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DTSTART:20240310T030000
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BEGIN:VEVENT
DTSTAMP:20240126T154523Z
UID:AEA65A40-5AF4-4DB3-892D-A43AD01B036F
DTSTART;TZID=America/New_York:20240119T123000
DTEND;TZID=America/New_York:20240119T133000
DESCRIPTION:Measuring electricity access is an expensive and difficult unde
 rtaking\, fraught with error and missingness. Leveraging computational ana
 lysis of remotely sensed data across thousands of nights\, we generate ind
 icators of electricity poverty across the globe at the settlement level\, 
 improving spatial resolution and filling in temporal gaps. We demonstrate 
 the reliability and validity of these classifications against ground-based
  surveys at multiple scales. We estimate the energy poor population is 1.1
 7 billion\, 60% higher than the official global estimate of 733 million la
 cking electricity access. Most of the world’s energy poor live in areas 
 that are more remote\, less densely populated\, and more rugged than energ
 y abundant areas. The results clarify the obstacles that impede equitable 
 access to sustainable and affordable energy and provide new data to improv
 e the targeting of solutions to address energy poverty across the world.\n
 \nCo-sponsored by: Dr Wencong Su\n\nSpeaker(s): Brian Min\, \n\nAgenda: \n
 Main Event is from 12\;30 PM to 1\;30 PM\n\nThus attending in person - ref
 reshments will be provided.\n\n4901 Evergreen Rd\, Dearborn\, Michigan\, U
 nited States\, 48128\, Virtual: https://events.vtools.ieee.org/m/400643
LOCATION:4901 Evergreen Rd\, Dearborn\, Michigan\, United States\, 48128\, 
 Virtual: https://events.vtools.ieee.org/m/400643
ORGANIZER:sharan.kalwani@ieee.org
SEQUENCE:31
SUMMARY:A Global Survey of Energy Poverty from Space
URL;VALUE=URI:https://events.vtools.ieee.org/m/400643
X-ALT-DESC:Description: <br /><p>Measuring electricity access is an expensi
 ve and difficult undertaking\, fraught with error and missingness. Leverag
 ing computational analysis of remotely sensed data across thousands of nig
 hts\, we generate indicators of electricity poverty across the globe at th
 e settlement level\, improving spatial resolution and filling in temporal 
 gaps. We demonstrate the reliability and validity of these classifications
  against ground-based surveys at multiple scales. We estimate the energy p
 oor population is 1.17 billion\, 60% higher than the official global estim
 ate of 733 million lacking electricity access. Most of the world&rsquo\;s 
 energy poor live in areas that are more remote\, less densely populated\, 
 and more rugged than energy abundant areas. The results clarify the obstac
 les that impede equitable access to sustainable and affordable energy and 
 provide new data to improve the targeting of solutions to address energy p
 overty across the world.</p><br /><br />Agenda: <br /><p>Main Event is fro
 m 12\;30 PM to 1\;30 PM</p>\n<p>Thus attending in person - refreshments wi
 ll be provided.</p>
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