Spatial Analysis & Techniques eJournal最新文献

{"title":"A Human Impacts-Driven Framework for Quantifying Disaster-Dependent Social Vulnerability: A Case Study of Hurricane Maria in Puerto Rico","authors":"Wilmer Martínez, T. Carvalhaes, Petar Jevtic, T. Agami Reddy","doi":"10.2139/ssrn.3878513","DOIUrl":"https://doi.org/10.2139/ssrn.3878513","url":null,"abstract":"We propose a supervised learning approach to statistically quantify the magnitude of extreme events on vulnerable communities using publicly available panel data directly reflective of the different dimensions and manifestations of social suffering. The manifestations along these dimensions include suicides, substance abuse, excess mortality, unemployment, and others. Our modified treatment-effect model allows counterfactual baseline conditions to be posited from which a quantitative multi-faceted measure of social suffering can be determined. This capability is greatly beneficial to policymakers who have to allocate scarce resources to strengthen a geographic region consisting of several administrative units. Our work represents a distinct deviation from the established approach of assessing social vulnerabilities of communities subject to extraordinary events that rely on composite indices (such as SoVI) based on published census data. Recent academic research points out that such approaches are ad hoc, do not consider the dynamics of actual events, and lack formal validation of the variables and models. Further, there is an ongoing challenge for indices to be validated with dependent variables that proxy realizations of vulnerability. We describe the supervised treatment-effect approach in detail and illustrate its applicability using panel data encompassing the 2017 Hurricane Maria event across various municipalities in Puerto Rico. Our statistical modeling methodology stands apart since it explicitly and more realistically captures the social hardships of the actual event as manifested by different published panel data indicators. Our methodology is flexible enough to accommodate individual preferences of different stakeholders in how they assign importance to different manifestations of social hardship.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disaster Vulnerability","authors":"Lisa Grow Sun, B. Daniels, D. Spencer, C. Sloan, Natalie J. Blades, Teresa Gomez","doi":"10.2139/ssrn.3807674","DOIUrl":"https://doi.org/10.2139/ssrn.3807674","url":null,"abstract":"Vulnerability drives disaster law—defining its successes and illustrating its failures. Although understanding vulnerability is critical to disaster law and scholarship, the literature lacks both an overarching analysis of the different aspects of vulnerability and a nuanced examination of the factors that shape disaster outcomes. This paper attempts to fill those holes.Despite its centrality to disaster law and policy, vulnerability often lurks in the shadows of a disaster, evident only once the worst is past and the bodies have been counted. The COVID-19 pandemic is a notable exception to this historical pattern: from the beginning of the pandemic, it has been clear that the virus poses different risks to different people, depending on different vulnerability variables. This most recent pandemic experience thus provides a useful vantage point for considering vulnerability in a more nuanced way and for illuminating how a data-driven approach to vulnerability could improve disaster policy more generally.Drawing on new empirical data, as well as experience from past disasters, we introduce and develop three dimensions of vulnerability and their implications for policymakers. First, we explore the geography of vulnerability. Using statistical analysis and GIS mapping, our team of public health, statistics, and legal experts develops perhaps the most sophisticated and detailed empirical tool ever deployed to understand disaster vulnerability—an innovative COVID-19 vulnerability index that draws on a rich dataset and uses statistical modeling of case fatality rates to accurately identify the country’s most vulnerable counties. We then demonstrate how this vulnerability index could have been used to inform two critical and contentious policy decisions that occupied decision-makers from the onset of the pandemic: mask mandates and voter accommodations during the 2020 elections. Building upon the lessons of COVID-19, we then show how similar modeling and thinking could make disaster management more proactive—better able to anticipate needs and prioritize disaster mitigation and response resources.Incorporating insights from our exploration of the geographic dimension of vulnerability, we then explore a second aspect of disaster vulnerability: competing or conflicting vulnerabilities. These are situations in which policymakers must navigate choices that require prioritizing one vulnerable group’s needs over another or one aspect of a group’s vulnerability over another. To illustrate these issues, we consider two other important problems that have challenged policymakers during the pandemic: school closures and vaccine distribution.Finally, we explore political vulnerability. This analysis encompasses a variety of ways that disasters make already vulnerable groups even more vulnerable to certain kinds of harms, including political neglect, stigmatization, disenfranchisement, displacement, and other forms of exploitation. In particular, we consider how vul","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125541379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Regulating Big Tech in Europe: Why, so What, and How Understanding Their Business Models and Ecosystems Can Make a Difference","authors":"M. Jacobides","doi":"10.2139/ssrn.3765324","DOIUrl":"https://doi.org/10.2139/ssrn.3765324","url":null,"abstract":"Europe is currently undertaking a frenzy of regulatory action against Big Tech. But the question arises: what will be the actual impact on Big Tech, and how will it actually improve the tech ecosystem in Europe? On the one hand, it is clear that the rise of very large digital platforms and their ecosystems raises new regulatory challenges, as existing tools are unfit to grapple with true power in the digital economy. On the other hand, it also is clear that geopolitics is driving much of the debate, with the EU reacting with profound scepticism to firms based in the USA, which also engage in unfair practices. How do these two driving forces combine to drive regulatory action? What are the key issues raised, and where do we see the power of Big Tech (and in particular, GAF – Google, Apple and Facebook) manifest in Europe? What are the current regulations likely to achieve, and how much might GAF be affected? While other BigTech firms like Amazon surely deserve a closer look, we focused on firms with a disproportionate impact on media- and focus on information. This white paper draws on an extensive project that engaged senior leaders in policy, politics, tech, industry, regulation, consultancies and academia, and also involved deep dives into how the current regulatory fervour might affect GAF, focusing on their business models and their ecosystems of complementors. We report on our expectation for the impact of regulations on GAF: limited, yet not trivial. We argue that the current regulatory discussion is missing two vital elements: an understanding of Big Tech business models, and an appreciation of how regulation will affect the broader ecosystem, both of which we review. We then consider what principles should underpin regulation, stressing the role of business models, monetization and the use of data. We argue that Europe’s best interests lie in a level playing field on the regulatory side, which allows fair competition between participants from Europe, as well as the US and China, coupled with a solid set of principles on business models. Finally, we suggest that neither competition policy nor geopolitically motivated restrictions will suffice to address the real malaise underlying European tech: proactive strategies from industrial leaders alongside a thriving and open ecosystem of tech participants will be equally important in building the foundations for future success.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114746938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Notions of Climate-Change-Related Uncertainty Among Stakeholders in the Coastal Region of Krummhörn, East Frisia, Germany","authors":"Marcus Agthe, Andreas Ernst, Stefan Baumgärtner","doi":"10.2139/ssrn.3725515","DOIUrl":"https://doi.org/10.2139/ssrn.3725515","url":null,"abstract":"Climate change impacts and adaptation measures are subject to various uncertainties. In communication and decision-making, these uncertainties need to be adequately considered. However, uncertainty is a conceptually multifaceted issue, a plethora of connotations and meanings surround the term, and most of that is not explicit but only implicit. We examined the notions of climate-change-related uncertainties actually held by stakeholders – from government and administration, water management, agriculture, tourism, nature conservation, education, and the insurance industry – in the coastal region of Krummhörn, East Frisia, Germany. We employed qualitative, semi-structured in-depth interviews, covering general as well as context-specific aspects of uncertainty. To analyze the interviews, we employed qualitative content analysis, using MAXQDA software and deductively and inductively formed codes. One main finding was the large heterogeneity in the responses: different stakeholders hold widely differing notions of uncertainty – across and even within sectors. Most stakeholders do not normally employ one of the established scientific concepts of uncertainty, but hold a normative perspective on uncertainty which is strongly based on subjective valuation. When dealing with objective information on the quantification of uncertainty, such as probabilities, most stakeholders are inconsistent. The particular perspective on uncertainty is strongly related to the specific topic. On a meta-level, we found that all stakeholders were unfamiliar with talking about uncertainty and had difficulties expressing their ideas in language. Overall, our study confirmed that uncertainty is a contested, pluralistic, and complex phenomenon, which is looked at from different perspectives by different stakeholders. We conclude that the communication of uncertainty at the science–society interface requires particular attention, as the notions of uncertainty held by stakeholders are not always in line with the established scientific concepts of uncertainty.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124208369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical Measures of Park Use in American Cities, and the Demographic Biases of Spatial Models","authors":"J. Saxon","doi":"10.2139/ssrn.3502949","DOIUrl":"https://doi.org/10.2139/ssrn.3502949","url":null,"abstract":"City planners have a professional and ethical responsibility to provide public goods equitably. Parks improve mental and physical health by nurturing social cohesion and enabling physical activity. So who gets parks? Park access has traditionally been evaluated using constructed variables of potential access: distance buffers or gravity models. These models have major limitations: they ignore commutes and other more intricate mobility behaviors. To address these issues, I propose a nationally scalable,empirical measure of realized use. Using a dataset of smartphone locations, I identify visits to parks in the twenty largest American cities. I use these data to calibrate existing models, and then contrast the models with realized use. The traditional models are not simply imprecise; they systematically over-estimate realized access by minority populations. In other words, they understate inequity. On the other hand,the new data come with substantial challenges. They are a convenience sample, biased towards wealthier,whiter populations. While these biases appear to be moderate, continued work with these and similar data will require continued attention to the sample frame.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123399006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Application of the Post-Typhoon Damage Model (Ṫ-Model) to The Typhoon Hagibis in Japan (October 2019)","authors":"Mario Arturo Ruiz Estrada, Donghyun Park, Michitaka Umemoto, J. Sapkota","doi":"10.2139/ssrn.3487478","DOIUrl":"https://doi.org/10.2139/ssrn.3487478","url":null,"abstract":"We introduce a new tool to evaluate the human and economic impact of typhoons. The new applicable tool is the “post-typhoon damage Model (Ṫ-Model)”. The Ṫ-Model is based on the application of six indicators, namely (i) post-typhoon damage ratio (Ṫ(i)-Ratio); (ii) post-typhoon damage total value (Ṫ(j)-Total Value); (iii) post-typhoon damage balance (Ṫ(j)-Balance); (iv) post-typhoon damage marginal rate (Ṫ(j)-Marginal Rate); (v) post-typhoon damage critical point (Ṫ(j)-Critical Point); and (vi) post-typhoon damage surface (Ṫ(j)-Surface). The measurement of the six indicators is based, in turn, on simultaneously evaluating nine sub-variables (svi). The nine sub-variables are all defined to be within a perimeter of 10 km2. The sub-variables are number of deaths (sv1), total number of missing people (sv2), total number of sick people (sv3), total number of people with minor injuries (sv4), total number of critically injured people (sv5), total number of people evacuated(sv6), total number of people with access to water and electricity (sv7), total number of people with access to food and water (sv8), and total number of hospitalized people (sv9). The central objective of the Ṫ-Model is to evaluate the human and economic impact from a typhoon. The model generates a Microsoft excel worksheet that inputs, stores, classifies, calculates, and visualizes a typhoon’s human and economic damage within a perimeter of 10 km2. Finally, the Ṫ-Model was applied to the Hagibis typhoon which hit Japan in October 2019.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133502251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building(s and) Cities: Delineating Urban Areas with a Machine Learning Algorithm","authors":"Daniel Arribas-Bel, M. García-López, Elisabet Viladecans-Marsal","doi":"10.2139/ssrn.3685818","DOIUrl":"https://doi.org/10.2139/ssrn.3685818","url":null,"abstract":"This paper proposes a novel methodology for delineating urban areas based on a machine learning algorithm that groups buildings within portions of space of sufficient density. To do so, we use the precise geolocation of all 12 million buildings in Spain. We exploit building heights to create a new dimension for urban areas, namely, the vertical land, which provides a more accurate measure of their size. To better understand their internal structure and to illustrate an additional use for our algorithm, we also identify employment centers within the delineated urban areas. We test the robustness of our method and compare our urban areas to other delineations obtained using administrative borders and commuting-based patterns. We show that: 1) our urban areas are more similar to the commuting-based delineations than the administrative boundaries but that they are more precisely measured; 2) when analyzing the urban areas’ size distribution, Zipf’s law appears to hold for their population, surface and vertical land; and 3) the impact of transportation improvements on the size of the urban areas is not underestimated.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122769424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Highly Disaggregated Land Unavailability","authors":"Chandler Lutz, Benjamin M. Sand","doi":"10.2139/ssrn.3478900","DOIUrl":"https://doi.org/10.2139/ssrn.3478900","url":null,"abstract":"We use new large-scale data techniques and comprehensive high resolution satellite imagery for the contiguous United States to construct novel datasets that capture the geographic determinants of house prices and housing supply: The percentage of undevelopable land – Land Unavailability – and its complement, buildable land. Our Land Unavailability measure expands on the popular proxy from Saiz (2010) by:<br><br>(1) using higher resolution satellite imagery from the USGS; <br><br>(2) more accurate geographic boundaries; and <br><br>(3) multiple levels of disaggregation. <br><br>Using highly disaggregated data we show that Land Unavailability is uncorrelated with housing demand proxies, validating Land Unavailability as an instrument for house prices; that the geographic components of Land Unavailability, especially in combination with modern machine learning techniques, provide substantial incremental predictive power for house prices; and previous studies that employed limited land unavailability datasets underestimated the impact of house prices on unemployment during the Great Recession by 30%. With our buildable land dataset we then test the supply side speculation theory that aims to explain the previously puzzling large house price growth in traditionally elastic housing markets. In line with theory, results document that housing markets with intermediate amounts of buildable land, those that are elastic in the short run but plausibly inelastic in the long run, experienced abnormally large house price growth during the 2000s.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129445229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trans-Boundary Air Pollution Spillovers: Physical Transport and Economic Costs by Distance","authors":"Shihe Fu, V. Viard, Peng Zhang","doi":"10.2139/ssrn.3408976","DOIUrl":"https://doi.org/10.2139/ssrn.3408976","url":null,"abstract":"The economic costs of trans-boundary pollution spillovers versus local effects is a necessary input in evaluating centralized versus decentralized environmental policies. Directly estimating these for air pollution is difficult because spillovers are high-frequency and vary with distance while economic outcomes are usually measured with low-frequency and local pollution is endogenous. We develop an approach to quantify local versus spillover effects as a flexible function of distance utilizing commonly-available pollution and weather data. To correct for the endogeneity of pollution, it uses a mixed two-stage least squares method that accommodates high-frequency (daily) pollution data and low-frequency (annual) outcome data. This avoids using annual pollution data which generally yields inefficient estimates. We apply the approach to estimate spillovers of particulate matter smaller than 10 micrograms (PM10) on manufacturing labor productivity in China. A one μg/m3 annual increase in PM10 locally reduces the average firm’s annual output by CNY 45,809 while the same increase in a city 50 kilometers away decreases it by CNY 16,248. The spillovers decline quickly to CNY 2,847 at 600 kilometers and then slowly to zero at about 1,000 kilometers. The results suggest the need for supra-provincial environmental policies or Coasian prices quantified under the approach.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"63 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120996154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nexus of Economic Activities and Haulage Transportation: An Ethnographic Perspective from Potiskum (Yobe State) Nigeria","authors":"Ali A. Hassan, Yunusa Hassan, U. M. Jambo","doi":"10.2139/ssrn.3462388","DOIUrl":"https://doi.org/10.2139/ssrn.3462388","url":null,"abstract":"Transportation industry does not only facilitate easy movement of people and goods between two geographical locations, it also aids the growth and development of it respective region. The present study investigate the economic prospective of grain market as well as interrelationship between the haulage transportation and the economic activities in Potiskum grain market. The study depends on both primary and secondary data. Primary data were generated using individual depth interview while the secondary data were collected from published and unpublished documents and, literatures from various peer reviewed studies. The study uncovered that the strategic geographical location of Potiskum offered a great advantage for the grain market development. However, the study unfold that the availability of many heavy duty trucks in this region greatly contributes toward the growth and development of the market as well as the economic activities through provision of easy medium of transportation both inward and outward of the region. Lastly, the study recommends the provision of modern parking space for heavy duty trucks as well as to facilitate easy passage within the market terrain.","PeriodicalId":293246,"journal":{"name":"Spatial Analysis & Techniques eJournal","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124471644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}