This Thesis deals with the national legal aspects of a particular space application: remote sensing by satellites, also referred to as earth observation systems. / Governments have been the leading providers and users of satellite imagery data since the advent of earth observation satellites (i.e. almost 40 years ago). However, this has changed, particularly in the United States, with several private companies having acquired and launched their own imaging satellite systems. This new trend towards commercialization and privatization of the remote sensing industry, which appeared firstly in the United States and which is now being extended to Canada, required a change in policy. The role played by the government policies and regulations in shaping the prospects for the emerging commercial remote sensing satellite firms is of critical importance. In this context, these policies and regulations will determine the conditions that will enable commercial firms to realize their competitive potential in both the domestic and international marketplace. / In this Thesis, a brief overview of the technical and historical legal backgrounds of remote sensing is provided. Then, the international legal framework of remote sensing is briefly analyzed. Finally, a thorough analysis of the policies, laws and regulations applicable within the United States and Canada is presented.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Electrical Engineering at the Cape Peninsula University of Technology, 2012 / This research project addresses the unique challenges of extensive farming in terms of monitoring and controlling remote equipment or events. Poorly maintained roads and escalating fuel costs increase difficulty of farming and the time spent on physically monitoring remote sites further reduces financial yields. The research showed that there are very few solutions that implement wireless or electronic technology to overcome the challenges associated with these isolated and arid areas and that a low-cost, long range wireless telemetry solution that is easy to use would be beneficial for the extensive farming industry. It was therefore the aim of this project to develop a remote monitoring and controlling solution that implements wireless technology to convey information of activities around the farm utilising electronic means. To be able to successfully develop a wireless telemetry solution that will accurately meet the needs of this specific sector of industry, market research was conducted. To guide the research, the QFD (quality function deployment) process for product development has been implemented. The research consisted out of various aspects including a survey, financial considerations and international comparisons. The research also aided in the understanding of the day-to-day activities and also the physical parameters of extensive farms. Also, currently available technologies and products were evaluated to establish whether similarities exist that will aid in the development of a new product. The development process was based on the results obtained in the market research and resulted in a wireless telemetry solution that overcame all the design challenges and proved to be technically feasible, successfully addressing the application requirements. Zigbee technology was utilized for wireless communication because it provided an off-the-shelf solution with a number of readily available development platforms from various technology providers. A communication range of up to 6 kilometres with a transmitted power of 11dBm was achieved for point-to-point communication and a mesh network topology has been implemented for even longer range and complete coverage on farms. Various types of measurements have been catered for, with custom-designed instrumentation which enabled measurements such as water levels, movement and analogue signals. Also, a basic user interface was developed to enable the user to monitor or control the equipment or events remotely from a personal computer, locally or even over the internet. The results of this research project showed that by carefully selecting available technologies and understanding the application, it is possible to develop a solution that addresses the monitoring and controlling needs associated with extensive farming. The wireless telemetry system that was developed resulted in a saving equal to 10% of the total expenses of the farms per year. The telemetry system is therefore a financially feasible solution with a payback period of less than 1 year and far below the initial estimated budget. Without the need to physically monitoring equipment and events, an increase in productivity and the expansion of the overall enterprise is a further benefit added unto the monetary savings. In addition to the financial benefits of implementing new wireless technology, this is an opportunity to contribute to a cleaner and more sustained future as a legacy for the next generation by reducing the carbon footprint of the farm.

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Phytoplankton size classes (pico-plankton, nano-plankton, and micro-plankton) provide information about pelagic ocean ecosystem structure, and their spatiotemporal variation is crucial in understanding ocean ecosystem structure and global carbon cycling. Remote sensing provides an efficient approach to estimate phytoplankton size compositions on global scale. In the first part of this thesis, a global sensitivity analysis method was used to determine factors mainly controlling the variations of remote sensing reflectance and inherent optical properties inverse algorithms. To achieve these purposes, average mass-specific coefficients of particles were first calculated through Mie theory, using particle size distributions and refractive indices as input; and then a synthesis remote sensing reflectance dataset was created using Hydrolight. Based on sensitivity analysis results, an algorithm for estimating phytoplankton size composition was proposed in the second part. This algorithm uses five types of spectral features: original and normalized remote sensing reflectance, two-band ratios, continuum removed spectra, and spectral curvatures. With the spectral features, phytoplankton size compositions were regressed using support vector machine. According to validation results, this algorithm performs well with simulated and satellite Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS), indicating that it is possible to estimate phytoplankton size compositions through satellite data on global scale.

The report herein consisted of two objectives, the first of which was a data collection effort in John H. Kerr Reservoir. Ten field monitoring trips were performed between March 30, 1981 and March 3, 1982. The temperature, velocity, and depth data from those trips are contained in Appendix A. Plots of temperature versus depth at the stations chosen in the reservoir are contained in Appendix B. The second objective was an application of the database to Landsat MSS data available during the same period of record. The effects of temperature and total suspended solids on Landsat MSS reflectance were investigated. The effect of increasing temperature was a notable decrease in reflectance especially in Bands 4 and 5. This temperature effect may have been influenced by other water quality parameters that were not measured. The effect of increasing total suspended solids was a pronounced reflectance increase in Band 5. / M.S.

The purpose of this research was to explore the potential of using LANDSAT MSS data in the study of land use/cover patterns and turbidity relationships within the Lake Anna watershed. Two premises of this research are that a relationship exists between land use/cover patterns and turbidity levels, and that LANDSAT MSS data can be used to study this relationship. Turbidity levels within Lake Anna were estimated by the chromaticity technique used by Munday et al and were correlated to two groups of ground-based data -- surface turbidity levels and the product of the Universal Soil Loss Equation (USLE). Estimated turbidity levels correlated moderately well with surface data, but only a slight relationship could be established between land use/cover patterns and estimated turbidity. Possible explanations for these results were grouped into two categories, practical and conceptual problems. Practical problems were defined as data collection problems and included LANDSAT system and data accuracy problems. Conceptual problems were problems based on theoretical issues of using LANDSAT MSS data to study relationships between land use/cover patterns and turbidity levels. Conceptual problems remained even after the practical problems were solved. The accomplishments of this research included the application of chromaticity analysis to small man-made reservoirs, further exploration of the relationship between land use/cover patterns, and turbidity levels, and extension of LANDSAT MSS data in watershed management. Most importantly, this research exposed some of the limitations in using LANDSAT MSS data to study relationships between land use/cover patterns and turbidity levels. / Master of Science

Master of Arts / Department of Geography / Kevin P. Price / Due primarily to changes in land management practices, eastern redcedar (Juniperus virginiana L.), a native Kansas conifer, is rapidly invading onto valuable rangelands. The suppression of fire and increase of intensive grazing, combined with the rapid growth rate, high reproductive output, and dispersal ability of the species have allowed it to dramatically expand beyond its original range. There is a growing interest in harvesting this species for use as a biofuel. For economic planning purposes, density and biomass quantities for the trees are needed. Three methods are explored for mapping eastern redcedar and quantifying its biomass in Riley County, Kansas. First, a land cover classification of redcedar cover is performed using a method that utilizes a support vector machine classifier applied to a multi-temporal stack of Landsat TM satellite images. Second, a Small Unmanned Aircraft System (sUAS) is used to measure individual redcedar trees in an area where they are encroaching into a pasture. Finally, a hybrid approach is used to estimate redcedar biomass using high resolution multispectral and light detection and ranging (LiDAR) imagery. These methods showed promise in the forestry, range management, and bioenergy industries for better understanding of an invasive species that shows great potential for use as a biofuel resource.

This doctoral thesis investigates the potential of classification methods based on spatial context to infer specific forms of land use from remote sensing data. The problem is that some types of land use are characterized by a complex configuration of land covers that traditional per-pixel based methods have problems classifying due to spectral heterogeneity. The problem of spectral heterogeneity is also present in classification of high resolution imagery. Two novel methods based on contextual information are evaluated, Spatial Relational Post-Classification (SRPC) and Window Independent Context Segmentation (WICS). The thesis includes six case studies in rural and urban areas focusing on the classification of: agricultural systems, urban characteristics, and dead wood areas. In the rural case studies specific types of agricultural systems associated with different household strategies are mapped by inferring the physical expression of land use using the SRPC method. The urban remote sensing studies demonstrate how the WICS method is able to extract information corresponding to different phases of development. Additionally, different urban classes are shown to correspond to different socioeconomic profiles, demonstrating how urban remote sensing can be used to make a connection between the physical environment and the social lives of residents. Finally, in one study the WICS method is used to successfully classify dead trees from high resolution imagery. Taken together these studies demonstrate how approaches based on spatial context can be used to extract information on land use in rural and urban environments where land use manifests itself in the form of complex spectral class and land cover patterns. The thesis, thus, contributes to the research field by showing that contextual methods can capture multifaceted patterns that can be linked to land use. This, in turn, enables an increased use of remote sensing data, particularly in the social sciences. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript. Paper 5: Manuscript. Paper 6: Manuscript.</p>

The Kafue Flats floodplain wetland system in southern Zambia is under increasing climate and human pressures. Firstly, drought episodes appear more prevalent in recent years in the region and secondly, two dams were built on the lower and upper ends of the wetland in 1972 and 1978, respectively, across the Kafue River which flows through the wetland. The study uses multi-temporal remote sensing to assess change in extent and vigour of green vegetation, and extent of water bodies and dry land cover on the Kafue Flats. The change detection's management value is assessed. Four normalised, co-registered digital Landsat images from 24 September 1984, 3 September 1988, 12 September 1991 and 20 September 1994 were used. The main change detection method used was comparison of classifications, supplemented by Normalised Difference Vegetation Index (NDVI) and Principal Component Analysis (PCA) change detection. Ancillary land use and environmental data were used in interpreting the change in the context of cause and effect. The results indicate inconsistent trends in the changes of most land cover classes, as a result of manipulation of the wetland by man through annual variations in the timing and magnitude of regulated flows into the wetland, as well as burning. However, the results also show spatial reduction in the wetland's dry season dense green reed-grass vegetation in upstream sections which are not affected by the water backing-up above of the lower dam. Sparse green vegetation is replacing the dense green vegetation in these upstream areas. It is inferred that this dry season degradation of the wetland threatens bird species which may use the reeds for dry season nesting. It is proposed that ground surveying and monitoring work at the micro-habitat level is necessary to ascertain the implications of the losses. It is concluded that, in spite of difficulties, multi-temporal remote sensing has a potential role in wetland change assessment on the Kafue Flats at the community level, but that it needs to be supplemented by targeted, micro-habitat level ground surveys.

Remote sensing and GIS have become standard tools for evaluating spatial components of wildlife habitats. These techniques were implemented to evaluate Rio Grande wild turkey (Meleagris gallopavo) poult-rearing habitat in the Western Cross Timbers region of Texas. Texas Parks and Wildlife (TPWD) random roving turkey counts for 1987-1989 and 1998-2000 were selected, indicating locations where hens with poults were observed. Satellite imagery from 1988 and 1999 was classified and then processed with Patch Analyst. To add robustness, stream, road and census population densities were also evaluated for each turkey location. Analysis of the 1988 canopy cover image, comparing observed locations with randomly-selected habitat cells (N = 20) indicated significant differences (p <.05) for patch edge variables. Mean patch edge was significantly greater for habitat locations where hens with poults were observed than for those selected at random. Spatial data for 1999 did not indicate a significant difference (p < .05) between sampling groups (observed vs. random, N = 30). Significant differences (p <.05) did occur for turkey locations observed in both 1988 and 1999 (N = 7). This demonstrates the adaptability of wild turkey hens, as habitats change over time, hens continued to visit the same locations even though the habitat had significantly changed for select spatial variables.