Miu, Hoi Shun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 170-182). / Abstracts in English and Chinese. / Abstract --- p.ii / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.4 / Chapter 1.2 --- Contributions --- p.5 / Chapter 1.3 --- Thesis Organization --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- Multi-agent Systems --- p.8 / Chapter 2.1.1 --- Agent Architectures --- p.9 / Chapter 2.1.2 --- Multi-agent system frameworks --- p.12 / Chapter 2.1.3 --- The Advantages and Disadvantages of Multi-agent Systems --- p.15 / Chapter 2.2 --- Evolutionary Computation --- p.16 / Chapter 2.2.1 --- Genetic Algorithms --- p.17 / Chapter 2.2.2 --- Genetic Programming --- p.18 / Chapter 2.2.3 --- Evolutionary Strategies --- p.19 / Chapter 2.2.4 --- Evolutionary Programming --- p.19 / Chapter 2.3 --- Object Recognition --- p.19 / Chapter 2.3.1 --- Knowledge Representation --- p.20 / Chapter 2.3.2 --- Object Recognition Methods --- p.21 / Chapter 2.4 --- Evolutionary Multi-agent Systems --- p.25 / Chapter 2.4.1 --- Competitive Coevolutionary Agents --- p.26 / Chapter 2.4.2 --- Cooperative Coevolutionary Agents --- p.26 / Chapter 2.4.3 --- Cellular Automata --- p.27 / Chapter 2.4.4 --- Emergent Behavior --- p.28 / Chapter 2.4.5 --- Evolutionary Agents for Image processing and Pattern Recog- nition --- p.29 / Chapter 3 --- System Architecture and Agent Behaviors in SIMULATORS --- p.33 / Chapter 3.1 --- Organization of the System --- p.34 / Chapter 3.1.1 --- General Architecture of Object Recognition System --- p.34 / Chapter 3.1.2 --- Introduction to SIMULATORS --- p.35 / Chapter 3.1.3 --- System Flow of SIMULATORS --- p.37 / Chapter 3.1.4 --- Layered Digital Image Environment --- p.39 / Chapter 3.2 --- Architecture of Autonomous Agents --- p.41 / Chapter 3.2.1 --- Internal Object Model in an Agent --- p.41 / Chapter 3.2.2 --- Current State of an Agent --- p.46 / Chapter 3.2.3 --- Local Information Sensor --- p.46 / Chapter 3.2.4 --- Direction Density Vector --- p.47 / Chapter 3.3 --- Agent Behaviors --- p.48 / Chapter 3.3.1 --- Feature Target Marking --- p.49 / Chapter 3.3.2 --- Reproduction --- p.49 / Chapter 3.3.3 --- Diffusion --- p.52 / Chapter 3.3.4 --- Vanishing --- p.54 / Chapter 3.4 --- Clustering for Autonomous Agent Training --- p.56 / Chapter 3.4.1 --- Introduction --- p.56 / Chapter 3.4.2 --- Creating the Internal Object Model --- p.58 / Chapter 3.5 --- Summary --- p.63 / Chapter 4 --- Evolutionary Algorithms for Multi Agent System --- p.64 / Chapter 4.1 --- Evolutionary Agent Behaviors in SIMULATORS --- p.65 / Chapter 4.1.1 --- Overview --- p.65 / Chapter 4.1.2 --- Evolutionary Autonomous Agents --- p.66 / Chapter 4.1.3 --- Reproduction --- p.68 / Chapter 4.1.4 --- Fitness Function --- p.68 / Chapter 4.1.5 --- Direction Density Vector Propagation --- p.73 / Chapter 4.1.6 --- Mutation --- p.73 / Chapter 4.2 --- Agents Voting Mechanism --- p.74 / Chapter 4.2.1 --- Overview --- p.74 / Chapter 4.2.2 --- Voting for Cooperative Agents --- p.75 / Chapter 4.3 --- Evolutionary Multi Agent Object Recognition --- p.79 / Chapter 4.4 --- Summary --- p.81 / Chapter 5 --- Experimental Results and Applications --- p.82 / Chapter 5.1 --- Experiment Methodology --- p.82 / Chapter 5.1.1 --- Introduction to Fung Shui Woodland --- p.83 / Chapter 5.1.2 --- Testing Images --- p.83 / Chapter 5.1.3 --- Creating Internal Object Model --- p.85 / Chapter 5.1.4 --- Experiment Parameters --- p.86 / Chapter 5.2 --- Experimental Results of Fung Shui Woodland Recognition --- p.92 / Chapter 5.2.1 --- Experiment 1: artificial0l --- p.92 / Chapter 5.2.2 --- Experiment 2: artificial0l´ؤnoise --- p.92 / Chapter 5.2.3 --- Experiment 3: artificial02 --- p.93 / Chapter 5.2.4 --- Experiment 4: FungShui0l --- p.93 / Chapter 5.2.5 --- Experiment 5: FungShui0l´ؤnoise --- p.94 / Chapter 5.2.6 --- Experiments 6 to 11: FungShui02 to FungShui07 --- p.94 / Chapter 5.3 --- Discussion --- p.119 / Chapter 5.4 --- An Example of Eyes Detection --- p.124 / Chapter 5.4.1 --- Result of the Eyes Detection --- p.128 / Chapter 5.5 --- Summary --- p.132 / Chapter 6 --- Conclusion --- p.133 / Chapter 6.1 --- Summary --- p.133 / Chapter 6.2 --- Future Work --- p.136 / Chapter A --- The Figures in the Experiments --- p.138

<p> Hyperspectral and polarimetric imaging of the ocean, both below and above the water surface, has increased the interest of the Ocean Color (OC) scientific community for decades in an attempt to answer questions related to climate change, monitoring of water quality, assessment of the impact of anthropogenic activities on marine life and underwater ecosystems, detection and characterization of underwater targets. These needs are recognized by worldwide efforts devoted to acquiring accurate time series measurements in open-ocean and coastal waters by OC satellite imagery to produce reliable high-quality data records, which can be used both in support of operations and in climate studies. The reliability of satellite observations of the open-ocean and coastal zones requires these remote instruments to be regularly assessed and validated against actual in-situ measurements along with related atmospheric corrections. However, despite improvements in satellite data and retrieval algorithms, accurate retrievals in coastal waters remain challenging. </p><p> Modern hyperspectral imagers usually carry out their measurements on moving platforms, aircrafts or orbiting satellites, using push-broom scanning techniques for the acquisition of 3-D data cubes (along-track, cross-track and spectral). These data, however, may not always reflect accurately the temporal variability of measurements in a very dynamic atmosphere-ocean environment, especially in coastal areas. In recent years, new technologies have made possible the exploration of snapshot hyperspectral and polarimetric imaging of the ocean in an attempt to improve the accuracy of existing methods and exploring the pixel-by-pixel variability of the signal measured, often neglected in standard approaches. </p><p> The work presented in this thesis investigates and discusses imaging of underwater polarimetric targets in various water types and the estimation of parameters of the veiling light and the attenuation coefficients responsible for image degradation and blurring as a function of the water properties. In above water observations the effects of atmospheric aerosols and wind speed on the surface reflectance coefficients are studied along with the pixel-by-pixel variability of water-leaving radiance (<i>L_w</i>) and its relationship to water constituents for different coastal waters and atmospheric conditions, the impact of this variability on the uncertainties in above water measurements and satellite retrievals. Validation of all results has been achieved by the comparison with the comprehensive Vector Radiative Transfer simulations of the Atmosphere-Ocean System, as well as measurements by a number of other collocated radiometric and polarimetric instruments. </p><p>

An objective technique which produces regularly spaced fields of winds, temperatures, humidity, wind stress and sensible and latent heat fluxes is developed. It combines in-situ Volunteer Observing Ship (VOS) data and remotely sensed data from SEASAT during the analysis period, July 7-October 10, 1978 for the north Atlantic. The objective technique is a variational method which reduces a set of several constraints expressing closeness to input data, climatology and kinematics. Analysis results are presented for monthly and 5-day periods during the analysis period. / Seasonal (3 month) means of temperature, humidity, and flux determined by the monthly and 5-day results are comparable. However, 5-day wind results had much smaller errors than the monthly mean winds averaged over the 3-month period. / Variability of the 5-day results indicates high variability of temperatures, humidity, and heat fluxes in the vicinity of the Gulf Stream. Sea surface temperature (SST) variability is high in the eastern Atlantic and is coupled to wind driven ocean variability in the region. / Heat fluxes are coupled to and determined by various parameters. The variations for both sensible and latent heat fluxes in the extra-tropics are determined by the position and strength of the circulation of the semi-permanent high pressure system. Some evidence is also found to indicate dependence of SST on latent heat. In the tropics, the heat fluxes are determined by a combination of factors, including zonal wind and SST. / Estimates of errors due to insufficient sampling and random data are presented for the monthly results. The sampling and random errors in wind stress are in the range of 10%-20% of the mean values. For the sensible and latent heat fluxes, the sampling errors are about half of those attributable to random errors. Because of the difference operator used in diagnosing heat fluxes, these fluxes are found to be more sensitive to the accuracies of temperatures and humidity than accuracies of winds. / Source: Dissertation Abstracts International, Volume: 53-03, Section: B, page: 1417. / Major Professor: James J. O'Brien. / Thesis (Ph.D.)--The Florida State University, 1992.

Klarälven är en av Sveriges längsta älvar och är unik i Skandinavien för sitt karaktäristiska meanderlopp. Det unika i Klarälvens fall är att älvfåran är instängd mellan två bergssidor. Klarälvens meanderlopp innebär erosion och förändringar i älvens lopp. Syftet med studien är att jämföra och analysera hur erosionen längs en sträcka av Klarälven har förändrats över tid. Underlaget består av en historisk karta från 1883 samt ortofoton från 1961 och 2014. Studien är avgränsad till en 25 km lång sträcka norr om Ekshärad i Värmland. Metoder som används omfattar georeferering av den historiska kartan samt skärmdigitalisering av samtliga data. Därefter granskades och jämfördes resultaten genom överlagringsanalys uppdelat i två perioder samt alla perioder på en gång. Resultatet visar att omfattande erosion och avlagring har skett. I älvens ytterkurvor där vattnets hastighet är som högst har störst erosion skett och i innerkurvorna där vattnet rinner långsammare har det eroderade materialet avlagrats. De största skillnaderna är uppmätta mellan åren 1883 och 1961. Men erosionsförändring i mindre skala har skett även mellan 1961 och 2014. / River Klarälven is one of Sweden's longest rivers and is unique in Scandinavia because of its characteristic meander course.  The uniqueness in the case of Klarälven is that the riverbed is trapped between two mountain sides. The meandering course of Klarälven means major changes in its path due to extensive erosion along some reaches. The purpose of this study is to compare and analyze how some reaches of River Klarälven have changed over time. The data consists of a historical map from 1883 as well as orthophotos from 1961 and 2014. The study is limited to a 25 km meandering reach north of the town Ekshärad in northern Värmland. Methods involved are georeferencing of the historical map and screen digitizing of all data. Subsequently, the results were reviewed and compared by overlay analysis divided into two periods and all periods at once. The result shows that extensive erosion and deposit have taken place. In the river's outer curves where the velocity of the water is highest is also the place where most erosion occurs. In the inner curves where the water velocity is slower, the eroded material is deposited. The largest differences were measured between the years 1883 and 1961. However, erosion changes on a smaller scale also occurred between 1961 and 2014.

No description available.

This thesis illustrates the specific aspects that influence or limit the application of remotely-sensed data for information retrieval from coastal marine, estuarine and riverine environments. The thesis is drawn principally from ten separate studies and is divided into discrete sections, or experiments, that provide an understanding of the fundamental aspects of the effects of the atmosphere, water surface, water column and bottom on sensor-received reflected signal.The results show the importance of precise calculation of acquisition parameters and the absolute importance of relevant reference data. Most instrumentation for remote sensing at visible wavelengths has been developed for terrestrial applications where signal is rarely limiting and target features are relatively static. For in-water applications, where signal is small and noise can be large, the features to be sensed may be temporally dynamic and obscured.However, the work presented also shows the great benefit and spatial cost-effectiveness that can be obtained if the spectral and temporal specification is adequately considered. The prime motivation for such applications usually comes from the requirement to detect and quantify water column characteristics, such as phytoplankton forming as algal blooms, and bottom stratigraphic condition, such as benthic habitat mapping for fishery or conservation purposes.

Australia is one of the leading mineral resource extraction nations in the world. It is one of the world’s top producers of nickel, zinc, uranium, lithium, coal, gold, iron ore and silver. However, the complexity of the environmental issues and the potentially damaging consequences of mining have attracted public attention and political controversy. Other types of underground natural resource exploitation, such as ground water, gas or oil extractions, also cause severe land deformation on different scales in space and time. The subsidence due to underground mining and underground fluid extractions has the potential to impact on surface and near surface infrastructure; as well as water quality and quantity, that in turn has the potential to impact on threatened flora and fauna, and biodiversity conservation. Subsidence can also impact natural and cultural heritage. To date, most of land deformation monitoring is done using conventional surveying techniques, such as total stations, levelling, GPS, etc. These surveying techniques provide high precision in height at millimetre accuracy, but with the drawbacks of inefficiency and costliness (labour intensive and time consuming) when surveying over a large area. Radar interferometry is an imaging technique for measuring geodetic information of terrain. It exploits phase information of the backscattered radar signals from the ground surface to retrieve the altitude or displacements of the objects. It has been successfully applied in the areas of cartography, geodesy, land cover characterisation, mitigation of natural or man-made hazards, etc. The goal of this dissertation was to develop a system which integrated differential interferometric synthetic aperture radar (DInSAR), ground survey data and geographic information systems (GIS) as a whole to provide the land deformation maps for underground mining and water extraction activities. This system aimed to reinforce subsidence assessment processes and avoid or mitigate potential risks to lives, infrastructure and the natural environment. The selection of suitable interferometric pairs is limited to the spatial and temporal separations of the acquired SAR images as well as the characteristics of the site, e.g. slope of terrain, land cover, climate, etc. Interferometric pairs with good coherence were selected for further DInSAR analysis. The coherence analysis of both C- and L-band spaceborne SAR data was studied for sites in the State of New South Wales, Australia. The impact of the quality of the digital elevation models (DEM), used to remove the static topography in 2-pass DInSAR, were also analysed. This dissertation examined the quality of the DEM generated using aerial photogrammetry, InSAR, and airborne laser scanning (ALS) against field survey data. Kinematic and real-time kinematic GPS were introduced here as an efficient surveying method for collecting ground truth data for DEM validation. For mine subsidence monitoring, continuous DInSAR mine subsidence maps were generated using ERS-1/2, Radarsat-1 and JERS-1 data with the assumption of negligible horizontal displacement. One of the significant findings of this study was the results from the ERS-1/2 tandem DInSAR, which showed an immediate mine subsidence of 1cm occurred during a period of 24 hours. It also raised the importance of SAR constellations for disaster mitigation. In order to understand the 3-D displacement vectors of mine deformation, this dissertation also proposed a method using the SAR data acquired at 3 independent incidence angles from both ascending and descending orbits. Another issue of the high phase gradient, induced by the mine subsidence, was also addressed. Phase gradient was clearly overcome by having the L-band ALOS data with an imaging resolution of 10m, which is better than the imaging resolution of 18m of the previous generation of the Japanese L-band SAR satellite, JERS-1. The ground survey data over a similar duration was used for validation. Besides mine subsidence monitoring the land deformation caused by groundwater pumping were also presented. In contrast to mine subsidence, the underground water extraction induced subsidence has the characteristics of a slow rate of change and less predictable location and coverage. Two case studies were presented. One was at the geothermal fields in New Zealand and another was the urban subsidence due to underground water over exploitation in China. Both studies were validated against ground survey data. Finally, SAR intensity analysis for detecting land deformation was demonstrated when DInSAR was not applicable due to strong decorrelation. The region of land surface change, which may be caused by human activities or natural disasters, can be classified. Two cases studies were given. The first study was the surface change detection at an open-cut mine. The second one was the 2004 Asian tsunami damage assessment near Banda Aceh. The results presented in this dissertation showed that the integrated system of DInSAR, GIS and ground surveys has the potential to monitor mine subsidence over a large area. The accuracy of the derived subsidence maps can be further improved by having a shorter revisit cycle and better imaging resolution of the newly launched and planned SAR satellites and constellation missions. The subsidence caused by groundwater pumping can be monitored at an accuracy of millimetre by utilising the technique of persistent scatterer InSAR.

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Airborne hyperspectral imagery has the potential to overcome the spectral and spatial resolution limitations of multispectral satellite imagery for monitoring salinity at both regional and farm scales. In particular, saline areas that have good cover of salt tolerant plants are difficult to map with multispectral satellite imagery. Hyperspectral imagery may provide a more reliable salinity mapping method because of its potential to discriminate halophytic plant cover from non - halophytes. HyMap and CASI airborne imagery ( at 3m ground resolution ) and Hyperion satellite imagery ( at 30 resolution ) were acquired over a 140 sq km dryland agricultural area in South Australia, which exhibits severe symptoms of salinity, including extensive patches of the perennial halophytic shrub samphire ( Halosarcia pergranulata ), sea barley grass ( Hordeum marinum ) and salt encrusted pans. The HyMap and Hyperion imagery were acquired in the dry season ( March and February respectively ) to maximise soil and perennial vegetation mapping. The optimum time of year to map sea barley grass, an annual species, was investigated through spectral discrimination analysis. Multiple reflectance spectra were collected of sea barley grass and other annual grasses with an ASD Fieldspec Pro spectrometer during the September spring flush and in November during late senescence. Comparing spectra of different species in November attempted to capture the spectral differences between the late senescing sea barley grass and other annual grasses. Broad NIR and SWIR regions were identified where sea barley grass differs significantly from other species in November during late senescence. The sea barley grass was therefore shown to have the potential to be discriminated and mapped with hyperspectral imagery at this time and as a result the CASI survey was commission for November. Other salinity symptoms were characterised by collecting single field and laboratory spectra for comparison to image derived spectra in order to provide certainty about the landscape components that were to be mapped. Endmembers spectra associated with saltpans and samphire patches were extracted from the imagery using automated endmember generation procedures or selected regions of interest and used in subsequent partial unmixing. Spectral subsets were evaluated for their ability to optimise salinity maps. The saltpan spectra contained absorption features consistent with montmorillonite and gypsum. A single gypsum endmember from one image strip successfully mapped saltpans across multiple images strips using the 1750 nm absorption feature as the input to matched filter unmixing. The individual spectra of green and red samphire are dominated by photosynthetic vegetation characteristics. The spectra of green samphire, often seen with red tips, exhibit peaks in both green and red wavebands whereas the red samphire spectra only contain a significant reflectance peak in the visible red wavelength region. For samphire, Mixture Tuned Matched Filtering using image spectra, containing all wavelength regions, from known samphire patches produced the most satisfactory mapping. Output salinity maps were validated at over 100 random sites. The HyMap salinity maps produced the most accurate results compared to CASI and Hyperion. HyMap successfully mapped highly saline areas with a good cover of samphire vegetation at Point Sturt without the use of multitemporal imagery or ancillary data such as topography or PIRSA soil attribute maps. CASI and Hyperion successfully mapped saltpan, however, their samphire maps showed a poor agreement with field data. These results suggest that perennial vegetation mapping requires all three visible, NIR and SWIR wavelength regions because the SWIR region contains important spectral properties related to halophytic adaptations. Furthermore, the unconvincing results of the CASI sea barley grass maps suggests that the optimal sensor for mapping both soil and vegetation salinity symptoms are airborne sensors with high spatial and spectral resolution, that incorporate the 450 to 1450 nm wavelength range, such as HyMap. This study has demonstrated that readily available software and image analysis techniques are capable of mapping indicators of varying levels of salinity. With the ability to map symptoms across multiple image strips, airborne hyperspectral imagery has the potential for mapping larger areas covering sizeable dryland agriculture catchments, closer in extent to single satellite images. This study has illustrated the advantage of the hyperspectral imagery over traditional soil mapping based on aerial photography interpretation such as the NLWRA Salinity 2000 and the PIRSA soil landscape unit maps. The HyMap salinity maps not only improved mapping of saline areas covered with samphire but also provided salinity maps that varied spatially within saline polygons. / Thesis (Ph.D.)--School of Earth and Environmental Sciences, 2006.

<p>For multispectral Remote Sensing (RS) image analysis, a big problem is that original dataalways include Clouds-Interference (CI). Especially in the bad weather conditions, the CI is evidentin RS image. So during the pre-processing of RS image, the CI should be reduced as much aspossible. In this paper, reducing CI is researched as the central problem, so that much Ground-Objects Feature (GOF) can be obtained. An analysis about the clouds reflection in differentSpectral-Bands (SBs) was done based on optical theory and early researches. Moreover, therelationships between clouds reflection and ground-objects reflection are presented to understandwhat the Digital Number (DN) represented in each SB, and to reduce the impact of CI the Same DNSpectral Matching Method (SDN-SMM) based on the multispectral application is applied. Finally,two cases are tested using Matlab Programme to indicate the rationality and practicability of SDNSMM.About SDN-SMM, some advantages and disadvantages are concluded through discussion onfinal results. The method can be used in any kind of multispectral sensors image with simplecalculation, while, the original data of clouds-free region will not be changed. However, the qualityof CI reduction depends on the precision of clouds identification and the SB which is used forspectral position relationship creating. In the end of this paper, the improvement is also presentedfor the future work.</p>