Identifying Population Hollowing Out Regions and Their Dynamic Characteristics across Central China

Continuous urbanization and industrialization lead to plenty of rural residents migrating to cities for a living, which seriously accelerated the population hollowing issues. This generated series of social issues, including residential estate idle and numerous vigorous laborers migrating from undeveloped rural areas to wealthy cities and towns. Quantitatively determining the population hollowing characteristic is the priority task of realizing rural revitalization. However, the traditional field investigation methods have obvious deficiencies in describing socio-economic phenomena, especially population hollowing, due to weak efficiency and low accuracy. Here, this paper conceives a novel scheme for representing population hollowing levels and exploring the spatiotemporal dynamic of population hollowing. The nighttime light images were introduced to identify the potential hollowing areas by using the nightlight decreasing trend analysis. In addition, the entropy weight approach was adopted to construct an index for evaluating the population hollowing level based on statistical datasets at the political boundary scale. Moreover, we comprehensively incorporated physical and anthropic factors to simulate the population hollowing level via random forest (RF) at a grid-scale, and the validation was conducted to evaluate the simulation results. Some findings were achieved. The population hollowing phenomenon decreasing gradually was mainly distributed in rural areas, especially in the north of the study area. The RF model demonstrated the best accuracy with relatively higher R2 (Mean = 0.615) compared with the multiple linear regression (MLR) and the geographically weighted regression (GWR). The population hollowing degree of the grid-scale was consistent with the results of the township scale. The population hollowing degree represented an obvious trend that decreased in the north but increased in the south during 2016–2020 and exhibited a significant reduction trend across the entire study area during 2019–2020. The present study supplies a novel perspective for detecting population hollowing and provides scientific support and a first-hand dataset for rural revitalization

COVID-19ロックダウンによって生じた人間活動の変化の大気汚染レベルへの影響

Tohoku University博士（環境科学）thesi

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

Long-term exposure to environmental factors and risk of metabolic disorders in children

Epidemiological studies have yielded evidence that environmental pollution can adversely influence human metabolic health, including conditions such as diabetes and obesity. However, the existing literature has mainly focused on adults or the elderly, leaving a gap in the knowledge about the risks in children. Moreover, potential mechanisms through which early-life exposures may affect children’s metabolism require more evidence. To address this gap, the main objective of this research work was to explore associations between exposure to environmental factors and the risk of metabolic disorders during early childhood, using data from a large-scale public health screening of children in Bavaria, Germany. Long-term exposure estimates of air pollutants, air temperature, greenness, and light at night for each participant’s residence were assessed using high-resolution data from reliable sources. Two important aspects of children’s health were studied in this thesis. In the first publication, a novel approach was employed to investigate the associations between prenatal and early life exposure to air pollution, air temperature, and surrounding greenness, and the development of islet autoimmunity (a crucial precursor of type 1 diabetes). This study used high temporal-spatial resolution data to examine different exposure windows in 85,251 children at the zip code level and 52,636 children at the residential level, all aged between 1.75 and 5.99 years. The results showed a higher risk of islet autoimmunity with decreasing air temperature. In the second publication, the effects of outdoor artificial light at night on body mass were investigated among 62,212 children younger than 11 years, and the analyses revealed significant positive associations, with the effects being more pronounced in boys. In conclusion, this thesis significantly advances our understanding of the adverse health impacts of environmental factors on children’s metabolic health. While affirming prior research findings, it also introduces novel evidence and strengthens the existing body of knowledge. This study stands as one of the first to examine the effects of a wide range of environmental factors on children’s metabolic health. Nevertheless, further research is needed to gain a deeper understanding of the associations and to explore the underlying mechanisms. Moreover, the different geographic regions with different exposure patterns and with the incorporation of behavioral and lifestyle data. impacts of environmental factors on children’s health should be further investigated across different geographic regions with different exposure patterns and with the incorporation of behavioral and lifestyle data.Epidemiologische Studien haben gezeigt, dass sich Umweltverschmutzung negativ auf die menschliche Stoffwechselgesundheit auswirken kann, einschließlich Erkrankungen wie Diabetes und Adipositas. Die vorhandene Literatur konzentriert sich jedoch hauptsächlich auf Erwachsene oder ältere Menschen, so dass eine Wissenslücke bzgl. der Risiken bei Kindern besteht. Auch die potenziellen Mechanismen, durch die frühkindliche Expositionen den Stoffwechsel von Kindern beeinflssen können, benötigenweiter evidenz. Um diese Lücke zu schließen, bestand das Hauptziel dieser Forschungsarbeit darin, Zusammenhänge zwischen der Exposition gegenüber Umweltfaktoren und dem Risiko von Stoffwechselstörungen in der frühen Kindheit zu untersuchen. Hierzu wurden Daten aus einem groß angelegten Public Health Screening von Kindern in Bayern verwendet wurden. Anhand von hochauflösenden Daten aus zuverlässigen Quellen wurden für den Wohnort jedes Teilnehmenden Langzeitexpositionsschätzungen für Luftschadstoffe, Lufttemperatur, Grünflächen und Lichtexposition bei Nacht abgeschätzt. Im Rahmen dieser Forschung wurden zwei wichtige Aspekte der Gesundheit von Kindern untersucht. In der ersten Veröffentlichung wurden ein innovativer Ansatz verfolgt, der die Untersuchung verscgidener Expositionszeitfenster mit hochauflösenden zeitlich-räumlichen Daten einschloss. Dieser ansatz diente dazu, die Zusammenhänge zwischen vorgeburtlicher und frühkindlicher Exposition gegenüber Luftschadstoffen, Lufttemperatur, und Grünheit, und der Autoimmunität der Inselzellen (eine entscheidende Vorstufe von Typ-1-Diabetes) bei 85,251 Kindern auf Postleitzahl- und bei 52,636 Kindern auf Wohngebietsebene im Alter zwischen 1.75 und 5.99 Jahren untersucht. Die Ergebnisse zeigten ein höheres Risiko für Inselzellen-Autoimmunität mit abnehmender Lufttemperatur. In der zweiten Veröffentlichung wurden die Auswirkungen von nächtlichem künstlichem Licht im Freien auf die Körpermasse von 62,212 Kindern im Alter von unter 11 Jahren untersucht. Die Analysen ergaben signifikante positive Zusammenhänge, wobei die Auswirkungen bei Jungen stärker ausgeprägt waren. Zusammenfassend lässt sich sagen, dass diese Dissertation unser Verständnis für die negativen gesundheitlichen Auswirkungen von Umweltfaktoren auf die meabolische Gesundheit vn Kindern erheblich erweitert. Sie bestätigt frühere forschungsergebnisse und liefert darüer hinaus neue, die bestehendenErkentnisse Stärkende epidemiologische Evidenz. Diese Studie gehört zu den ersten, die die auswirkunken eines breiten spektrums von umweltfaktoren auf die metabolische Gesundheit von Kindern untersuchen. Dennoch ist weitere Forschung erfordlich, um ein tieferes Verständnis dieser Zusammenhänge zu erlangen und die zugrunde liegenden Mechanismen zu erforschen. Außerdem sollten die Auswirkungen von Umweltfaktoren auf die Gesundheit von Kindern in verschiedenen geografischen Regionen mit unterschiedlichen Expositionsmustern und unter Einbeziehung von Verhaltens- und Lebensstildaten weiter untersucht werden

SATELLITE AND ARTIFICIAL INTELLIGENCE IN MAPPING MULTIDIMENSIONAL POVERTY IN AFRICA

Context and background Multidimensional Poverty (MP) considers poverty in multiple dimensions of deprivations such as health, education, energy, the standard of living and access to basic services. MP remains a major challenge in Africa, with a large proportion of the population living in MP. According to United Nations Development Programme (UNDP), Africa has shown the highest Multidimensional Poverty Index (MPI) having over 40% of its population living in MP. Goal and Objectives: This paper is a review, aimed at assessing the potential of the integration of satellite and Artificial Intelligence (AI) in mapping MP, with a specific focus on Africa. Methodology: Based on the reviews of past studies, the combination of satellite data such as nighttime light, daytime satellite imagery and high-resolution settlement data in combination with techniques such as field surveys, statistical correlation models (transfer learning) and AI (deep learning) has been applied in mapping MP. Results: The findings from studies show that the combination of satellite data and AI has the capability of providing more accurate and granular MP maps, compared to the traditional approach. Again, this paper explains the concept of MP with a specific focus on Africa and presents a map depicting the current MPI in African countries. Finally, pitfalls especially in the accuracy, granularity and frequency of MP data were identified. Consequently, the satellite and AI approaches are recommended for more accurate, frequent, cost-effective and granular data, required in mapping poverty and design of interventions that effectively address the needs of the vulnerable populations in Africa.

The Canadian Urban Environmental Health Research Consortium - A protocol for building a national environmental exposure data platform for integrated analyses of urban form and health

Background: Multiple external environmental exposures related to residential location and urban form including, air pollutants, noise, greenness, and walkability have been linked to health impacts or benefits. The Canadian Urban Environmental Health Research Consortium (CANUE) was established to facilitate the linkage of extensive geospatial exposure data to existing Canadian cohorts and administrative health data holdings. We hypothesize that this linkage will enable investigators to test a variety of their own hypotheses related to the interdependent associations of built environment features with diverse health outcomes encompassed by the cohorts and administrative data. Methods: We developed a protocol for compiling measures of built environment features that quantify exposure; vary spatially on the urban and suburban scale; and can be modified through changes in policy or individual behaviour to benefit health. These measures fall into six domains: air quality, noise, greenness, weather/climate, and transportation and neighbourhood factors; and will be indexed to six-digit postal codes to facilitate merging with health databases. Initial efforts focus on existing data and include estimates of air pollutants, greenness, temperature extremes, and neighbourhood walkability and socioeconomic characteristics. Key gaps will be addressed for noise exposure, with a new national model being developed, and for transportation-related exposures, with detailed estimates of truck volumes and diesel emissions now underway in selected cities. Improvements to existing exposure estimates are planned, primarily by increasing temporal and/or spatial resolution given new satellite-based sensors and more detailed national air quality modelling. Novel metrics are also planned for walkability and food environments, green space access and function and life-long climate-related exposures based on local climate zones. Critical challenges exist, for example, the quantity and quality of input data to many of the models and metrics has changed over time, making it difficult to develop and validate historical exposures. Discussion: CANUE represents a unique effort to coordinate and leverage substantial research investments and will enable a more focused effort on filling gaps in exposure information, improving the range of exposures quantified, their precision and mechanistic relevance to health. Epidemiological studies may be better able to explore the common theme of urban form and health in an integrated manner, ultimately contributing new knowledge informing policies that enhance healthy urban living

Assessing contributions of agricultural and nonagricultural emissions to atmospheric ammonia in a Chinese megacity

Ammonia (NH3) is the predominant alkaline gas in the atmosphere contributing to formation of fine particles—a leading environmental cause of increased morbidity and mortality worldwide. Prior findings suggest that NH3 in the urban atmosphere derives from a complex mixture of agricultural (mainly livestock production and fertilizer application) and nonagricultural (e.g., urban waste, fossil fuel-related emissions) sources; however, a citywide holistic assessment is hitherto lacking. Here we show that NH3 from nonagricultural sources rivals agricultural NH3 source contributions in the Shanghai urban atmosphere. We base our conclusion on four independent approaches: (i) a full-year operation of a passive NH3 monitoring network at 14 locations covering urban, suburban, and rural landscapes; (ii) model-measurement comparison of hourly NH3 concentrations at a pair of urban and rural supersites; (iii) source-specific NH3 measurements from emission sources; and (iv) localized isotopic signatures of NH3 sources integrated in a Bayesian isotope mixing model to make isotope-based source apportionment estimates of ambient NH3. Results indicate that nonagricultural sources and agricultural sources are both important contributors to NH3 in the urban atmosphere. These findings highlight opportunities to limit NH3 emissions from nonagricultural sources to help curb PM2.5 pollution in urban China

Assessing sustainable development in industrial regions towards smart built environment management using Earth observation big data

This thesis investigates the sustainability of nationwide industrial regions using Earth observation big data, from environmental and socio-economic perspectives. The research contributes to spatial methodology design and decision-making support. New spatial methods, including the robust geographical detector and the concept of geocomplexity, are proposed to demonstrate the spatial properties of industrial sustainability. The study delivers scientific decision-making advice to industry stakeholders and policymakers for the post-construction assessment and future planning phases. The research has been published in prestigious geography journals, demonstrating its success

A framework for mapping earth observation capabilities to the OHCHR indicators

Satellite imagery is advantageously situated to monitor human activities and environmental changes, particularly if the target is remote and across large spatial areas. In some instances in-situ data collection is not possible, this is for example if the target is isolated or the political stance of the country prevents ground access. Human rights research can faces these obstacles when trying to collect and use traditional in-situ data methods. This paper focuses on the human rights and security sector, by presenting a systematic framework developed and used to understand and explore the applicability of satellite imagery to human rights monitoring. An extensive literature review of research papers and development projects was conducted to identify all the capabilities of Earth Observation (EO), by also suggesting relevant missions, supplementary data products, algorithms and analytical processes. An outline of the review is presented in the paper through a taxonomy of all relevant satellite applications that meet the Office of the United Nations High Commissioner for Human Rights (OHCHR) framework on human rights indicators. Overall, this research aims to ensure that this data source is maximized for its full potential in the field, to ensure that effective human rights studies are conducted. This form of research has already been conducted extensively for the UN’s Sustainable Development Goals (SDG) and so the purpose of this paper is to advance this research even further, but with particular emphasis on human rights monitoring and corresponding indicators. Some of the OHCHR indicators do not have overlap with the SDGs, such as for example ‘Proportion of households living in or near hazardous conditions rehabilitated’ in ‘Right to Adequate Housing’. Hence this research draws particular focus onto these indicators and wants to fill an existing gap on EO capabilities mapping. The vast scope of EO data applications is made clear through this paper, however future developments in space technology and future planned missions are also discussed to understand which human rights insights can be met in the future with more frequent and higher spatial and spectral resolution information. Despite the essential need for EO data in the sector and the advancement of the Space industry, it also comes with its own limitations, which are discussed in detail in the paper