Assessing the Impact of Nightlight Gradients on Street Robbery and Burglary in Cincinnati of Ohio State, USA

Previous research has recognized the importance of edges to crime. Various scholars have explored how one specific type of edges such as physical edges or social edges affect crime, but rarely investigated the importance of the composite edge effect. To address this gap, this study introduces nightlight data from the Visible Infrared Imaging Radiometer Suite sensor on the Suomi National Polar-orbiting Partnership Satellite (NPP-VIIRS) to measure composite edges. This study defines edges as nightlight gradients—the maximum change of nightlight from a pixel to its neighbors. Using nightlight gradients and other control variables at the tract level, this study applies negative binomial regression models to investigate the effects of edges on the street robbery rate and the burglary rate in Cincinnati. The Akaike Information Criterion (AIC) of models show that nightlight gradients improve the fitness of models of street robbery and burglary. Also, nightlight gradients make a positive impact on the street robbery rate whilst a negative impact on the burglary rate, both of which are statistically significant under the alpha level of 0.05. The different impacts on these two types of crimes may be explained by the nature of crimes and the in-situ characteristics, including nightlight

Nighttime Lights as a Proxy for Economic Performance of Regions

Studying and managing regional economic development in the current globalization era demands prompt, reliable, and comparable estimates for a region’s economic performance. Night-time lights (NTL) emitted from residential areas, entertainment places, industrial facilities, etc., and captured by satellites have become an increasingly recognized proxy for on-ground human activities. Compared to traditional indicators supplied by statistical offices, NTLs may have several advantages. First, NTL data are available all over the world, providing researchers and official bodies with the opportunity to obtain estimates even for regions with extremely poor reporting practices. Second, in contrast to non-standardized traditional reporting procedures, the unified NTL data remove the problem of inter-regional comparability. Finally, NTL data are currently globally available on a daily basis, which makes it possible to obtain these estimates promptly. In this book, we provide the reader with the contributions demonstrating the potential and efficiency of using NTL data as a proxy for the performance of regions

Multisource Remote Sensing based Impervious Surface Mapping

Impervious surface (IS) not only serves as a key indicator of urbanization, but also affects the micro-ecosystem. Therefore, it is essential to monitor IS distribution timely and accurately. Remote sensing is an effective approach as it can provide straightforward and consistent information over large area with low cost. This thesis integrates multi-source remote sensing data to interpretate urban patterns and provide more reliable IS mapping results. Registration of optical daytime and nighttime lights (NTL) data is developed in the first contribution. An impervious surface based optical-to-NTL image registration algorithm with iterative blooming effect reduction (IS_iBER) algorithm is proposed. This coarse-to-fine procedure investigates the correlation between optical and NTL features. The iterative registration and blooming effect reduction method obtains precise matching results and reduce the spatial extension of NTL. Considering the spatial transitional nature of urban-rural fringes (URF) areas, the second study proposed approach for URF delineation, namely optical and nighttime lights (NTL) data based multi-scale URF (msON_URF).The landscape heterogeneity and development vitality derived from optical and NTL features are analyzed at a series of scales to illustrate the urban-URF-rural pattern. Results illustrate that msON_URF is effective and practical for not only concentric, but also polycentric urban patterns. The third study proposes a nighttime light adjusted impervious surface index (NAISI) to detect IS area. Parallel to baseline subtraction approaches, NAISI takes advantage of features, rather than spectral band information to map IS. NAISI makes the most of independence between NTL-ISS and pervious surface to address the high spectral similarity between IS and bare soil in optical image. An optical and NTL based spectral mixture analysis (ON_SMA) is proposed to achieve sub-pixel IS mapping result in the fourth study. It integrates characteristics of optical and NTL imagery to adaptively select local endmembers. Results illustrate the proposed method yields effective improvement and highlight the potential of NTL data in IS mapping. In the fifth study, GA-SVM IS mapping algorithm is investigated with introduction of the achieved urban-URF-rural spatial structure. The combination of optical, NTL and SAR imagery is discussed. GA is implemented for feature selection and parameter optimization in each urban scenario

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

On-Orbit Geometric Calibration and Validation of Luojia 1-01 Night-Light Satellite

The Luojia 1-01 Satellite (LJ1-01) is the first professional night-light remote-sensing satellite in China, and thus, it is of pioneering significance for the development of night-light remote sensing satellites in China and the application of remote sensing in the social and economic fields. To ensure the application of night-light remote-sensing data, several studies concerning on-orbit geometric calibration and accuracy verification have been carried out for the complementary metal oxide semiconductor (CMOS) rolling shutter camera of LJ1-01 since the launch of the satellite. Owing to the lack of high-precision nightlight geometric reference at home and abroad, it is difficult to directly calibrate the nighttime light image of LJ1-01. Based on the principle of rolling shutter dynamic imaging, a rigorous geometric imaging model of the time-sharing exposure of the rolling shutter of LJ1-01 is established, and a geometric calibration method for daytime imaging calibration and compensated nighttime light data is proposed. The global public Landsat digital orthophoto image (DOM) with a 15-m resolution and 90-m Shuttle Radar Topography Mission digital elevation model (SRTM-DEM) are used as control data. The images obtained in England, Venezuela, Caracas, Damascus, and Torreon (Mexico) were selected as experimental data. The on-orbit calibration and accuracy verification of LJ1-01 were carried out. Experiments show that after on-orbit geometric calibration, the daytime calibration parameters can effectively compensate for the systematic errors of night-light images. After compensation, the positioning accuracy of night-light images without geometric control points (GCPs) is improved from nearly 20 km to less than 0.65 km. The internal accuracy of the calibrated night-light images is better than 0.3 pixels, which satisfies the requirement of subsequent applications