A 915 MHz wireless IR image transfer system, comprised of an IR-160 Thermal Camera and MDS iNet 900 transceivers, was assessed for image transfer capabilities in different environments. Image transfer through natural and artificial obstructions, the capability of transferring images under urban environments, and an exploration of interference issues associated with RF communication links were investigated in detail. Concrete, wood, various construction materials, and building walls were examined to assess indoor propagation capabilities. Data transmission through random trees, buildings, foliage under various atmospheric conditions is also evaluated for outdoor system capabilities. A maximum free space range for acceptable IR image transferring is determined as 23 miles for line of sight (LOS). Non line of sight (NLOS) urban environment measurements revealed that urban path loss (15-60 dBm) is highly dependent on antenna orientation and obstruction geometry rather than the T-R separation distance.

In the last decade, advances in sensor and computing technology are revolutionary. The latest-generation of hyperspectral and synthetic aperture radar ((SAR) instruments have increased their spectral, spatial, and temporal resolution. Consequently, the data sets collected are increasing rapidly in size and frequency of acquisition. Remote sensing applications are requiring more computing resources for data analysis. High performance computing (HPC) infrastructure such as clusters, distributed networks, grids, clouds and specialized hardware components, have been used to disseminate large volumes of remote sensing data and to accelerate the computational speed in processing raw images and extracting information from remote sensing data. In previous research we have shown that we can improve computational efficiency of a hyperspectral image denoising algorithm by parallelizing the algorithm utilizing a distributed computing grid. In recent years, computational cloud technology is emerging, bringing more flexibility and simplicity for data processing. Hadoop MapReduce is a software framework for distributed commodity computing clusters, allowing parallel processing of massive datasets. In this project, we implement a software application to map forest aboveground biomass (AGB) with normalized difference vegetation indices (NDVI) using Landsat Thematic Mapper’s bands 4 and 5 (ND45). We present observations and experimental results on the performance and the algorithmic complexity of the implementation. There are three research questions answered in this thesis, as follows. 1) How do we implement remote sensing algorithms, such as forest AGB mapping, in a computer cloud environment? 2) What are the requirements to implement distributed processing of remote sensing images using the cloud programming model? 3) What is the performance increase for large area remote sensing image processing in a cloud environment? / Graduate / 0799 / 0984

This thesis analyses the use of remote sensing technologies in efforts that seek to combat wildlife crime in East and Southern Africa. Companies and organisations working on the development of remote sensing technology used for anti-poaching efforts, in the study region, are identified through the creation of a database. The social impacts and risks involved in using these technologies are then outlined by analysing the responses to a research survey from those in the conservation community working with wildlife crime. The species focus is on rhino and elephant poaching, thus, the thesis begins with a background on the legislation surrounding both the hunting and trade of these species. Stockpiling of rhino horn and elephant tusk will be discussed as well as other anti-poaching strategies that do not use remote sensing technology. Three key research questions are then answered: Which remote sensing technologies are in use and what kinds of companies and organisations are mainly working on their development? What are the main risks of using remote sensing technology to specifically target wildlife crime in this region? And can the increased use of remote sensing technologies to combat wildlife crime be regarded as an extension of the militarised approach to conservation? The last question is discussed in relation to existing research on this topic. Considering the findings from this paper, recommendations for further research are then made.

A novel wavelet-based scheme to increase coefficient independence in hyperspectral images is introduced for lossless coding. The proposed regression wavelet analysis (RWA) uses multivariate regression to exploit the relationships among wavelettransformed components. It builds on our previous nonlinear schemes that estimate each coefficient from neighbor coefficients. Specifically, RWA performs a pyramidal estimation in the wavelet domain, thus reducing the statistical relations in the residuals and the energy of the representation compared to existing wavelet-based schemes. We propose three regression models to address the issues concerning estimation accuracy, component scalability, and computational complexity. Other suitable regression models could be devised for other goals. RWA is invertible, it allows a reversible integer implementation, and it does not expand the dynamic range. Experimental results over a wide range of sensors, such as AVIRIS, Hyperion, and Infrared Atmospheric Sounding Interferometer, suggest that RWA outperforms not only principal component analysis and wavelets but also the best and most recent coding standard in remote sensing, CCSDS-123.

The Salish Sea is a ecologically important coastal region located on the southwest part of British Columbia. Optical measurements were taken using a set of hyperspectral radiometers, the SAS Solar Tracker developed by Satlantic. This sensor is installed on the Queen of Oak Bay ferry, that runs between Nanaimo and Vancouver, as part of the Ferry Ocean Colour Observation Systems (FOCOS) project. We developed a computer program to process the raw sensor data and generate remote sensing reflectance (Rrs) values. This performs similar functions to Prosoft, Satlantic’s own software to process the data. However, we added new features such as an additional preprocessing step to filter the data based on longitude, and new meteorological flag testing and wind speed calculations. The system was tested using Pearson correlation to compare our output with the output from Satlantic Prosoft. Testing helped us identify a few issues, such as adding longitude flags to remove data at the start and end of the trip where the sensor could produce inaccurate results if aiming at land instead of water. Another issue was where the SAS Solar Tracker does not update its pointing angle fast enough when the ferry makes sharp turns and could result in inaccurate data. / Graduate

Search strategies have been a central activity within archaeology, varying with the types of questions being addressed, technological tools available, and theoretical proclivity of the investigator. This thesis will test the utility of LiDAR remote sensing and GIS spatial technologies against a phenomenological field methodology. Modeled lands include select areas within Northeast Graham Island, Haida Gwaii, located off the northern Pacific coast of Canada. The time scale in question includes the entire Holocene. A history of the landscape concept is evaluated, fleshing out a decisive working term. An Interdisciplinary Multilogical Framework is devised, linking the two modeling methods with a breadth of information sources on the physical and cultural attributes of landscapes. This dialectic approach culminates in a holistic anthropological practice, and grounds for interpretive analysis of the archaeological record. The role of archaeological predictive modeling in the contemporary socio-political context of heritage management in British Columbia is discussed.

The Composite Infrared Spectrometer (CIRS) instrument onboard the Cassini spacecraft will be used to probe the atmosphere and surface of Saturn's giant moon Titan. This thesis describes an investigation of the capabilities of CIRS as a remote sounding instrument. To enable infrared spectra to be computed, a radiative transfer code has been adapted for Titan's atmosphere. The atmospheric model, including gases and aerosol particles, was refined by comparison of synthetic spectra with results from the IRIS instrument of the Voyager 1 spacecraft. Characteristics of the instrument have been deduced from laboratory measurements. The size and shape of the field of view was found for the mid-infrared detectors. A Fourier code was developed to transform the raw data (interferograms). Blackbody spectra taken with the flight instrument were analysed to calculate the noise equivalent radiance for the detectors of all three focal planes. Finally, the data regarding instrument performance was used in combination with the predictive radiative transfer code to consider in detail the extent to which gaseous bands and other spectral features will be observable for a variety of limb and nadir viewing modes. Current observing strategies are reviewed and recommendations for scientific emphasis in the light of the actual instrument performance are made.

Northeastern forests are being impacted by unprecedented environmental stressors, including acid deposition, invasive pests, and climate change. Forest health monitoring at a landscape scale is necessary to evaluate the changing condition of forest resources and to inform management of forest stressors. Traditional forest health monitoring is often limited to specific sites experiencing catastrophic decline or widespread mortality. Satellite remote sensing can complement these efforts by providing comprehensive forest health assessments over broad regions. Subtle changes in canopy health can be monitored over time by applying spectral vegetation indices to multitemporal satellite imagery. This project used historical archives of Landsat-5 TM imagery and geographic information systems to examine forest health trends in the northern Green Mountains of Vermont from 1984 to 2009. Results indicate that canopy health has remained relatively stable across most of the landscape, although decline was present in localized areas. Significant but weak relationships were discovered between declining forest health and spruce-fir-paper birch forests at high elevations. Possible causes of decline include the interacting effects of acid deposition, windthrow, and stressful growing environments typical of montane forests.

GIS (Geographic Information Systems) and remote sensing techniques were used to predict relationships between bald eagle nest presences and land type, distance to land type and impervious surface cover area. Data plots revealed bald eagle nest presence decreases in response to an increase in area of bareland; increases with an increase in area of forested land; decreases with an increase in distance (m) to shoreline, and decreases in response to an increase in area of impervious surfaces. Logistic regression models identified impervious surfaces as an indicator for bald eagle nest presence (P 24% as unsuitable. Unsuitable area covered 17.82% of the total study area, impacted area covered 13.40%, and, sensitive area covered 68.77%. The projected increase in population in the state of Virginia and subsequent increase in impervious surfaces presents a challenge to the future viability of the Virginia Chesapeake Bay bald eagle population. The threshold analysis identified areas of prime conservation concern for bald eagle nest presence within the defined study area. These areas provide the basis for a conservation management plan and for further scientific study.

The application of high temporal satellite image data for designation of the spectral characteristic of vegetation Abstract The objektive of this paper is to evaluate possibilities of high temporal satellite data assimilation for continuous monitoring of the spectral characteristic of vegetation. There is also given the suggestion of metodology for processing MERIS data and for continuous monitoring of spectral characteristic of landscape objects. Finally, vegetation cover database for the Czech Republic in the year 2009 is created from sectorial analysis. In the paper there is used the LSU classification and thresholding of vegetation indicies histograms. The universal decision algorithm for classification of vegetation landscape component are described and particular thresholding values for the year 2009 given. The finally product of this paper is Czech vegetation cover database for the year 2009 with overall accuracy of 63,35 %. Accuracy for forest is even over 80 %. Keywords: remote sensing, MERIS, vegetation, spectral reflectance, LSU, BEAM