This $4.5m project successfully surveyed1,610 transects in the 23 river catchments of the Murray Darling Basin and used the data to develop an objective and repeatable measure of the health of the rivers of the agricultural heartland of Australia.
The Murray Darling Basin covers one million square kilometres and includes more than 85,000 kilometres of rivers. Sampling the health of such an extensive network of rivers in the field would exceed the capacity of Australia’s field biologists and geomorphologists. Terranean in close consultation with the Murray Darling Basin Authority (MDBA) developed and implemented a completely new approach of using High Definition LiDAR to measure detailed stream and vegetation statisics. These, in turn were processed by innovative GIS modeling routines to develop detailed environmental and ecological information about the rivers in a period of less than 12 months.
This ambitious project successfully utilised new spatial technologies and developed and used innovative GIS modeling techniques to cost effectively and scientifically measure the health of the Basin’s rivers. It is a clear demonstration of the spatial information industry helping to secure Australia’s environmental and economic security.
The Murray Darling Basin supports over one third of Australia’s total gross value of agricultural production and three quarters of Australia’s irrigated crops and pastures are grown in the Basin. The future of the economies and populations that are supported by this agriculture depend on the sustainable management of the Basin’s rivers and land systems. This project provides vital information for monitoring the health of the Basin’s rivers, assessing the impact of different land use and water usage and the effectiveness of programs for the amelioration of environmental degradation. Without the innovative application of the latest spatial technologies to this problem, the information would not be available to develop, implement and monitor a Basin Management Plan.
The project represents a new methodology for geomorphologic assessment. Previously this could only be performed by experienced geomophologists in the field because 1) remotely sensed data types was not able to provide sufficiently detailed and accurate three dimensional representations of river channels and 2) methods for measuring and characterising the physical form of river channels from high resolution DEMs had not been developed. This project was overseen by a technical advisory panel that included experts on fluvial geomorphology. The project showed that high definition full waveform LiDAR resolves river channels to a level that enables detailed geomorphologic assessment and characterisation. The concepts developed by the geomorphologic experts on the technical advisory panel were implemented by Terranean as geospatial algorithms. Together these open up a new field of geomorphology by remote sensing that has the potential to enable cost effective mapping of fluvial systems at unprecedented levels of detail.
The project measured complex environmental variables over a large area in an objective and repeatable way. It did this by solving 3 core problems using new spatial technologies. The first problem to overcome was to measure the precise shape of the river channels and the distribution of foliage in three dimensions using an objective and repeatable method that minimises the introduction of bias caused by human interpretation and measurement. The task would be impossible or at least highly impractical using traditional field survey methods. The solution was to use high density, full wave form LiDAR scanning 4 laser pulses per square metre, returning up to 20 echoes per metre in complex vegetation.
The second problem was to extract geomorphic variables that could be statistically analysed, from the high resolution LiDAR DEMs. This involved the development of geospatial tools using the TNTmips geospatial programming language to automatically define the top bank and bottom bank lines. At each site nineteen transects were randomly generated across the river channel. Twenty-five geomorphologic measurements were taken for each transect, representing variables such as channel width, channel depth and cross sectional area of the channel.
The third problem was to derive a set of vegetation metrics that could be statistically analysed to help determine the health of the river at that site. Spatial algorithms were developed using TNTmips that generated eighteen vegetation measurements for specified zones in and adjacent to the river channel. The measurements represent attributes such as vegetation height, shading (of the river channel) and foliage density within a range of strata.
The methods developed for measuring vegetation have potential applications in a wide range of natural resource projects. The project shows that high definition LiDAR, in conjunction with suitable algorithms for extracting variables can be used to enable baseline assessment and ongoing monitoring of processes such as soil erosion, salination and changes in site quality and vegetation cover. The principles and methods developed have a wide range of potential applications including monitoring of site rehabilitation and carbon accounting.
Full waveform, high definition LiDAR provides a means for remotely measuring the ground surface and above ground features such as vegetation to an unprecedented level of resolution. Automating the extraction of information from this dense data is a priority of spatial technology research. This project demonstrates the potential for developing innovative solutions for environmental monitoring and natural resource management. The project demonstrated a method for acquiring detailed information that would be impossible to obtain by field survey using experienced biologists and geomorphologists.
This competitive tender was let by the Queensland Department of Infrastructure and Planning, on behalf of the Environmental Protection Agency (EPA)to carry out a LiDAR survey to produce a highly detailed Digital Elevation Model (DEM) and contours of a section of potential new national Park in South East Queensland. The EPA needed mapping of this level of detail so they could plan the implementation of the new National Park and monitor the possible effects of climate change over this low lying coastal land.
The EPA required 0.2 meter contours over the 64 sq km area to understand even the most subtle of the drainage dynamics of the project area. The area is covered by a variety of land types including dense littoral forest, sand dunes and mud flats.
The key to a good result were high accuracy and good penetration of the vegetation to achieve a high number of points on the ground. As illustrated in the diagrams below, the LiDAR scans achieved excellent penetration through the thick vegetation with no discernable difference in DEM quality between the vegetated and non-vegetated areas. Checking of the control indicated an absolute accuracy of approximately 10 cm and a relative accuracy of a very high 15mm were achieved.
The project was successfully delivered with the EPA receiving an accurate and reliable DEM on which they can base their assessment, planning and future monitoring.
Land Cover Mapping over South East Queensland
Believe it or not, up until now there has been no up to date map of "Land Cover" over the fastest growing area in Australia, South East Queensland. Land Cover shows what is actually on the ground. For example, the extent of urbanisation, the extent of agricultural land and the extent of forests - all essential information for planners trying to grapple with the rapid changes occuring in SE Queensland.
Terranean was contracted by NRM group, SEQ Catchments, to carry out this satellite imagery value-add work. SEQ Catchments has made the large investment to create a seamless 2.5m colour SPOT mosaic over SE Qld. However, while this data is very useful is little more than a picture. Terranean used sophisticated techniques to combine this data with other geographic information to produce an accurate and up to date Land Cover map over the whole region.
Terranean developed a new innovative approach to what has previously been a labour intensive and subjective task. In summary, we used statistical image analysis techniques to map four Primary Classes - Trees, Non-Tree Vegetation, Non-Vegetated Surfaces and Water. We then developed complex GIS rules that sub-divided the Primary Classes into Secondary Classes using externally sourced spatial information such as Landuse, Zoning, Forestry, Agriculture and Vegetation. For example the Primary class, Trees, was allocated to secondary classes Plantation, Orchard or Native Vegetation depending on Landuse and Vegetation type.
Terranean is one of the few private companies in Australia that specialises in value adding Satellite Imagery and we are presently carrying out similar projects for other NRM groups, Government Departments and private companies.
US Army Corps of Engineers
Arkansas River Mapping Project
The Arkansas River is one of the most important rivers, historically and economically, in the US. Over 2300 kilometres in length, it is the longest tributary in the Missouri-Mississippi system and is the 4th longest river in the US. The Oklahoma and Arkansas River reaches are of particular importance as they play a vital role in barge traffic and recreation.
The US Army Corps of Engineers (COE) is charged with a number of environmental, flood management, and river navigation responsibilities for the Arkansas River. In order to fulfil these responsibilities, the COE requires accurate and reliable digital elevation data for the Arkansas River and surrounding areas.
The challenge for this project was to produce a dataset of accurate height points at 5-metre intervals across the entire project area, covering 1500 square kilometres along a 500-kilometre length of the river.
Terranean’s advanced digital photogrammetry systems were used for the project. These leading-edge computer mapping systems use scanned, overlapping, aerial photographs to view and measure terrain in three dimensions. Terranean processed 2800 frames of aerial photography using this technique, in order to provide digital data to the required standard.
Throughout the course of the project, Terranean encountered and overcame a considerable number of technical challenges. Several thousand gigabytes of data had to be effectively stored and managed. Undertaking final quality assurance for the enormous volumes of data created a significant production bottleneck, which was overcome by using specially developed automated quality assurance routines, operating 24 hours per day. Extensive use of Internet-based file transfer protocol (ftp) for delivery of datasets to the US enabled prompt delivery.
Arkansas River Mapping Project project took 12 months to complete and was completed on budget, one week ahead of schedule on 31 May 2004. During the course of the project, digital elevation data comprising over 60 million height points was produced to the client’s strict quality standards. Export income of AUD$260,000 was earned by Terranean on this project.
What are Forest Agreements?
Allocating forest areas to the most appropriate uses provides certainty for the timber industry, and ensures that all forest types are adequately protected. In order to achieve this ideal, the NSW Government initiated the Regional Forest Assessments to objectively assess the conservation value, as well as the economic and social value of its forests. An integral part of this process was the accurate mapping and compilation of detailed forest inventory data over all State Forests in NSW.
Terranean Mapping Technologies demonstrated superior skills in air photo interpretation (API), vegetation mapping, and GIS development, which were necessary to carry out this exacting and politically sensitive project.
The work involved developing a production process that included API, ortho-rectification, and geo-referencing the API polygons. Large amounts of data were then merged and edited. Specific software was developed to automatically ortho-rectify the digitized vector information without changing the aerial photographic images.
Because Terranean’s unique range of skills, it became the key contractor for this large and prestigious project. Terranean developed more than $300,000 worth of environmental forest inventory data from more than 4000 aerial photographs, and compiled the final data for each region.
Scenic Amenity Modelling
Caboolture Shire is one of South East Queensland’s primary growth areas, and contains some of Queensland’s most impressive scenery, including part of the Glass House Mountains. As a relatively underdeveloped shire, Caboolture needs to accommodate rapid development while maintaining its unique semi-rural lifestyle and landscapes.
Caboolture Shire needed assistance with deciding where to locate development, while minimising damage to the landscape, a sustainable tourism industry, and quality of life. Specifically, it needed to identify, on a Council-wide basis, areas regarded by the community as precious and worth preserving.
Terranean Mapping Technologies, in association with Forest Images and the Queensland Environmental Protection Agency, developed a process called Scenic Amenity Modelling. Terranean and Forest Images were chosen by Caboolture Shire to carry out this modelling work.
The first stage of the process involved a survey of public opinion using photographs of different landscapes in the area, such as forest, pasture, residential, industrial etc. The results of the survey were statistically analysed to produce a model that can be applied to a land-cover map within a GIS. A Scenic Preference map showing community appreciation for different types of landscape then was created.
The next step involved mapping Visual Exposure across the landscape, relative to a set of viewing locations including roads, trails, tourist attractions, community facilities, lookouts etc. Previous models for mapping Visual Exposure simply counted the number of viewing locations that could be seen from each point in the landscape, without taking into account distance, orientation (slope and aspect), the intervening vegetation, and number of viewers. Visual Exposure was calculated from a DEM and a set of viewing locations.
The final step involved combining Scenic Preference and Visual Exposure in order to produce a map of Scenic Amenity. Scenic Amenity was calculated so that highly visible, preferred landscapes were given the highest score, while the high visibility least preferred landscapes were given the lowest score. Areas with low visibility have intermediate Scenic Amenity.
Caboolture Shire was extremely happy with the work, which has become a key council-planning tool. The project won two Planning Institute of Australia Awards for Excellence, in the Media and Environmental Planning categories.The methodology has also been endorsed by the South East Queensland Regional Organisation of Councils (SEQROC) as the preferred method for assessing Scenic Amenity. Terranean and Forest Images also have applied the methodology in projects for the Ipswich and Brisbane City Councils, and the Lockyer Valley, as well as the South East Queensland regional plan.
Australian National University
Aerial photography and Satellite Remote Sensing data can be valuable for mapping vegetation; however, it is relatively insensitive to subtle differences in species composition and requires significant ground truthing for reliable results. The Australian National University needed a way of increasing the probability of prediction of vegetation communities, without generating excessive extra cost.
GIS is a powerful tool for environmental data analysis and predictive modelling. Previously, it had been shown that the distribution of plant species and communities were determined by the interactions illustrated above.
On the basis of these relationships, a new and innovative procedure was developed to map vegetation communities using a combination of GIS and artificial intelligence. The methodology was tested on an area of forest where the vegetation communities had previously been identified by classification of floristic survey data.
The range of physical variables, thought to influence the distribution of vegetation communities, was derived from readily available mapping data. The variables included topographic exposure, slope, aspect, catchment area, steepness, and geology. A combination of GIS modelling and Decision Tree Analysis was used to classify the study area into environments that were likely to support different forest communities.
The resulting map predicted the distribution of forest communities with an exceptional accuracy of approximately 85%, and was recognised as a great improvement on remote sensing alone. Since then, the methodology has been used in a range of projects for mapping ecological distributions.
The Panguna mine in Bougainville is well known because of the actions of Francis Ona and his followers, which led to the closure of the mine because of concerns about environmental and economic exploitation. Mining began in 1968 and the mine grew to a width of 2.5 km and a depth of 400 m, making it the largest mine in Papua New Guinea, and one of the largest open-cut mines in the world. As part of their ongoing obligation to the project, CRA Bougainville Ltd resolved to objectively assess the extent of change caused to the Jaba River during, and subsequent to, the operation of the mine.
Terranean Mapping Solutions was engaged to carry out GIS and remote sensing analysis, in order to accurately quantify, through remote sensing, the extent of hydrological and catchment sedimentation,along the Jaba River.
Topographic maps, derived from 1973 photography, were digitised and compared with data derived from 1984 Aerial Photography, 1989 and 1990 Landsat images, and 1996 RADARSAT imagery. Remote Sensing and GIS modelling techniques were used to accurately quantify changes in sedimentary and hydrological processes during a 30-year period.
The project succeeded in developing a quantifiable, repeatable method of assessing the sedimentation, vegetation cover, and hydrological processes of the Jaba River and its catchment.