Cantilever extension of ground control in strips of convergent photographs by analytical triangulation.

"Contract no. DA-44-009 Eng-2986, Department of the Army Project no. 8-35-11-106."

A solution of the general analytical aerotriangulation problem.

"Contract no. DA-44-009 Eng 2986, Department of the Army Project no. 8-35-11-101."

Annual earth resources program review.

Mode of access: Internet.

A simple method of surveying from air photographs,

(Gt. Brit. Air survey committee. Professional papers, no. 8 Supplement)

ABC's of photogrammetry.

Errata sheet inserted in each part.

Automated digital mosaicking of airborne videography /

"FHTET 96-12."

Study, MTMS, stereo input

Cover title.

Elements of photogrammetry.

Mode of access: Internet.

How the west was once: vegetation change in south-west Queensland from 1930 to 1995

Conflicting perceptions of past and present rangeland condition and limited historical data have led to debate regarding the management of vegetation in pastoral landscapes both internationally and in Australia. In light of this controversy we have sought to provide empirical evidence to determine the trajectory of vegetational change in a semi-arid rangeland for a significant portion of the 20th century using a suite of proxy measures. Ambathala Station, approximately 780 km west of Brisbane, in the semi-arid rangelands of south-western Queensland, Australia. We excavated stratified deposits of sheep manure which had accumulated beneath a shearing shed between the years 1930 and 1995. Multi-proxy data, including pollen and leaf cuticle analyses and analysis of historical aerial photography were coupled with a fine resolution radiocarbon chronology to generate a near annual history of vegetation on the property and local area. Aerial photography indicates that minor (< 5%) increases in the density of woody vegetation took place between 1951 and 1994 in two thirds of the study area not subjected to clearing. Areas that were selectively or entirely cleared prior to the 1950s (approximately 16% of the study area) had recovered to almost 60% of their original cover by the 1994 photo period. This slight thickening is only partially evident from pollen and leaf cuticle analyses of sheep faeces. Very little change in vegetation is revealed over the nearly 65 years based on the relative abundances of pollen taxonomic groups. Microhistological examination of sheep faeces provides evidence of dramatic changes in sheep diet. The majority of dietary changes are associated with climatic events of sustained above-average rainfall or persistent drought. Most notable in the dietary analysis is the absence of grass during the first two decades of the record. In contrast to prevailing perceptions and limited research into long-term vegetation change in the semi-arid areas of eastern Australia, the record of vegetation change at the Ambathala shearing shed indicates only a minor increase in woody vegetation cover and no decrease in grass cover on the property over the 65 years of pastoral activity covered by the study. However, there are marked changes in the abundance of grass cuticles in sheep faeces. The appearance and persistence of grass in sheep diets from the late 1940s can be attributed to the effects of periods of high rainfall and possibly some clearing and thinning of vegetation. Lower stock numbers may have allowed grass to persist through later drought years. The relative abundances of major groups of plant pollen have not changed significantly over the past 65 years.

Recent developments on a nearshore, terrigenous-influenced reef: Low Isles Reef, Australia

Low Isles Reef is the most southerly located of 46 coral reef platforms unique to the inner shelf of the northern Great Barrier Reef Province, Australia, which support both sea grass and mangrove growth. Such reefs develop in areas that are influenced by river flood plumes and where interreef sediments are dominated by terrigenous mud. Low Isles Reef has long been a popular tourist destination. Informal reports of decreasing visibility, a decline in scleractinian corals, and increases in soft coral and macroalgae have sparked speculation that agricultural activities in coastal catchments are affecting the reef. Comparison of the modern surface of Low Isles Reef with historical surveys and photographs dating back to 1928 allows quantification of modern sedimentary processes, rates of change, and factors influencing reef development. Results indicate that changes on Low Isles Reef are related to remobilization of coarse sediment during storm events and gradual shoreline retreat associated with rising sea level. Retreat of shingle ramparts and elongate ridges of coral debris toward the reef interior has led to the infilling of subtidal ponds on the reef top, which supported hard coral colonies in 1928. The gradual development of a composite shingle rampart along the windward margin has promoted an increase (;150%) in the area of the reef top covered by mangroves. On the leeward margin, a decrease in hard corals since 1950 may reflect a rising contribution of organic debris from the expanding mangrove swamp. Results suggest that recent changes on Low Isles Reef can be explained in the context of natural processes. Further study is needed before the effects of agricultural activities in coastal catchments on reef health can be confirmed.

Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

The geometric correction and registration of airborne line-scanned imagery for temporal thermal studies

This thesis begins by providing a review of techniques for interpreting the thermal response at the earth's surface acquired using remote sensing technology. Historic limitations in the precision with which imagery acquired from airborne platforms can be geometrically corrected and co-registered has meant that relatively little work has been carried out examining the diurnal variation of surface temperature over wide regions. Although emerging remote sensing systems provide the potential to register temporal image data within satisfactory levels of accuracy, this technology is still not widely available and does not address the issue of historic data sets which cannot be rectified using conventional parametric approaches. In overcoming these problems, the second part of this thesis describes the development of an alternative approach for rectifying airborne line-scanned imagery. The underlying assumption that scan lines within the imagery are straight greatly reduces the number of ground control points required to describe the image geometry. Furthermore, the use of pattern matching procedures to identify geometric disparities between raw line-scanned imagery and corresponding aerial photography enables the correction procedure to be almost fully automated. By reconstructing the raw image data on a truly line-by-line basis, it is possible to register the airborne line-scanned imagery to the aerial photography with an average accuracy of better than one pixel. Providing corresponding aerial photography is available, this approach can be applied in the absence of platform altitude information allowing multi-temporal data sets to be corrected and registered.

The application of remote sensing to the management of urban wildlife habitats

The project set out with two main aims. The first aim was to determine whether large scale multispectral aerial photography could be used to successfully survey and monitor urban wildlife habitats. The second objective was to investigate whether this data source could be used to predict population numbers of selected species expected to be found in a particular habitat type. Panchromatic, colour and colour infra-red, 1:2500 scale aerial photographs, taken in 1981 and 1984, were used. For the orderly extraction of information from the imagery, an urban wildlife habitat classification was devised. This was based on classifications already in use in urban environments by the Nature Conservancy Council. Pilot tests identified that the colour infra-red imagery provided the most accurate results about urban wildlife habitats in the study area of the Blackbrook Valley, Dudley. Both the 1981 and 1984 colour infra-red photographs were analysed and information was obtained about the type, extent and distribution of habitats. In order to investigate whether large scale aerial photographs could be used to predict likely animal population numbers in urban environments, it was decided to limit the investigation to the possible prediction of bird population numbers in Saltwells Local Nature Reserve. A good deal of research has already been completed into the development of models to predict breeding bird population numbers in woodland habitats. These models were analysed to determine whether they could be used successfully with data extracted from the aerial photographs. The projects concluded that 1:2500 scale colour infra-red photographs can provide very useful and very detailed information about the wildlife habitats in an urban area. Such imagery can also provide habitat area data to be used with population predictive models of woodland breeding birds. Using the aerial photographs, further investigations into the relationship between area of habitat and the breeding of individual bird species were inconclusive and need further research.

A framework for automatic feature extraction from airborne light detection and ranging data

Recent advances in airborne Light Detection and Ranging (LIDAR) technology allow rapid and inexpensive measurements of topography over large areas. Airborne LIDAR systems usually return a 3-dimensional cloud of point measurements from reflective objects scanned by the laser beneath the flight path. This technology is becoming a primary method for extracting information of different kinds of geometrical objects, such as high-resolution digital terrain models (DTMs), buildings and trees, etc. In the past decade, LIDAR gets more and more interest from researchers in the field of remote sensing and GIS. Compared to the traditional data sources, such as aerial photography and satellite images, LIDAR measurements are not influenced by sun shadow and relief displacement. However, voluminous data pose a new challenge for automated extraction the geometrical information from LIDAR measurements because many raster image processing techniques cannot be directly applied to irregularly spaced LIDAR points. ^ In this dissertation, a framework is proposed to filter out information about different kinds of geometrical objects, such as terrain and buildings from LIDAR automatically. They are essential to numerous applications such as flood modeling, landslide prediction and hurricane animation. The framework consists of several intuitive algorithms. Firstly, a progressive morphological filter was developed to detect non-ground LIDAR measurements. By gradually increasing the window size and elevation difference threshold of the filter, the measurements of vehicles, vegetation, and buildings are removed, while ground data are preserved. Then, building measurements are identified from no-ground measurements using a region growing algorithm based on the plane-fitting technique. Raw footprints for segmented building measurements are derived by connecting boundary points and are further simplified and adjusted by several proposed operations to remove noise, which is caused by irregularly spaced LIDAR measurements. To reconstruct 3D building models, the raw 2D topology of each building is first extracted and then further adjusted. Since the adjusting operations for simple building models do not work well on 2D topology, 2D snake algorithm is proposed to adjust 2D topology. The 2D snake algorithm consists of newly defined energy functions for topology adjusting and a linear algorithm to find the minimal energy value of 2D snake problems. Data sets from urbanized areas including large institutional, commercial, and small residential buildings were employed to test the proposed framework. The results demonstrated that the proposed framework achieves a very good performance. ^

2003 Habitat Maps derived from Grey Nurse Shark (GNS) Project of Wolf Rock, Double Island Point, Queensland, Australia

Surveying habitats critical to the survival of grey nurse sharks in South-East Queensland has mapped critical habitats, gathered species inventories and developed protocols for ecological monitoring of critical habitats in southern Queensland. This information has assisted stakeholders with habitat definition and effective management. In 2002 members of UniDive applied successfully for World Wide Fund for Nature, Threatened Species Network funds to map the critical Grey Nurse Shark Habitats in south east Queensland. UniDive members used the funding to survey, from the boats of local dive operators, Wolf Rock at Double Island Point, Gotham, Cherub's Cave, Henderson's Rock and China Wall at North Moreton and Flat Rock at Point Look Out during 2002 and 2003. These sites are situated along the south east Queensland coast and are known to be key Grey Nurse Shark aggregation sites. During the project UniDive members were trained in mapping and survey techniques that include identification of fish, invertebrates and substrate types. Training was conducted by experts from the University of Queensland (Centre of Marine Studies, Biophysical Remote Sensing) and the Queensland Parks and Wildlife Service who are also UniDive members. The monitoring methods (see methods) are based upon results of the UniDive Coastcare project from 2002, the international established Reef Check program and research conducted by Biophysical Remote Sensing and the Centre of Marine Studies. Habitats were mapped using a combination of towed GPS photo transects, aerial photography, bathymetry surveys and expert knowledge. This data provides georeferenced information regarding the major features of each of Sites mapped including Wolf Rock