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Author He, L.; Páez, A.; Jiao, J.; An, P.; Lu, C.; Mao, W.; Long, D.
Title Ambient Population and Larceny-Theft: A Spatial Analysis Using Mobile Phone Data Type Journal Article
Year 2020 Publication ISPRS International Journal of Geo-Information Abbreviated Journal Ijgi
Volume 9 Issue 6 Pages 342
Keywords Remote Sensing; Public Safety
Abstract In the spatial analysis of crime, the residential population has been a conventional measure of the population at risk. Recent studies suggest that the ambient population is a useful alternative measure of the population at risk that can better capture the activity patterns of a population. However, current studies are limited by the availability of high precision demographic characteristics, such as social activities and the origins of residents. In this research, we use spatially referenced mobile phone data to measure the size and activity patterns of various types of ambient population, and further investigate the link between urban larceny-theft and population with multiple demographic and activity characteristics. A series of crime attractors, generators, and detractors are also considered in the analysis to account for the spatial variation of crime opportunities. The major findings based on a negative binomial model are three-fold. (1) The size of the non-local population and people’s social regularity calculated from mobile phone big data significantly correlate with the spatial variation of larceny-theft. (2) Crime attractors, generators, and detractors, measured by five types of Points of Interest (POIs), significantly depict the criminality of places and impact opportunities for crime. (3) Higher levels of nighttime light are associated with increased levels of larceny-theft. The results have practical implications for linking the ambient population to crime, and the insights are informative for several theories of crime and crime prevention efforts.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2220-9964 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2997
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Author Lin, J.; Shi, W.
Title Statistical Correlation between Monthly Electric Power Consumption and VIIRS Nighttime Light Type Journal Article
Year 2020 Publication ISPRS International Journal of Geo-Information Abbreviated Journal Ijgi
Volume 9 Issue 1 Pages 32
Keywords Remote Sensing
Abstract The nighttime light (NTL) imagery acquired from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) enables feasibility of investigating socioeconomic activities at monthly scale, compared with annual study using nighttime light data acquired from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS). This paper is the first attempt to discuss the quantitative correlation between monthly composite VIIRS DNB NTL data and monthly statistical data of electric power consumption (EPC), using 14 provinces of southern China as study area. Two types of regressions (linear regression and polynomial regression) and nine kinds of NTL with different treatments are employed and compared in experiments. The study demonstrates that: (1) polynomial regressions acquire higher reliability, whose average R square is 0.8816, compared with linear regressions, whose average R square is 0.8727; (2) regressions between denoised NTL with threshold of 0.3 nW/(cm2·sr) and EPC steadily exhibit the strongest reliability among the nine kinds of processed NTL data. In addition, the polynomial regressions for 12 months between denoised NTL with threshold of 0.3 nW/(cm2·sr) and EPC are constructed, whose average values of R square and mean absolute relative error are 0.8906 and 16.02%, respectively. These established optimal regression equations can be used to accurately estimate monthly EPC of each province, produce thematic maps of EPC, and analyze their spatial distribution characteristics.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2220-9964 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2820
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Author Wang,; Sutton,; Qi,
Title Global Mapping of GDP at 1 km2 Using VIIRS Nighttime Satellite Imagery Type Journal Article
Year 2019 Publication ISPRS International Journal of Geo-Information Abbreviated Journal Ijgi
Volume 8 Issue 12 Pages 580
Keywords Remote Sensing
Abstract Frequent and rapid spatially explicit assessment of socioeconomic development is critical for achieving the Sustainable Development Goals (SDGs) at both national and global levels. Over the past decades, scientists have proposed many methods for estimating human activity on the Earth’s surface at various spatiotemporal scales using Defense Meteorological Satellite Program Operational Line System (DMSP-OLS) nighttime light (NTL) data. However, the DMSP-OLS NTL data and the associated processing methods have limited their reliability and applicability for systematic measuring and mapping of socioeconomic development. This study utilized Visible Infrared Imaging Radiometer Suite (VIIRS) NTL and the Isolation Forest machine learning algorithm for more intelligent data processing to capture human activities. We used machine learning and NTL data to map gross domestic product (GDP) at 1 km2. We then used these data products to derive inequality indexes (e.g., Gini coefficients) at nationally aggregate levels. This flexible approach processes the data in an unsupervised manner at various spatial scales. Our assessments show that this method produces accurate subnational GDP data products for mapping and monitoring human development uniformly across the globe.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2220-9964 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2787
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Author Tagliabue, L.C.; Re Cecconi, F.; Moretti, N.; Rinaldi, S.; Bellagente, P.; Ciribini, A.L.C.
Title Security Assessment of Urban Areas through a GIS-Based Analysis of Lighting Data Generated by IoT Sensors Type Journal Article
Year 2020 Publication Applied Sciences Abbreviated Journal Applied Sciences
Volume 10 Issue 6 Pages 2174
Keywords Lighting
Abstract The current perspective about urban development expects 70% of energy consumption will be concentrated in the cities in 2050. In addition, a growing density of people in the urban context leads to the need for increased security and safety for citizens, which imply a better lighting infrastructure. Smart solutions are required to optimize the corresponding energy effort. In developing countries, the cities’ lighting is limited and the lighting world map is strongly significant about the urban density of the different areas. Nevertheless, in territories where the illumination level is particularly high, such as urban contexts, the conditions are not homogenous at the microscale level and the perceived security is affected by artificial urban lighting. As an example, 27.2% of the families living in the city of Milan, ombardy Region, Italy, consider critical the conditions of lighting in the city during the night, although the region has diffused infrastructure. The paper aims to provide a local illuminance geographic information system (GIS) mapping at the neighborhood level that can be extended to the urban context. Such an approach could unveil the need to increase lighting to enhance the perceived safety and security for the citizens and promote a higher quality of life in the smart city. Lighting mapping can be matched with car accident mapping of cities and could be extended to perceived security among pedestrians in urban roads and green areas, also related to degradation signs of the built environment. In addition, such an approach could open new scenarios to the adaptive street lighting control used to reduce the energy consumption in a smart city: the perceived security of an area could be used as an additional index to be considered during the modulation of the level of the luminosity of street lighting. An example of a measurement set-up is described and tested at the district level to define how to implement an extensive monitoring campaign based on an extended research schema.
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Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2076-3417 ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2873
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Author Avtar, R.; Tripathi, S.; Aggarwal, A.K.
Title Assessment of Energy–Population–Urbanization Nexus with Changing Energy Industry Scenario in India Type Journal Article
Year 2019 Publication Land Abbreviated Journal Land
Volume 8 Issue 8 Pages 124
Keywords Remote Sensing
Abstract The demand for energy has been growing worldwide, especially in India partly due to the rapid population growth and urbanization of the country. To meet the ever-increasing energy requirement while maintaining an ecological balance is a challenging task. However, the energy industry-induced effect on population and urbanization has not been addressed before. Therefore, this study investigates the linkages between energy, population, and urbanization. The study also aims to find the quantifiable indicators for the population growth and rate of urbanization due to the expanding energy industry. The integrated framework uses a multi-temporal Landsat data to analyze the urbanization pattern, a census data for changes in population growth, night time light (NTL) data as an indicator for economic development and energy production and consumption data for energy index. Multi-attribute model is used to calculate a unified metric, termed as the energy–population–urbanization (EPU) nexus index. The proposed approach is demonstrated in the National Thermal Power Corporation (NTPC) Dadri power plant located in Uttar Pradesh, India. Landsat and NTL data clearly shows the urbanization pattern, economic development, and electrification in the study area. A comparative analysis based on various multi-attribute decision model assessment techniques suggests that the average value of EPU nexus index is 0.529, which significantly large compared to other studies and require special attention by policymakers because large EPU index indicates stronger correlation among energy, population, and urbanization. The authors believe that it would help the policymakers in planning and development of future energy projects, policies, and long-term strategies as India is expanding its energy industry.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2073-445X ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number GFZ @ kyba @ Serial 2620
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