Evaluation of aerial remote sensing techniques for defining critical geologic features pertinent to tunnel location and design /

Mode of access: Internet.

Accidents in Aerial Application Activities

Title Varies: Aerial Crop Control Accidents

The Power of the Palestinian Landscape : An exploratory study of the functions of power using aerial image interpretation

The Palestinian region is changing rapidly, with both economic and cultural consequences. One way of approaching this very political process is thru the concept of landscape. By viewing the region as a multiprocessual, dynamic landscape the analysis allows for a holistic read where historical and contemporary projections, interpretations and notions of power are fused. This thesis draws on the scholarly fields of humanistic landscape research and aerial image interpretation as well as theories of orientalism and power. A case study of two regions of the West Bank is performed; interviews and observations provide localized knowledge that is then used in open-access image interpretation. By performing image interpretations this thesis explores the power embedded in mapping and the possible inclinations the development towards open-access geospatial analytic tools could have on the functions of power in the Palestinian landscape. By investigating the spatial configuration of the Palestinian landscape and tracing its roots this thesis finds four major themes that are particularly pivotal in the processual change of the Palestinian landscape: the Israeli/Palestinian time-space, the blurring of the conflict, the dynamics of the frontier region and the orientalist gaze. 

Observations of Joints Present in the Lawton Clay Member of the Vashon Stade, Exposed at a Coastal Bluff in Discovery Park, Seattle, Washington

The southwest-facing coastal bluff present at Discovery Park, Seattle, Washington, displays distinctive joints throughout the exposed Lawton Clay Member. Exhibiting a characteristic local stratigraphy of permeable advance outwash over the impermeable proglacial lacustrine clay, this bluff is located in an area of Seattle at high risk from landslides. This project addressed the relationship between the joints observed at this coastal bluff and the coherency of the bluff as a whole, through remote sensing and field measurements. Aerial drone photography taken of the bluff was processed through a photogrammetry software to produce a 3-dimensional Structure from Motion model, allowing for a digital manipulation and broad examination of the bluff not possible by foot. Stereonet plots produced from these measurements provided insight into patterns of varying joint strike along a horizontal transect of the observed bluff face. Taken together, these two visualizations provided a better picture of the possible chicken-and-egg interaction of the joints and bluff topography; they demonstrated the likelihood that the joint formation at the bluff was most likely to be primarily influenced by the local topography of the bluff over other sources of possible tensional stress in the immediate area.

A Novel Framework for Real-time Traffic Flow Parameter Estimation from Aerial Videos

Thesis (Master's)--University of Washington, 2016-06

Mapping and characterising subtropical estuarine landscapes using aerial photography and GIS for potential application in wildlife conservation and management

Coarse-resolution thematic maps derived from remotely sensed data and implemented in GIS play an important role in coastal and marine conservation, research and management. Here, we describe an approach for fine-resolution mapping of land-cover types using aerial photography and ancillary GIs and ground data in a large (100 x 35 km) subtropical estuarine system (Moreton Bay, Queensland, Australia). We have developed and implemented a classification scheme representing 24 coastal (subtidal, intertidal. mangrove, supratidal and terrestrial) cover types relevant to the ecology of estuarine animals, nekton and shorebirds. The accuracy of classifications of the intertidal and subtidal cover types, as indicated by the agreement between the mapped (predicted) and reference (ground) data, was 77-88%, depending on the zone and level of generalization required. The variability and spatial distribution of habitat mosaics (landscape types) across the mapped environment were assessed using K-means clustering and validated with Classification and Regression Tree models. Seven broad landscape types could be distinguished and ways of incorporating the information on landscape composition into site-specific conservation and field research are discussed. This research illustrates the importance and potential applications of fine-resolution mapping for conservation and management of estuarine habitats and their terrestrial and aquatic wildlife. (c) 2005 Elsevier Ltd. All rights reserved.

Integrating JERS-1 imaging radar and elevation models for mapping tropical rainforest communities in far North Queensland, Australia

The Wet Tropics World Heritage Area in Far North Queens- land, Australia consists predominantly of tropical rainforest and wet sclerophyll forest in areas of variable relief. Previous maps of vegetation communities in the area were produced by a labor-intensive combination of field survey and air-photo interpretation. Thus,. the aim of this work was to develop a new vegetation mapping method based on imaging radar that incorporates topographical corrections, which could be repeated frequently, and which would reduce the need for detailed field assessments and associated costs. The method employed G topographic correction and mapping procedure that was developed to enable vegetation structural classes to be mapped from satellite imaging radar. Eight JERS-1 scenes covering the Wet Tropics area for 1996 were acquired from NASDA under the auspices of the Global Rainforest Mapping Project. JERS scenes were geometrically corrected for topographic distortion using an 80 m DEM and a combination of polynomial warping and radar viewing geometry modeling. An image mosaic was created to cover the Wet Tropics region, and a new technique for image smoothing was applied to the JERS texture bonds and DEM before a Maximum Likelihood classification was applied to identify major land-cover and vegetation communities. Despite these efforts, dominant vegetation community classes could only be classified to low levels of accuracy (57.5 percent) which were partly explained by the significantly larger pixel size of the DEM in comparison to the JERS image (12.5 m). In addition, the spatial and floristic detail contained in the classes of the original validation maps were much finer than the JERS classification product was able to distinguish. In comparison to field and aerial photo-based approaches for mapping the vegetation of the Wet Tropics, appropriately corrected SAR data provides a more regional scale, all-weather mapping technique for broader vegetation classes. Further work is required to establish an appropriate combination of imaging radar with elevation data and other environmental surrogates to accurately map vegetation communities across the entire Wet Tropics.

Automatic building detection using the Dempster-Shafer algorithm

An approach and strategy for automatic detection of buildings from aerial images using combined image analysis and interpretation techniques is described in this paper. It is undertaken in several steps. A dense DSM is obtained by stereo image matching and then the results of multi-band classification, the DSM, and Normalized Difference Vegetation Index (NDVI) are used to reveal preliminary building interest areas. From these areas, a shape modeling algorithm has been used to precisely delineate their boundaries. The Dempster-Shafer data fusion technique is then applied to detect buildings from the combination of three data sources by a statistically-based classification. A number of test areas, which include buildings of different sizes, shape, and roof color have been investigated. The tests are encouraging and demonstrate that all processes in this system are important for effective building detection.

Aerial view of Ocean View Farmhouse model, Mount Mee

Cardboard and balsa model as seen from above.

The use of context in the classification of urban aerial imagery

Urban regions present some of the most challenging areas for the remote sensing community. Many different types of land cover have similar spectral responses, making them difficult to distinguish from one another. Traditional per-pixel classification techniques suffer particularly badly because they only use these spectral properties to determine a class, and no other properties of the image, such as context. This project presents the results of the classification of a deeply urban area of Dudley, West Midlands, using 4 methods: Supervised Maximum Likelihood, SMAP, ECHO and Unsupervised Maximum Likelihood. An accuracy assessment method is then developed to allow a fair representation of each procedure and a direct comparison between them. Subsequently, a classification procedure is developed that makes use of the context in the image, though a per-polygon classification. The imagery is broken up into a series of polygons extracted from the Marr-Hildreth zero-crossing edge detector. These polygons are then refined using a region-growing algorithm, and then classified according to the mean class of the fine polygons. The imagery produced by this technique is shown to be of better quality and of a higher accuracy than that of other conventional methods. Further refinements are suggested and examined to improve the aesthetic appearance of the imagery. Finally a comparison with the results produced from a previous study of the James Bridge catchment, in Darleston, West Midlands, is made, showing that the Polygon classified ATM imagery performs significantly better than the Maximum Likelihood classified videography used in the initial study, despite the presence of geometric correction errors.