Thesis (M.S. in Applied Science)--Naval Postgraduate School, June 2004. / Thesis advisor(s): Richard Harkins, D. Scott Davis. Includes bibliographical references (p. 61). Also available online.

Thesis (M.S.)--Middle East Technical University, 2003. / Keywords: Remote sensing, alteration mapping, spectral library, Cappadocian Volcanic Province.

Thesis (Ph.D.)--York University, 2008. Graduate Programme in Earth and Space Science. / Typescript. Includes bibliographical references (leaves 218-238). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:NR39016

Conventional land use change detections with remote sensing use annual remote sensing images because of the limitations of optical sensors that cannot collect data in bad weather and cloudy conditions. This limits its applications in rapidly developing areas which are cloudy, such as the Pearl River Delta in China. These areas also need to detect land use changes in short intervals, such as on a monthly basis, in order to monitor illegal land use changes and prevent irreversible land use changes that may damage the environment. The objective of the thesis is to examine short-interval land use change detection, especially the change from agriculture to built-up areas, using RADARSAT-1 images which can go through clouds. This thesis firstly examines the classification of RADARSAT-1 images with pixel-based and object-based classification methods respectively. Based on the classification results, post-classification change detection method are conducted in order to obtain the detailed information of land use changes for the analysis of short-interval land use change. Land use change detection accuracies can be improved as the number of the RADARSAT-1 images used in land use change detection increased. More images, which represent longer monitoring period, can obtain better results of land use change detection. For short-interval land use changes detection, four time periods is the maximum otherwise the period of monitoring will be too long. Agricultural activities such as planting and harvesting have significant effects on the monitoring of land use changes. In planting and harvesting months, the accuracies of the land use change detection are lower than other months because its land cover is often confused with other land uses, such as water and bare soils. The process of construction can be considered as a three-stage process and a combination of two land uses. However, construction sites are often confused with vegetation and bare soil in RADARSAT-1 images because the values of backscatter coefficients of construction sites and the two land uses are very similar. The land cover changes during the planting and harvest seasons are often confused with the process of construction. It is found that construction sites can be identified with their two stages of low values of backscatter coefficients, which is not found in the pattern curves of backscatter coefficients of other land uses. By the comparison of the accuracies of identifying construction sites using two, three and four RADARSAT-1 images, it is found that using three time periods can get better accuracies which is different from the result of general land use change detection. This thesis does not try to evaluate land use change detection methods or find the best method for monitoring land use changes. Instead, it focused on the analysis of confusions caused by the time periods of land use change detection and seasonal variation of vegetations. The main contributions of this study are as follows: 1) it explores the use of multi-temporal RADARSAT-1 images into the land use change detection to overcome the problems of cloudy conditions, making short-interval land use change detection possible for areas which are often covered by clouds; 2) pixel-based maximum likelihood method and the object-based classification method were compared for their accuracies in land use classification of RADARSAT-1 images; 3) it examines the optimal time periods for land use change detection; and 4) it examines the appropriate number of images that are needed for monitoring land use changes in different seasons in order to obtain the best accuracies. / published_or_final_version / Urban Planning and Design / Doctoral / Doctor of Philosophy

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<p> This dissertation presents the collection and processing of dense high-precision geode- tic data across major faults throughout Southern California. The results are used to inform numerical models of the long-term slip rate and interseismic behavior of these faults, as well as their frictional and rheological properties at shallow depths. The data include campaign surveys of dense networks of GPS monuments crossing the faults, and Interferometric Synthetic Aperture Radar (InSAR) observations from ENVISAT. Using a Bayesian framework, we first assess to what extent these data constrain relative fault slip rates on the San Andreas and San Jacinto faults, and show that the inferred parameters depend critically on the assumed fault geometry. We next look in detail at near-field observations of strain across the San Jacinto fault, and show that the source of this strain may be either deep anomalous creep or a new form of shallow, distributed yielding in the top few kilometers of the crust. On the San Andreas fault, we show that this type of shallow yielding does occur, and its presence or absence is controlled by variations in the local normal stress that result from subtle bends in the fault. Finally, we investigate shallow creep on the Imperial fault, and show that thanks to observations from all parts of the earthquake cycle it is now possible to obtain a strong constraint on the shallow frictional rheology and depth of the material responsible for creep. The results also suggest activity on a hidden fault to the West, whose existence has been previously suggested but never confirmed.</p>

<p> Savannas are mixed tree-grass systems and as one of the world's largest biomes represent an important component of the Earth system affecting water and energy balances, carbon sequestration and biodiversity as well as supporting large human populations. Savanna vegetation structure and its distribution, however, may change because of major anthropogenic disturbances from climate change, wildfire, agriculture, and livestock production. The overstory and understory may have different water use strategies, different nutrient requirements and have different responses to fire and climate variation. The accurate measurement of the spatial distribution and structure of the overstory and understory are essential for understanding the savanna ecosystem. </p><p> This project developed a workflow for separating the dynamics of the overstory and understory fractional cover in savannas at the continental scale (Australia, South America, and Africa). Previous studies have successfully separated the phenology of Australian savanna vegetation into persistent and seasonal greenness using time series decomposition, and into fractions of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil (BS) using linear unmixing. This study combined these methods to separate the understory and overstory signal in both the green and senescent phenological stages using remotely sensed imagery from the MODIS (MODerate resolution Imaging Spectroradiometer) sensor. The methods and parameters were adjusted based on the vegetation variation.</p><p> The workflow was first tested at the Australian site. Here the PV estimates for overstory and understory showed best performance, however NPV estimates exhibited spatial variation in validation relationships. At the South American site (Cerrado), an additional method based on frequency unmixing was developed to separate green vegetation components with similar phenology. When the decomposition and frequency methods were compared, the frequency method was better for extracting the green tree phenology, but the original decomposition method was better for retrieval of understory grass phenology. Both methods, however, were less accurate than in the Cerrado than in Australia due to intermingling and intergrading of grass and small woody components. </p><p> Since African savanna trees are predominantly deciduous, the frequency method was combined with the linear unmixing of fractional cover to attempt to separate the relatively similar phenology of deciduous trees and seasonal grasses. The results for Africa revealed limitations associated with both methods. There was spatial and seasonal variation in the spectral indices used to unmix fractional cover resulting in poor validation for NPV in particular. The frequency analysis revealed significant phase variation indicative of different phenology, but these could not be clearly ascribed to separate grass and tree components. </p><p> Overall findings indicate that site-specific variation and vegetation structure and composition, along with MODIS pixel resolution, and the simple vegetation index approach used was not robust across the different savanna biomes. The approach showed generally better performance for estimating PV fraction, and separating green phenology, but there were major inconsistencies, errors and biases in estimation of NPV and BS outside of the Australian savanna environment.</p>

Remote sensing is being used in agriculture for crop management. Ground based remote sensing data acquisition system was used for collection of high spatial and temporal resolution data for irrigated broccoli crop. The system was composed of a small cart that ran back and forth on a rail system that was mounted on a linear move irrigation system. The cart was equipped with a sensor that had 4 discrete wavelengths; 550 nm, 660 nm, 720 nm, and 810 nm, and an infrared thermometer, all had 10 nm bandwidth. A global positioning system was used to indicate the cart position. The study consisted of two parts; the first was to evaluate remotely sensed reflectance and indices in broccoli during the growing season, and determine whether remotely sensed indices or standard deviation of indices can distinguish between nitrogen and water stress in broccoli, and the second part of the study was to evaluate remotely sensed indices and standard deviation of remotely sensed indices in broccoli during daily changes in solar zenith angle. Results indicated that nitrogen was detected using Ratio Vegetation index, RVI, Normalized Difference Vegetation Index, NDVI, Canopy Chlorophyll Concentration Index, CCCI, and also using the reflectance in the Near-Infrared, NIR, bands. The Red reflectance band capability of showing stress was not as clear as the previous indices and bands reflectance. The Canopy Chlorophyll Concentration Index, CCCI, was the most successful index. The Crop Water Stress Index was able to detect water stress but it was highly affected by the solar zenith angle change along the day.

This paper describes the development, characterization, and modeling of a Tunable Filter Camera (TFC). The TFC is a new multispectral instrument with electronically tuned spectral filtering and low-light-level sensitivity. It represents a hybrid between hyperspectral and multispectral imaging spectrometers that incorporates advantages from each, addressing issues such as complexity, cost, lack of sensitivity, and adaptability. These capabilities allow the TFC to be applied to low-altitude video surveillance for real-time spectral and spatial target detection and image exploitation. Described herein are the theory and principles of operation for the TFC, which includes a liquid crystal tunable filter, an intensified CCD, and a custom apochromatic lens. The results of proof-of-concept testing, and characterization of two prototype cameras are included, along with a summary of the design analyses for the development of a multiple-channel system. A significant result of this effort was the creation of a system-level model, which was used to facilitate development and predict performance. It includes models for the liquid crystal tunable filter and intensified CCD. Such modeling was necessary in the design of the system and is useful for evaluation of the system in remote-sensing applications. Also presented are characterization data from component testing, which included quantitative results for linearity, signal to noise ratio (SNR), linearity, and radiometric response. These data were used to help refine and validate the model. For a pre-defined source, the spatial and spectral response, and the noise of the camera, system can now be predicted. The innovation that sets this development apart is the fact that this instrument has been designed for integrated, multi-channel operation for the express purpose of real-time detection/identification in low-light-level conditions. Many of the requirements for the TFC were derived from this mission. In order to provide background for the design requirements for the TFC development, the mission and principles of operation behind the multi-channel system will be reviewed. Given the combination of the flexibility, simplicity, and sensitivity, the TFC and its multiple-channel extension can play a significant role in the next generation of remote-sensing instruments.

This study focuses on the applications of remote sensing techniques and digital analysis to characterizing of tectonic features of the Rincon Mountains metamorphic core complex. Data included Landsat Thematic Mapper (TM) images, digital elevation models (DEM), and digital orthophoto quadrangle quads (DOQQ). The main findings in this study are two nearly orthogonal systems of structures that have never been reported in the Rincon Mountains. The first system, a penetrative faulting system of the footwall rocks, trends N10-30°W. Similar structures identified in other metamorphic core complexes. The second system trends N60-70°E, and has only been alluded indirectly in the literature of metamorphic core complexes. The structures pervade mylonites in Tanque Verde Mountain, Mica Mountain, and the Rincon Peak area. As measured on the imagery, spacing between the N10-30°W lineaments ranges from ∼0.5 to 2 km, and from 0.25 to 1 km for the N60-70°E system. Field inspection reveals that the N10-30°W trending system, are high-angle normal faults dipping mainly to the west. One of the main faults, named here the Cabeza de Vaca fault, has a polished, planar, striated and grooved surface with slickenlines indicating pure normal dip-slip movement (N10°W, 83°SW; slickensides rake 85°SW). The Cabeza de Vaca fault is the eastern boundary of a 2 km-wide graben, with displacement as great as 400 meters. The N10-30°W faults are syn- to post-mylonitic, high-angle normal faults that formed during isostatic uplift of the Rincon core complex during mid-Tertiary time. This interpretation is based on previous works, which report similar fault patterns in other metamorphic core complexes. Faults trending N20-30°W, shape the east flank of Mica Mountain. These faults, on the back dipping mylonitic zone, dip east and may represent late-stage antithetic shear zones. The Cabeza de Vaca fault and the back dipping antithetic faults accommodate as much as 65% of the extension due to doming of the core complex. The N60-70°E structures, not verified as a fault system, are a joint system pervading the footwall rocks of the metamorphic core complex. This system is less systematic. Spacing varies from 0.25 to 1 km. Both systems control the drainage of the mountains.