<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-19T15:25:06Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/139973" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/139973</identifier><datestamp>2022-02-08T03:29:26Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Zheng, Siqi</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Williams, Matías</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Department of Urban Studies and Planning</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2022-02-07T15:16:31Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2022-02-07T15:16:31Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued">2021-09</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="submitted">2021-12-06T19:35:22.953Z</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/139973</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract">The objectives of this thesis project are: (1) how to use nightlight data to track changing patterns of economic activities within cities worldwide, and (2) examine intra-city spatial consequences of the COVID-19 pandemic and whether these patterns differ across them. Informed by existing literature, I propose a cluster analysis using two groups, residential activities and work and play activities, to further understand the local consequences of the COVID-19 pandemic. Using Geographic Information Systems (GIS) and Graph Theory, I create metrics to compare the impact across several cities worldwide. The results of this thesis indicate that the work and play activities were more affected than the residential activities. However, this impact was not evenly distributed spatially.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree">M.C.P.</dim:field>
   <dim:field mdschema="dc" element="publisher">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights">In Copyright - Educational Use Permitted</dim:field>
   <dim:field mdschema="dc" element="rights">Copyright retained by author(s)</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri">https://rightsstatements.org/page/InC-EDU/1.0/</dim:field>
   <dim:field mdschema="dc" element="title">Measuring the COVID-19 Shock from Outer Space: Local Economic Vibrancy in 15 Global Cities</dim:field>
   <dim:field mdschema="dc" element="type">Thesis</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="mimetype">application/pdf</dim:field>
   <dim:field mdschema="mit" element="thesis" qualifier="degree">Master</dim:field>
   <dim:field mdschema="thesis" element="degree" qualifier="name">Master in City Planning</dim:field>
   <dim:field mdschema="dspace" element="entity" qualifier="type">Publication</dim:field>
   <dim:field mdschema="others" element="access-status">unknown</dim:field>
   <dim:field mdschema="others" element="access-status">unknown</dim:field>
   <dim:field mdschema="cerif" element="openaire" authority="" confidence="-1">&lt;Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="a3f905dc-75d9-4518-95d2-3181827aa3b2">
	&lt;Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843&lt;/Type>
   	&lt;Title>Measuring the COVID-19 Shock from Outer Space: Local Economic Vibrancy in 15 Global Cities&lt;/Title>
   	&lt;PublishedIn>
    	&lt;Publication>
      	&lt;/Publication>
   	&lt;/PublishedIn>
   	&lt;PublicationDate>2021-09&lt;/PublicationDate>
   	&lt;Authors>
      	&lt;Author>
        	&lt;DisplayName>Williams, Matías&lt;/DisplayName>
         	&lt;Affiliation>
         		&lt;OrgUnit>
         		&lt;/OrgUnit>
         	&lt;/Affiliation>
      	&lt;/Author>
	&lt;/Authors>
   	&lt;Editors>
	&lt;/Editors>
    &lt;Publishers>
        &lt;Publisher>
            &lt;DisplayName>Massachusetts Institute of Technology&lt;/DisplayName>
            &lt;OrgUnit />
        &lt;/Publisher>
    &lt;/Publishers>
    &lt;License>https://rightsstatements.org/page/InC-EDU/1.0/&lt;/License>
   	&lt;Abstract>The objectives of this thesis project are: (1) how to use nightlight data to track changing patterns of economic activities within cities worldwide, and (2) examine intra-city spatial consequences of the COVID-19 pandemic and whether these patterns differ across them. Informed by existing literature, I propose a cluster analysis using two groups, residential activities and work and play activities, to further understand the local consequences of the COVID-19 pandemic. Using Geographic Information Systems (GIS) and Graph Theory, I create metrics to compare the impact across several cities worldwide. The results of this thesis indicate that the work and play activities were more affected than the residential activities. However, this impact was not evenly distributed spatially.&lt;/Abstract>
	&lt;Access xmlns="http://purl.org/coar/access_right" 
    >
    &lt;/Access>
&lt;/Publication>
</dim:field>
</dim:dim>
</metadata></record></GetRecord></OAI-PMH>