At the Barbara Hardy Institute, much of our research focuses on how humans utilise the landscape in diverse ways.
From heavily industrialised cities and their surrounds, to tracts of infrequently visited wilderness, we influence the landscape around the globe. Importantly, the way in which we use the landscape varies over both space and time.
Over space we see changes that we can map, like the locations of cities, forests, farms, mineral deposits, and rainfall catchments. On a finer scale, within cities, we can see patterns of built structures like houses, high-rises, towers, industrial areas, and pavements, with waterways and waterbodies both natural and built, and pockets of vegetation in parks, along roads, and in backyards.
Over time we can also see change. We can use these observations to model the impacts of the change. Change occurs rapidly around cities due to their increasing populations and, with increasing affluence, residents' rising demands for goods.
A good example of changing land use, visible to people in Adelaide, is the quarry scars on the Adelaide hills face zone. Much of the building resources required for development of the city in the 19th and 20th centuries were taken from these quarries to allow the city's growth. These 'scars' are visible from most parts of the Adelaide plains, from the air and from satellites observing our Earth.
Mapping and modelling landscapes
A variety of technologies are used that enable us to map geographical distributions of landscape features and uses:
Remote sensing and photogrammetry use images from satellite sensors and aerial cameras, useful in monitoring large areas, and able to detect many wavelengths of light.
Geographic Information Systems (GIS) use computers to assist in the collection, storage, access, and analysis of maps and other spatial information.
Global Positioning Systems (GPS) make use of multiple satellites to determine precise locations on earth, as well as the speed and direction of travel.
Using spatial analysis and computer modelling we can predict future change and impacts. These techniques are not limited to landscape analysis, and can also be used for monitoring and analysis of animal populations, soil salinisation and other forms of land degradation, rural or urban rainfall catchments, human population distributions, and potential hazards.
Early detection of vegetation degradation
Using spatial technologies, vegetation distribution can be observed in urban, peri-urban, and agricultural areas. Changes over space and time can be monitored for both the distribution of vegetation and its health. Remote sensing can help assess the health of vegetation by revealing comparative water and chlorophyll content. For example, it can be discerned that the health of eucalypt trees in urban areas decreases with an increase of paved area around them.
Multi-criteria decision making in urban and peri-urban planning
Using multiple criteria, both spatial and non-spatial, can assist in urban planning. For example, the decision on the location of a new urban road, or the upgrading of an existing road, can be influenced by car traffic flows, walking and cycling routes, water courses, biodiversity corridors, the location of services, and the potential for community social interaction. Each criterion can be considered, and a level of importance can be assigned to it. The use of computers is essential to present the information effectively and aid in the decision making process.
Multi-criteria decision making can help in land management and the planning of land use changes in peri-urban areas, especially where there are conflicting development pressures. For example, in areas around Adelaide, including the Clare Valley and the Southern Vales, there are residential development pressures on viticultural lands. Computer modelling can be used to describe the current situation, and prescribe or predict scenarios of land use. These scenarios can be based on sound land evaluation practices that include physical and economic criteria of land suitability. Spatial models (maps) of alternative land use scenarios can be produced using GIS integrated with traditional techniques of multi-criteria and multi-objective decision making.
Land use patterns and planning
It is important to maximise landscape use to reduce the extent of human impacts on the earth. We cannot maintain a growing population and the health of natural systems without optimising land use. Using spatial technologies and techniques, such as Geographic Information Systems (GIS), we can choose appropriate land use activities for urban development, food or fibre production, resource extraction, or protection of the natural environment. For example, information on climate, soils, topography, hydrology, and ecology would help in siting new vineyards. Such applications can also be used in precision agriculture, to maximise the use of land, water, seed, fertiliser, and human resources. In the urban environment the amount of paved surfaces humans create has a direct impact on water runoff into streams and storm water networks. Spatial technologies serve an important role in documenting where and how much to such paved surfaces exists and feed results into water management models and into biodiversity models.
Remote sensing and photogrammetry
- Optical and infrared multispectral and panchromatic (Landsat, SPOT, ALOS-PRISM, Terra ASTER, Quickbird, Ikonos, Cartosat, IRS-1 C/D; Hyperion)
- Microwave: airborne (InSAR) and satellite-borne ERS, ALOS-PALSAR, Envisat, Radarsat
- Hyperspectral (HYMAP) and Hyperion
- LIDAR (Rigel-ARA)
- Airborne Digital Multispectral Imagery (DMSI-Specterra Services Pty Ltd)
- Image Processing Software: Leica Geosystems (Imagine)
Geographic Information Systems (GIS)
- Idrisi Andes
Global Positioning Systems (GPS)
- High precision
Advanced digital image processing
- Object oriented
- Fuzzy logic
- Neural networks
- Multi-sensor image fusion
- Knowledge and rule-based systems
- Spectral indices
- Cartographic modelling
- Fuzzy logic
- Spatio-temporal models
- Point pattern analysis
- Network analysis
- Terrain analysis
- Raster analysis
GIS-based decision making
- Models of spatial planning for sustainable development
For further information please contact David Bruce.