Enhanced data and methods for improving open and free global population grids: putting ‘leaving no one behind’ into practice     

Sergio Freire  Marcello Schiavina  Aneta J. Florczyk  Kytt MacManus  Martino Pesaresi  Christina Corbane 《International Journal of Digital Earth》2020,13(1):61-77

ABSTRACT

Data on global population distribution are a strategic resource currently in high demand in an age of new Development Agendas that call for universal inclusiveness of people. However, quality, detail, and age of census data varies significantly by country and suffers from shortcomings that propagate to derived population grids and their applications. In this work, the improved capabilities of recent remote sensing-derived global settlement data to detect and mitigate major discrepancies with census data is explored. Open layers mapping built-up presence were used to revise census units deemed as ‘unpopulated’ and to harmonize population distribution along coastlines. Automated procedures to detect and mitigate these anomalies, while minimizing changes to census geometry, preserving the regional distribution of population, and the overall counts were developed, tested, and applied. The two procedures employed for the detection of deficiencies in global census data obtained high rates of true positives, after verification and validation. Results also show that the targeted anomalies were significantly mitigated and are encouraging for further uses of free and open geospatial data derived from remote sensing in complementing and improving conventional sources of fundamental population statistics.  相似文献   

Exploring the usability of PPGIS among older adults: challenges and opportunities     

Sarah Gottwald  Tiina E. Laatikainen  Marketta Kyttä 《International journal of geographical information science》2016,30(12):2321-2338

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A place-based model of local activity spaces: individual place exposure and characteristics     

Kamyar Hasanzadeh  Tiina Laatikainen  Marketta Kyttä 《Journal of Geographical Systems》2018,20(3):227-252

Researchers for long have hypothesized relationships between mobility, urban context, and health. Despite the ample amount of discussions, the empirical findings corroborating such associations remain to be marginal in the literature. It is growingly believed that the weakness of the observed associations can be largely explained by the common misspecification of the geographical context. Researchers coming from different fields have developed a wide range of methods for estimating the extents of these geographical contexts. In this article, we argue that no single approach yet has sufficiently been capable of capturing the complexity of human mobility patterns. Subsequently, we discuss that reaching a better understanding of individual activity spaces can be possible through a spatially sensitive estimation of place exposure. Following this discussion, we take an integrative person and place-based approach to create an individualized residential exposure model (IREM) to estimate the local activity spaces (LAS) of the individuals. This model is created using data collected through public participation GIS. Following a brief comparison of IREM with other commonly used LAS models, the article continues by presenting an empirical study of aging citizens in Helsinki area to demonstrate the usability of the proposed framework. In this study, we identify the main dimensions of LASs and seek their associations with socio-demographic characteristics of individuals and their location in the region. The promising results from comparisons and the interesting findings from the empirical part suggest both a methodological and conceptual improvement in capturing the complexity of local activity spaces.  相似文献