Towards a compact representation of temporal rasters

Big research efforts have been devoted to efficiently manage spatio-temporal data. However, most works focused on vectorial data, and much less, on raster data. This work presents a new representation for raster data that evolve along time named Temporal k^2 raster. It faces the two main issues that arise when dealing with spatio-temporal data: the space consumption and the query response times. It extends a compact data structure for raster data in order to manage time and thus, it is possible to query it directly in compressed form, instead of the classical approach that requires a complete decompression before any manipulation. In addition, in the same compressed space, the new data structure includes two indexes: a spatial index and an index on the values of the cells, thus becoming a self-index for raster data.Comment: This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Actions H2020-MSCA-RISE-2015 BIRDS GA No. 690941. Published in SPIRE 201

Geographical and temporal weighted regression (GTWR)

Both space and time are fundamental in human activities as well as in various physical processes. Spatiotemporal analysis and modeling has long been a major concern of geographical information science (GIScience), environmental science, hydrology, epidemiology, and other research areas. Although the importance of incorporating the temporal dimension into spatial analysis and modeling has been well recognized, challenges still exist given the complexity of spatiotemporal models. Of particular interest in this article is the spatiotemporal modeling of local nonstationary processes. Specifically, an extension of geographically weighted regression (GWR), geographical and temporal weighted regression (GTWR), is developed in order to account for local effects in both space and time. An efficient model calibration approach is proposed for this statistical technique. Using a 19-year set of house price data in London from 1980 to 1998, empirical results from the application of GTWR to hedonic house price modeling demonstrate the effectiveness of the proposed method and its superiority to the traditional GWR approach, highlighting the importance of temporally explicit spatial modeling

The Role of Local Communities and Well-Being in UNESCO World Heritage Site Conservation: An Analysis of the Operational Guidelines, 1994–2019

UNESCO’s world heritage program aims to protect sites of cultural and natural heritage worldwide. Issues of local communities and well-being have been given increasing attention by heritage conservation scholars, but a systemic review of UNESCO guidelines has not been performed. Here, we examine the evolution of the ‘Operational Guidelines for the Implementation of the World Heritage Convention,’ documents representing the heritage conservation policies of UNESCO over the period 1994–2019. Using keyword analysis and document analysis, the findings show evidence of an increasing emphasis on local communities, growing primarily since 2005. However, the theme of well-being only first emerged in the operational guidelines in 2019. Political, economic, and environmental challenges idiosyncratic to specific places often complicate the role of local communities and well-being in heritage conservation priorities. Future research should investigate the potential implementation and implications of these changes for the guidelines at specific UNESCO world heritage sites.Temple University. College of Liberal ArtsGeography and Urban StudiesTemple University Libraries Open Access Publishing Fund, 2021-2022 (Philadelphia, Pa.

Enhancing spatial accuracy of mobile phone data using multi-temporal dasymetric interpolation

Novel digital data sources allow us to attain enhanced knowledge about locations and mobilities of people in space and time. Already a fast-growing body of literature demonstrates the applicability and feasibility of mobile phone-based data in social sciences for considering mobile devices as proxies for people. However, the implementation of such data imposes many theoretical and methodological challenges. One major issue is the uneven spatial resolution of mobile phone data due to the spatial configuration of mobile network base stations and its spatial interpolation. To date, different interpolation techniques are applied to transform mobile phone data into other spatial divisions. However, these do not consider the temporality and societal context that shapes the human presence and mobility in space and time. The paper aims, first, to contribute to mobile phone-based research by addressing the need to give more attention to the spatial interpolation of given data, and further by proposing a dasymetric interpolation approach to enhance the spatial accuracy of mobile phone data. Second, it contributes to population modelling research by combining spatial, temporal and volumetric dasymetric mapping and integrating it with mobile phone data. In doing so, the paper presents a generic conceptual framework of a multi-temporal function-based dasymetric (MFD) interpolation method for mobile phone data. Empirical results demonstrate how the proposed interpolation method can improve the spatial accuracy of both night-time and daytime population distributions derived from different mobile phone data sets by taking advantage of ancillary data sources. The proposed interpolation method can be applied for both location- and person-based research, and is a fruitful starting point for improving the spatial interpolation methods for mobile phone data. We share the implementation of our method in GitHub as open access Python code.Peer reviewe

Understanding family experiences as a means for developing relevant curriculum for children in a pre-kindergarten classroom.

This study examined the households of three preschool students and their families. The study consisted of three main areas of study. One area of investigation was the personal interviews relating to family histories, educational histories and work histories of the family (three lower middle income families). Another area was the sociodramatic play development of the children. The last area of investigation was the home inventory of the living environment of the children. The information gathered from this study was then used to help create a more appropriate child centered curriculum for these students

“How Are We Refocusing Our Lives on God?”: Implementing the Lenten Vision of Sacrosanctum Concilium on a High School Campus

In many Catholic high schools, students discuss Lent with a focus on their actions associated with penance, fasting and almsgiving as a self-denial Olympics without understanding the true purpose. This causes students to robotically move through the motions of Lent instead of internalizing it as a period of preparation for Baptism and penance. This paper will propose a program, for the Catholic high school setting, on how to implement the Second Vatican Council’s vision of Lent, as outlined in Sacrosanctum Concilium. The paper begins by exploring the history and development of Lent throughout the centuries. It then examines the twofold characteristics of Lent as outlined in Sacrosanctum Concilium as preparation for Baptism as well as a period of penance. After analyzing the two characteristics in the constitution, I examine how they are operationalized in the Rite of Christian Initiation for Adults (RCIA) into the presentations and Scrutinies. Next, I propose a seven-week Lenten program on how to better implement the Council\u27s vision of Lent at a Catholic high school. This will be implemented by discussing a different theme every week based on the order and content of the presentations and Scrutinies as outlined by the RCIA. This program will refocus students’ Lenten observance as a period of preparation and calls for more research into how to bridge the program into the celebration of Easter. This will lead conversations in the classrooms and halls away from “What are you giving up?” to “How are we refocusing our lives on God?

A framework for interpolating scattered data using space-filling curves

The analysis of spatial data occurs in many disciplines and covers a wide variety activities. Available techniques for such analysis include spatial interpolation which is useful for tasks such as visualization and imputation. This paper proposes a novel approach to interpolation using space-filling curves. Two simple interpolation methods are described and their ability to interpolate is compared to several interpolation techniques including natural neighbour interpolation. The proposed approach requires a Monte-Carlo step that requires a large number of iterations. However experiments demonstrate that the number of iterations will not change appreciably with larger datasets

Spatiotemporal patterns of population in mainland China, 1990 to 2010

According to UN forecasts, global population will increase to over 8 billion by 2025, with much of this anticipated population growth expected in urban areas. In China, the scale of urbanization has, and continues to be, unprecedented in terms of magnitude and rate of change. Since the late 1970s, the percentage of Chinese living in urban areas increased from ~18% to over 50%. To quantify these patterns spatially we use time-invariant or temporally-explicit data, including census data for 1990, 2000, and 2010 in an ensemble prediction model. Resulting multi-temporal, gridded population datasets are unique in terms of granularity and extent, providing fine-scale (~100 m) patterns of population distribution for mainland China. For consistency purposes, the Tibet Autonomous Region, Taiwan, and the islands in the South China Sea were excluded. The statistical model and considerations for temporally comparable maps are described, along with the resulting datasets. Final, mainland China population maps for 1990, 2000, and 2010 are freely available as products from the WorldPop Project website and the WorldPop Dataverse Repository

Superfund, Hedonics, and the Scales of Environmental Justice

Environmental justice (EJ) is prominent in environmental policy, yet EJ research is plagued by debates over methodological procedures. A well-established economic approach, the hedonic price method, can offer guidance on one contentious aspect of EJ research: the choice of the spatial unit of analysis. Environmental managers charged with preventing or remedying inequities grapple with these framing problems. This article reviews the theoretical and empirical literature on unit choice in EJ, as well as research employing hedonic pricing to assess the spatial extent of hazardous waste site impacts. The insights from hedonics are demonstrated in a series of EJ analyses for a national inventory of Superfund sites. First, as evidence of injustice exhibits substantial sensitivity to the choice of spatial unit, hedonics suggests some units conform better to Superfund impacts than others. Second, hedonic estimates for a particular site can inform the design of appropriate tests of environmental inequity for that site. Implications for policymakers and practitioners of EJ analyses are discussed