Urban dynamics at regional scales has been increasingly important for economics, policies, and land use planning, and monitoring regional scale urban dynamics has become an urgent need in recent years. This study illustrated the use of time series nighttime light (NTL) data from the United States Air Force Defense Meteorological Satellites Program/Operational Linescan System (DMSP/OLS) to delineate urban boundaries and tracked three key urban changes: land cover change, population growth and GDP growth within Virginia. NTL data from different years were inter-calibrated to be comparable by using linear regression model and Pseudo Invariant Features (PIFs) method. Urban patches were delineated by applying thresholding techniques based on digital number (DN) values extracted from DMSP/OLS imagery. Compounded Night Light Index (CNLI) values were calculated to help estimate GDP, and these processes were applied in a time series from 2000 to 2010. Spatial patterns of DN change and the variation of CNLI indicate that human activities were increasing during the 10 years in Virginia. Accuracy of the results was confirmed using ancillary data sources from the U.S. Census and NLCD imagery. / Master of Science / Urban areas concentrate built environment, population, and economic activities, therefore, generating urban sprawl is a simultaneous result of land-use change, economic growth, population growth and so on. Remote sensing has been used to map urban sprawl within individual cities for a long time, while there has been less research focused on regional scale urban dynamics. However, the regional scale urban dynamics for economics, formulating policies, and land use planning has been increasingly important, and monitoring regional scale urban dynamics has become an urgent need in recent years. Here, we illustrated the use of multi-temporal United States Air Force Satellites data to help monitor urban sprawls by delineating urban patches and we measured a variety of urban changes, such as urban population growth and land cover change within Virginia based on the delineation. For doing so, digital number values, which measures the brightness of satellite imagery, were extracted and other relative index values were calculated based on digital number values, and these processes were applied in a time series from 2000 to 2010. Spatial patterns of digital number values change and the variation of another light index values indicate that human activities were increasing during the 10 years in Virginia.

<p>Nowadays, NRTS (Nighttime Road Traffic Safety) and energy saving are very hot topics in transportation field. This thesis investigates a general optimal model for minimizing NRTAs (nighttime road traffic accidents) and power consumption of the road lighting. To establish this model, the relationship between N/D RTAs (Night to Day Road Traffic Accidents) ratio and road lighting condition and the relationship between power consumption and road lighting condition have been studied and explained. A media variable “economic cost” has been chosen which is used for making a connection between these two relationships. The evaluations of NRTAs and power consumption from cost point of view are introduced as well. The impacts of each internal factor defined by author are explained carefully. The result of the model based on these relationships and internal influencing factors is presented in the paper. Finally, the recommendations for reducing NRTAs and/or power consumption, as well as other interesting areas for further study are presented.</p>

Nowadays, NRTS (Nighttime Road Traffic Safety) and energy saving are very hot topics in transportation field. This thesis investigates a general optimal model for minimizing NRTAs (nighttime road traffic accidents) and power consumption of the road lighting. To establish this model, the relationship between N/D RTAs (Night to Day Road Traffic Accidents) ratio and road lighting condition and the relationship between power consumption and road lighting condition have been studied and explained. A media variable “economic cost” has been chosen which is used for making a connection between these two relationships. The evaluations of NRTAs and power consumption from cost point of view are introduced as well. The impacts of each internal factor defined by author are explained carefully. The result of the model based on these relationships and internal influencing factors is presented in the paper. Finally, the recommendations for reducing NRTAs and/or power consumption, as well as other interesting areas for further study are presented.

How can light positively influence and encourage pedestrians’ engagement and interaction with the urban environments at night? In this Master Thesis, I questioned how to develop nighttime urban planning from a socially-oriented approach. In order to answer this question, I studied different evidence such as two publications, three lighting designers’ and a lighting studio’ approach; three case studies analyses, two of them located in Colombia (Cartagena and Medellín) and one in Sweden (Stockholm);and my own qualitative observation and quantitative measurements studied between April and May at Norrmalmstorg and Biblioteksgatan in Stockholm, Sweden. From that review, I propose a Guideline consisted of three sections: (1) Main dimensions, (2) lighting attributes, and (3) lighting systems in urban planning. In general, this guideline is a framework to develop the analytical tools for various design stages in nighttime urban planning.

Conventional surveillance systems present video to a user from more than one camera on a single display. Such a display allows the user to observe different part of the scene, or to observe the same part of the scene from different viewpoints. Each video is usually labeled by a fixed textual annotation displayed under the video segment to identify the image. With the growing number of surveillance cameras set up and the expanse of surveillance area, the conventional split-screen display approach cannot provide intuitive correspondence between the images acquired and the areas under surveillance. Such a system has a number of inherent flaws¡GLower relativity of split videos¡BThe difficulty of tracking new activities¡BLow resolution of surveillance videos¡BThe difficulty of total surveillance¡FIn order to improve the above defects, the ¡§Immersive Surveillance for Total Situational Awareness¡¨ use computer graphic technique to construct 3D model of buildings on the 2D satellite-images, the users can construct the floor platform by defining the information of each floor or building and the position of each camera. This information is combined to construct 3D surveillance scene, and the images acquired by surveillance cameras are pasted into the constructed 3D model to provide intuitively visual presentation. The users could also walk through the scene by a fixed-frequency , self-defined business model to perform a virtual surveillance. Multi-camera Human Tracking on Realtime 3D Immersive Surveillance System based on the ¡§Immersive Surveillance for Total Situational Awareness,¡¨ 1. Salient object detection¡GThe System converts videos to corresponding image sequences and analyze the videos provided by each camera. In order to filter out the foreground pixels, the background model of each image is calculated by pixel-stability-based background update algorithm. 2. Nighttime image fusion¡GUse the fuzzy enhancement method to enhance the dark area in nighttime image, and also maintain the saturation information. Then apply the Salient object detection Algorithm to extract salient objects of the dark area. The system divides fusion results into 3 parts: wall, ceiling, and floor, then pastes them as materials into corresponding parts of 3D scene. 3. Multi-camera human tracking¡GApply connected component labeling to filter out small area and save each block¡¦s infomation. Use RGB-weight percentage information in each block and 5-state status (Enter¡BLeave¡BMatch¡BOcclusion¡BFraction) to draw out the trajectory of each person in every camera¡¦s field of view on the 3D surveillance scene. Finally, fuse every camera together to complete the multi-camera realtime people tracking. Above all, we can track every human in our 3D immersive surveillance system without watching out each of thousand of camera views.

Studies of nesting behaviours of free-ranging apes typically focus on ecological variables such as preferred tree species and areas within the home range, heights of nests, and nest group sizes. However, nesting in captive apes is rarely studied, despite the ubiquity of this sleep-related behaviour. The paucity of field data is often attributed to the inherent difficulty in observing what is essentially a nighttime behaviour. Captive settings can provide researchers with an ideal opportunity to record nesting and sleep-related behaviours, yet such research on captive apes is also scant. Topics addressed include current practices in zoos regarding conditions for sleep in great apes, the potential effects of social and environmental factors on sleep site selection, the motor patterns involved in nest construction, preferred nesting structures and substrates, and nocturnal behaviours. This thesis documented and empirically tested hypotheses concerning nest-related activities in captive chimpanzees, with an aim to generate practical recommendations for enclosure design, sleeping areas, sleeping structures, and nesting substrates that have implications for the welfare of captive apes. As with the few reports that already exist, most chimpanzees in this research frequently constructed night nests. When building a nest, some techniques appeared to be universal across individuals and groups, where others were group-specific or occasionally characteristic of only certain individuals. An experiment showed that specific materials are preferred over others for nest building. Many chimpanzees appeared to express persistent preferences for particular sleeping sites, and for some this was to maintain proximity to kin or other closely bonded individuals. In one group, individual sleeping site preferences changed across seasons, although again this was subject to individual differences. Video analyses of nighttime behaviours demonstrated that, although nests/sleep sites are primarily used for rest subsequent to retirement, a number of social and non-social activities were performed throughout the night. In conjunction with analysis of postural and orientation shifts, these data are unique in describing the nocturnal behaviours of chimpanzees out with a laboratory setting. Several aspects of nest-related behaviours showed a high degree of inter-and intra-group variation. Although this cautions against generalising findings across captive populations, research of this type has applied implications for the management of captive ape species, and can add to our as-yet meagre understanding of their nest and sleep-related behaviours.

Marine deoxygenated areas are expanding, and more hypoxic zones emerge globally. Climate change induced warming and stratification can extrapolate the biological oxygen demand, more predominantly at coastal areas and reefs with dense vegetation and high metabolic activity. The diurnal oxygen fluctuation can reach a critically low oxygen level at nighttime, exposing aquatic organisms to severe hypoxia that could interfere with viable ecosystem functions. Little is known about the impact of hypoxia on marine primary producers macroalgae, mainly the physiological adaptation of the Red Sea macroalgae under climate change scenarios is understudied. Here we investigate hypoxia thresholds at night time for conspicuous Red Sea macroalgae species calcareous Halimeda opuntia and Padina boryana and noncalcifying brown algae Sargassum latifolium. We utilized a computer-based gas system to expose the samples to different oxygen treatments (normoxia, hypoxia, and severe hypoxia) that mimic in situ water chemistry at 32 °C. We monitored algal physiological response during 12 hours of exposure to different oxygen levels in the dark by measuring photochemical efficiency, respiration rates, and cellular viability. For the duration of our experiments (12h), we did not detect lethal thresholds. In all tested species, severe hypoxia significantly decreased photochemical efficiency, and hypoxia had a limited impact on photochemical efficiency. However, both low oxygen treatments significantly decreased respiration rates and induced changes in cellular activity. We concluded a sublethal O$_2$ thresholds SLC$_{(50)}$ of 1.2 ±0.1, 1.5 ±0.1, and 1.7 ±0.1 mg O$_2$ L$^{−1}$ ±SD for H. opuntia, P. boryana, and S. latifolium responses, respectively. We also found that during 12 hours of treatments, the median time to observe a 50% reduction in photochemical efficiency under severe hypoxia treatment relative to control was 6.3 ±1.4, 3.5 ±1.0, and 0.8 ±1.3 hours ±SD for H. opuntia, P. boryana, and S. latifolium responses, respectively. This study is the first assessment of Red Sea macroalgae response to hypoxia and the first dark nighttime algal adaptation of its kind for our proposed species. Further investigation is needed to assess daytime recovery, recurring dark hypoxia, and synergic or sequential effects of other environmental stressors on hypoxia thresholds.

No description available.

It has been found that traveling on the roadways at night is an inherently more dangerous task than driving during the daylight hours. Driving is primarily a visual task, and there are certain situations at night in which vision and safety may be compromised. The effects of glare produced by the headlamps of oncoming vehicles have become an interesting problem to many lighting researchers. Depending upon the opposing lighting design (beam distribution and intensity) and the lighting conditions inside the vehicle, oncoming headlamps can be both visually discomforting and disabling to drivers at night. In recent years, the newer High Intensity Discharge (HID) headlamps have raised some concern because of their increased light output and brighter appearance as opposed to traditional Halogen headlamps. The objective of this study was to evaluate the discomfort and disability glare produced by different oncoming headlamps under two driver light adaptation levels. This study took place on the Smart Road at the Virginia Tech Transportation Institute. During the Discomfort Glare portion, participants drove an experimental vehicle at 20mph past the oncoming headlamps and were asked to rate their overall discomfort with the subjective deBoer scale. The Disability Glare portion involved drivers detecting a static pedestrian in the roadway while approaching each different set of glare headlamps. It was hypothesized that there would be significant differences in detection distance and discomfort glare rating across the different glare headlamp and adaptation level combinations. It was also hypothesized that age would have a significant effect on detection distance, and the subjective ratings. The results of this study revealed many significant main effects and interactions for the discomfort and disability glare portions. The main effect of glare source was the only significant factor for discomfort glare. The main effects of age, glare source and pedestrian location were all significant for the disability portion. In addition, the interaction of pedestrian location and glare source was also significant. Overall, there was no clear relationship between subjective discomfort ratings and objective disability measures. The conclusions of this research will be valuable to the consumer as well as the manufacturers and designers of future headlamps in revealing how glare can affect drivers on the road at night. This information can help guide new designs to maximize forward visibility while minimizing glare. / Master of Science

There has been a significant number of security concerns in recent times; as a result, security cameras have been installed to monitor activities and to prevent crimes in most public places. These analysis are done either through video analytic or forensic analysis operations on human observations. To this end, within the research context of this thesis, a proactive machine vision based military recognition system has been developed to help monitor activities in the military environment. The proposed object detection, recognition and re-identification systems have been presented in this thesis. A novel technique for military personnel recognition is presented in this thesis. Initially the detected camouflaged personnel are segmented using a grabcut segmentation algorithm. Since in general a camouflaged personnel's uniform appears to be similar both at the top and the bottom of the body, an image patch is initially extracted from the segmented foreground image and used as the region of interest. Subsequently the colour and texture features are extracted from each patch and used for classification. A second approach for personnel recognition is proposed through the recognition of the badge on the cap of a military person. A feature matching metric based on the extracted Speed Up Robust Features (SURF) from the badge on a personnel's cap enabled the recognition of the personnel's arm of service. A state-of-the-art technique for recognising vehicle types irrespective of their view angle is also presented in this thesis. Vehicles are initially detected and segmented using a Gaussian Mixture Model (GMM) based foreground/background segmentation algorithm. A Canny Edge Detection (CED) stage, followed by morphological operations are used as pre-processing stage to help enhance foreground vehicular object detection and segmentation. Subsequently, Region, Histogram Oriented Gradient (HOG) and Local Binary Pattern (LBP) features are extracted from the refined foreground vehicle object and used as features for vehicle type recognition. Two different datasets with variant views of front/rear and angle are used and combined for testing the proposed technique. For night-time video analytics and forensics, the thesis presents a novel approach to pedestrian detection and vehicle type recognition. A novel feature acquisition technique named, CENTROG, is proposed for pedestrian detection and vehicle type recognition in this thesis. Thermal images containing pedestrians and vehicular objects are used to analyse the performance of the proposed algorithms. The video is initially segmented using a GMM based foreground object segmentation algorithm. A CED based pre-processing step is used to enhance segmentation accuracy prior using Census Transforms for initial feature extraction. HOG features are then extracted from the Census transformed images and used for detection and recognition respectively of human and vehicular objects in thermal images. Finally, a novel technique for people re-identification is proposed in this thesis based on using low-level colour features and mid-level attributes. The low-level colour histogram bin values were normalised to 0 and 1. A publicly available dataset (VIPeR) and a self constructed dataset have been used in the experiments conducted with 7 clothing attributes and low-level colour histogram features. These 7 attributes are detected using features extracted from 5 different regions of a detected human object using an SVM classifier. The low-level colour features were extracted from the regions of a detected human object. These 5 regions are obtained by human object segmentation and subsequent body part sub-division. People are re-identified by computing the Euclidean distance between a probe and the gallery image sets. The experiments conducted using SVM classifier and Euclidean distance has proven that the proposed techniques attained all of the aforementioned goals. The colour and texture features proposed for camouflage military personnel recognition surpasses the state-of-the-art methods. Similarly, experiments prove that combining features performed best when recognising vehicles in different views subsequent to initial training based on multi-views. In the same vein, the proposed CENTROG technique performed better than the state-of-the-art CENTRIST technique for both pedestrian detection and vehicle type recognition at night-time using thermal images. Finally, we show that the proposed 7 mid-level attributes and the low-level features results in improved performance accuracy for people re-identification.