-2018
Spatio-temporal analysis of the impact of climate, cropping intensity and means of irrigation: An assessment on rice yield determinants in Bangladesh
Publisher: Springer Science and Business Media LLC
Date: 19-07-2016
Mapping the surface expression and vegetation communities of Australian Great Artesian Basin springs using hyperspectral analyses
Publisher: IEEE
Date: 07-2013
A method to map riparian exotic vegetation (Salix spp.) area to inform water resource management
Publisher: Wiley
Date: 09-07-2014
DOI: 10.1002/HYP.9916
Severity of salinity accurately detected and classified on a paddock scale with high resolution multispectral satellite imagery
Publisher: Wiley
Date: 27-06-2013
DOI: 10.1002/LDR.1134
Detecting new Buffel grass infestations in Australian arid lands: Evaluation of methods using high-resolution multispectral imagery and aerial photography
Publisher: Springer Science and Business Media LLC
Date: 14-11-2014
Forest Cover Changes in Lao Tropical Forests: Physical and Socio-Economic Factors are the Most Important Drivers
Publisher: MDPI AG
Date: 28-03-2017
DOI: 10.3390/LAND6020023
Koala Counter: Recording Citizen Scientists’ search paths to Improve Data Quality
Publisher: Elsevier BV
Date: 12-2020
Evaluation of vegetation indices for assessing vegetation cover in southern arid lands in South Australia
Publisher: CSIRO Publishing
Date: 2007
DOI: 10.1071/RJ06033
Abstract: Vegetation indices are widely used for assessing and monitoring ecological variables such as vegetation cover, above-ground biomass and leaf area index. This study reviewed and evaluated different groups of vegetation indices for estimating vegetation cover in southern rangelands in South Australia. Slope-based, distance-based, orthogonal transformation and plant-water sensitive vegetation indices were calculated from Landsat thematic mapper (TM) image data and compared with vegetation cover estimates at monitoring points made during Pastoral Lease assessments. Relationships between various vegetation indices and vegetation cover were compared using simple linear regression at two different scales: within two contrasting land systems and across broader regional landscapes. Of the vegetation indices evaluated, stress related vegetation indices using red, near-infrared and mid-infrared TM bands consistently showed significant relationships with vegetation cover at both land system and landscape scales. Estimation of vegetation cover was more accurate within land systems than across broader regions. Total perennial and ephemeral plant cover was best predicted within land systems, while combined vegetation, plant litter and soil cryptogam crust cover was best predicted at landscape scale. These results provide a strong foundation for use of vegetation indices as an adjunct to field methods for assessing vegetation cover in southern Australia.
Non-detection errors in a survey of persistent, highly-detectable vegetation species
Publisher: Springer Science and Business Media LLC
Date: 22-03-2011
DOI: 10.1007/S10661-011-1991-0
Abstract: Rare, small or annual vegetation species are widely known to be imperfectly detected with single site surveys by most conventional vegetation survey methods. However, the detectability of common, persistent vegetation species is assumed to be high, but without supporting research. In this study, we evaluate the extent of false-negative errors of perennial vegetation species in a systematic vegetation survey in arid South Australia. Analysis was limited to the seven most easily detected persistent vegetation species and controlled for observer skill. By comparison of methodologies, we then predict the magnitude of non-detection error rates in a second survey. The analysis revealed that all but one highly detectable perennial vegetation species was imperfectly detected (detection probabilities ranged from 0.22 to 0.83). While focussed in the Australian rangelands, the implications of this study are far reaching. Inferences drawn from systematic vegetation surveys that fail to identify and account for non-detection errors should be considered potentially flawed. The identification of this problem in vegetation surveying is long overdue. By comparison, non-detection has been a widely acknowledged, and dealt with, problem in fauna surveying for decades. We recommend that, where necessary, vegetation survey methodology adopt the methods developed in fauna surveying to cope with non-detection errors.
Landsat and GRACE observations of arid wetland dynamics in a dryland river system under multi-decadal hydroclimatic extremes
Publisher: Elsevier BV
Date: 12-2016
Self-organization and complex dynamics of regenerating vegetation in an arid ecosystem: 82 years of recovery after grazing
Publisher: Elsevier BV
Date: 2013
Population status of eucalypt trees on the River Murray floodplain, South Australia
Publisher: Wiley
Date: 02-2005
DOI: 10.1002/RRA.846
Abstract: For populations to persist, recruitment must keep pace with mortality. In variable environments, opportunities for reproduction occur patchily in time and space, and favourable conditions must occur sufficiently often to allow growth to maturity (hence ‘recruitment’). The risks of local extinctions may be increased by anthropogenic factors. This scenario is illustrated by two tree species, river red gum ( Eucalyptus camaldulensis ) and black box ( E. largiflorens ), on the floodplain of the River Murray, South Australia. Fixed area plots were established at Banrock Station, where large, mature trees are common, although red gum outnumber black box by about four to one. Trunk diameter was measured as a surrogate for tree age. The smallest diameter (0–10 cm) black box are nearly as common as seedlings of that species, whereas the smallest diameter red gum (0–10 cm) are 10 times more abundant than seedlings. Small trees of both species occur in localized clumps, and the respective size‐class distributions exhibit series of peaks and falls, suggesting episodic recruitment and opportunistic survival. Population viability calculations suggest that more than 100% of existing saplings need to survive to maintain the local black box population (i.e. there are too few saplings). The red gum population apparently requires a smaller proportion of survivors, but the calculations may be biased by the clumped distribution of the saplings. Based on population structure and viability estimates, black box at this site appear to lack sufficient regeneration to compensate for adult mortality while red gum appear to have a much better balance. The methods established here may be useful for assessment of stands of these species in other areas. Copyright © 2005 John Wiley & Sons, Ltd.
Species composition related to spectral classification in an Australian Spinifex hummock grassland
Publisher: Informa UK Limited
Date: 11-1994
A generalizable NDVI-based wetland delineation indicator for remote monitoring of groundwater flows in the Australian Great Artesian Basin
Publisher: Elsevier BV
Date: 2016
Dingo interactions with exotic mesopredators: spatiotemporal dynamics in an Australian arid-zone study
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/WR15104
Abstract: Context Apex predators occupy the top level of the trophic cascade and often perform regulatory functions in many ecosystems. Their removal has been shown to increase herbivore and mesopredator populations, and ultimately reduce species ersity. In Australia, it has been proposed that the apex predator, the dingo (Canis dingo), has the potential to act as a biological control agent for two introduced mesopredators, the red fox (Vulpes vulpes) and the feral cat (Felis catus). Understanding the mechanisms of interaction among the three species may assist in determining the effectiveness of the dingo as a control agent and the potential benefits to lower-order species. Aims To test the hypotheses that feral cats and foxes attempt to both temporally avoid dingoes and spatially avoid areas of high dingo use. Methods Static and dynamic interaction methodologies based on global positioning system (GPS) telemetry data were applied to test temporal and spatial interactions between the two mesopredators (n = 15) and a dingo pair (n = 2). The experimental behavioural study was conducted in a 37-km2 fenced enclosure located in arid South Australia. Key results The dynamic interaction analysis detected neither attraction nor avoidance between dingoes and cats or foxes at short temporal scales. There was no suggestion of delayed interactions, indicating that dingoes were not actively hunting mesopredators on the basis of olfactory signalling. However, static interaction analysis suggested that, although broad home ranges of cats and foxes overlapped with dingoes, core home ranges were mutually exclusive. This was despite similar habitat preferences among species. Conclusions We found that avoidance patterns were not apparent when testing interactions at short temporal intervals, but were manifested at larger spatial scales. Results support previous work that suggested that dingoes kill mesopredators opportunistically rather than through active hunting. Implications Core home ranges of dingoes may provide refuge areas for small mammals and reptiles, and ultimately benefit threatened prey species by creating mesopredator-free space. However, the potential high temporal variation in core home-range positioning and small size of mutually exclusive areas suggested that further work is required to determine whether these areas provide meaningful sanctuaries for threatened prey.
A comparison of NOAA-AVHRR fire data with three Landsat data sets in arid and semi-arid Australia
Publisher: Informa UK Limited
Date: 03-10-2012
Spatial indicators of fire risk in the arid and semi-arid zone of Australia
Publisher: Elsevier BV
Date: 2011
Evaluating MODIS soil fractional cover for arid regions, using albedo from high-spatial resolution satellite imagery
Publisher: Informa UK Limited
Date: 04-03-2014
Arid land characterisation with EO-1 hyperion hyperspectral data
Publisher: Elsevier BV
Date: 10-2012
An introduction to patterns of fire in arid and semi-arid Australia, 1998-2004
Publisher: CSIRO Publishing
Date: 2008
DOI: 10.1071/RJ07039
Abstract: Fire is a crucial element in shaping our world, whether of natural or anthropogenic origin. These fires can have both positive and negative consequences and impacts on our natural environment, society and its economics, not to mention global climate. Previous analyses of fire regimes in arid and semi-arid Australia have been of limited spatial or temporal extent. This lack of knowledge has h ered attempts at effective fire management. Satellite imagery allows the continuous detection, monitoring and mapping of fires. Active fires can be detected as fire hotspots, and burned areas mapped as patches from the change of surface reflectance properties in successive images. Data from NOAA’s advanced very high resolution radiometer (AVHRR) were used to assess the distribution, seasonality, frequency, number and extent of fire hotspots (FHS) and fire affected areas (FAA) across the entire arid and semi-arid country of Australia from 1998 to 2004. Utilising both of these fire datasets is important, as they complement each other and provide a more robust analysis of fire patterns. Between 1998 and 2004 almost 27% of arid and semi-arid Australia burnt at least once. The main trends in fire distribution follow latitudinal rainfall gradients. Regression analysis also shows a strong relationship with the pattern of antecedent rainfall. The seasonality of fire events varies between climate zones in accordance with the varying distribution of precipitation and temperature, which influence fuel accumulation and curing. For the first time we have a picture of fire patterns across the entire arid and semi-arid regions of the country. This includes several high fire years in certain areas following above-average rainfall. This analysis highlights similarities and differences between regions, giving policy makers and managers a basis from which to make more informed decisions in the present, and with which to compare future regimes.
Generative Adversarial Network Synthesis of Hyperspectral Vegetation Data
Publisher: MDPI AG
Date: 08-06-2021
DOI: 10.3390/RS13122243
Abstract: New, accurate and generalizable methods are required to transform the ever-increasing amount of raw hyperspectral data into actionable knowledge for applications such as environmental monitoring and precision agriculture. Here, we apply advances in generative deep learning models to produce realistic synthetic hyperspectral vegetation data, whilst maintaining class relationships. Specifically, a Generative Adversarial Network (GAN) is trained using the Cramér distance on two vegetation hyperspectral datasets, demonstrating the ability to approximate the distribution of the training s les. Evaluation of the synthetic spectra shows that they respect many of the statistical properties of the real spectra, conforming well to the s led distributions of all real classes. Creation of an augmented dataset consisting of synthetic and original s les was used to train multiple classifiers, with increases in classification accuracy seen under almost all circumstances. Both datasets showed improvements in classification accuracy ranging from a modest 0.16% for the Indian Pines set and a substantial increase of 7.0% for the New Zealand vegetation. Selection of synthetic s les from sparse or outlying regions of the feature space of real spectral classes demonstrated increased discriminatory power over those from more central portions of the distributions.
Airborne hyperspectral characterisation of hydrothermal alteration in a regolith-dominated terrain, southern Gawler Ranges, South Australia
Publisher: Informa UK Limited
Date: 18-10-2020
Monitoring temporal dynamics of Great Artesian Basin wetland vegetation, Australia, using MODIS NDVI
Publisher: Elsevier BV
Date: 11-2013
Comparison of methods for estimation of absolute vegetation and soil fractional cover using MODIS normalized BRDF-adjusted reflectance data
Publisher: Elsevier BV
Date: 03-2013
MODIS EVI and LST Temporal Response for Discrimination of Tropical Land Covers
Publisher: MDPI AG
Date: 13-05-2015
DOI: 10.3390/RS70506026
An image-based diversity index for assessing land degradation in an arid environment in South Australia
Publisher: Elsevier BV
Date: 07-2008
Monitoring expansion of plantations in Lao tropical forests using Landsat time series
Publisher: SPIE
Date: 08-11-2014
DOI: 10.1117/12.2068283
Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation
Publisher: Public Library of Science (PLoS)
Date: 13-11-2015
EchidnaCSI – Improving monitoring of a cryptic species at continental scale using Citizen Science
Publisher: Elsevier BV
Date: 08-2021
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