Using Spatial Technologies in Geoconservation and Geotourism

Mr Mark Williams1

1School of Technology, Environments and Design, University of Tasmania, Hobart, Australia


Conservation of novel, representative and diverse landforms, rocks and soils is termed ‘Geoheritage Conservation.’ Conservation of geoheritage is both popular and supported by robust assessment criteria in parts of Europe and China, where preservation occurs in UNESCO and local geoparks and via formalised inventory listings and conservation covenants. As geoheritage conservation expands as a discipline globally, it has become apparent that new tools are required to assist practitioners and researchers to communicate, remotely assess and detect, visualise and educate others about geoheritage. Geographic Information Systems (GIS) and Remote Sensing tools are obvious complements to geoheritage conservation, due to their applicability across all facets of the conservation lifecycle. In this presentation, we describe approaches to geoheritage conservation and the ways in which GIS and remote sensing can be used to enhance decision support and communication/education objectives. We use the second most geodiverse landscape on the planet –Tasmania – to illustrate our presentation.


Mark is a geoscientist with twenty years’ experience working in various technology industries. Mark’s work focuses on the role of GIS, remote sensing and other digital technologies to assess, classify and visualise geoheritage for use in geoconservation and geotourism fields.

Patterns of vegetation and landscape change before and after rabbit eradication on subantarctic Macquarie Island

Mr Nick Fitzgerald1, Distinguished Professor Jamie Kirkpatrick, Dr Jenny Scott1, Associate Professor Arko Lucieer1

1University Of Tasmania, Hobart, Australia


Eradication of invasive European rabbits from subantarctic Macquarie Island was achieved in 2011. The impacts of introduced rabbits on the vegetation of Macquarie Island are well-documented but few studies have investigated the ecosystem recovery process following the eradication or compared vegetation change between types of terrestrial ecosystems. We hypothesised that changes in vegetation would vary in their magnitude and direction in different ecosystems. Repeat landscape photography covering a 34 year period was used to examine differences in vegetation characteristics at three times with different rabbit populations: moderate, high and none. Plant species cover data from long-term monitoring sites were also used to obtain spatial data. Spectral vegetation indices derived from satellite imagery provided a wider geographic picture of change covering the transition from high rabbit numbers to no rabbits. In high elevation feldmark vegetation, where rabbit impacts were minor, there was little to no change over 34 years. Tussock grass and megaherb vegetation severely impacted by rabbits shifted to short grassland and herbfield communities, a process that was partially reversed between 2009 and 2014. The spectral data proved to be of limited use in detecting vegetation change compared to the rephotography and plot data.


Nick Fitzgerald is a PhD candidate with interests in plant ecology, vegetation dynamics and spatial analysis who is presently studying the vegetation of subantarctic Macquarie Island

Assessing the effect of land use transition, climate and vegetation anomalies on fire and encroaching species distribution in mountainous grassland

Dr Kayode Adepoju1, Dr Samuel Adelabu1

1University of The Free State, Phuthadijthaba, South Africa


Fire disturbance and recovery exert a strong influence on distributions and future spread pattern of encroaching species. Encroaching species and fire disturbance are likely to increasing in distribution and intensity due to climate change. However, it is uncertain whether the relationship between fire and encroaching species will converge or diverge under varying degrees of combined socio-ecological disturbance situation.  In this study, we applied random forest machine learning and Maxent species distribution modelling algorithms to estimate the distribution of fire and Serethium Plimosum  – an encroaching species, based on remote sensing and meteorological variables in mountainous grassland of South Africa.  To further understand the effect  and uncertainty of socio-ecological systems we (1) used landuse transition matrix, trends and anomaly in climate and vegetation datasets to determine preceding socio-ecological conditions leading to current fire and species distribution patterns (2) explored the effect of these variables on future distribution of fire and encroaching species in mountainous grassland of South Africa. We propose that the result of this study may contribute to a better understanding of the relationship between socio-ecological drivers of drought and fire across multiple years under global change.


Dr. Adepoju is a Postdoctoral Research Fellow in the Department of Geography,  University of the Free State, South Africa. He has a Ph.D. degree in Ecology and Environmental Science and he has worked as a geospatial data scientist with regional government and academia, specializing in the design and implementation of early warning decision support systems for food security and disaster management in the Sahel region. His main research interest is on the integration of stochastic conceptual models using machine learning approaches with system dynamical models for ecological risk assessments with a view to providing complementary insights for environmental conservation

Time series of crustal motion using GNSS: Exploring the expression of systematic errors

Mr Nathaniel Young1, Dr Christopher Watson1

1University Of Tasmania, Sandy Bay, Australia


Time series of site positions determined using Global Navigation Satellite Systems (GNSS) have revolutionised the understanding of geophysical phenomena such as plate motion, earthquake deformation and crustal responses to mass loading and unloading.  As GNSS enters an era of modernisation with increasing accuracy and precision, it is vital that any potential systematic errors are understood to avoid misinterpretation of the underlying geophysical processes. This is particularly the case for understanding subtle rates of change (e.g. Glacial Isostatic Adjustment) or when interpreting quasi-periodic signals (e.g. understanding water mass transfer into and away from a continent). Geophysical interpretation of data acquired from Continuously Operating Reference Stations (CORS) first requires station locations to be parameterised and estimated, prior to undertaking time series analysis of estimated daily coordinates. Here, as part of a longer-term study to investigate systematic error propagation, we use a series of case study sites to investigate potential sources of systematic errors related to site infrastructure changes and identify their potential impact on geophysical interpretation. We review the potential sources and proxies that may induce or aid in the identification systematic error. We then investigate the impact and highlight the importance of site changes on time-series their subsequent geophysical interpretation.


Nathaniel is a Master student, with a focus on geodesy.  He enjoys applying GNSS and InSAR technologies to the evolution of the solid Earth over time.

Christopher Watson is a senior lecturer in Geodesy at the University of Tasmania. His research interests are focused on the use of space geodetic techniques such as satellite altimetry and GNSS applied to global climate change, sea-level and earth deformation studies.

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