BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//talks.staging.osgeo.org//foss4g-2022//talk//R8FHVA
BEGIN:VTIMEZONE
TZID:CET
BEGIN:STANDARD
DTSTART:20001029T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000326T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-foss4g-2022-R8FHVA@talks.staging.osgeo.org
DTSTART;TZID=CET:20220826T093000
DTEND;TZID=CET:20220826T100000
DESCRIPTION:Hey everyone\, my name is Saheel Ahmed. I work as a senior data
  scientist at Blue Sky Analytics. We are a climate tech startup primarily 
 focused on creating environmental datasets for better monitoring and clima
 te risk assessment for various stakeholders across the globe. To achieve t
 his\, we are leveraging the potential of geospatial analytics by creating 
 a catalogue of comprehensive and accurate climate data to drive sustainabl
 e decision-making. And all this is only possible because of the open-sourc
 e tools & knowledge made publicly by the good folks organising the event.\
 n\nGreenhouse gas (GHG) emissions from biomass burning (which includes the
  combustion of forests\, savannas\, and croplands) play an important role 
 in regional air quality\, global climate change\, and human health. In the
  year 2021\, all the continents except Antarctica witnessed major wildfire
 s. These enormous blazes some the size of a small country aren’t just de
 stroying native forests and vulnerable animal species. They’re also rele
 asing billions of tons of greenhouse gases into the atmosphere\, potential
 ly accelerating global warming and leading to even more fires. Accurate as
 sessment of biomass burning emissions is paramount to understanding and mo
 delling global climate change.\n\nBy combining open-source tools with geos
 patial data\, we present a global dataset that estimates the total GHG emi
 ssions due to biomass burning globally. We achieved this by linking satell
 ite-based fire observations\, aerosol optical depth (AOD)\, and vegetation
  type (based on land cover classification) to directly estimate how much c
 arbon dioxide (CO2)\, methane (CH4)\, and nitrous oxide (N2O) were emitted
  from each fire. We conducted further analysis of estimated emissions by c
 omparing our estimates with existing datasets from NASA's global fire emis
 sions database and ESA's Copernicus global fire assimilation system. Overa
 ll\, our estimates agree well against both of these sources with an R2 sco
 re of 0.91\, 0.71\, and MAE score of 9\, 14 MtCO2e/yr against GFEDv4.1s an
 d GFASv1.2 respectively across 245 nations between 2015-2020. The dataset 
 includes country-level estimates of gross GHG emissions across different v
 egetation types such as forest\, cropland\, shrubland\, and grassland for 
 the last 5 years.\n\nThe dataset is currently a work in progress as we aim
  to add more features such as covering other landcover types\, ground trut
 h alternatives. The dataset and its documentation are available at https:/
 /github.com/blueskyanalytics/get-started. The dataset is also our contribu
 tion to the global coalition Climate Trace (https://www.climatetrace.org/)
 \, an independent group for monitoring & publishing GHG emissions across d
 ifferent sectors.
DTSTAMP:20260404T020735Z
LOCATION:Room 4
SUMMARY:Use of open source tools to estimate global GHG emissions. - Saheel
  Ahmed
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/R8FHVA/
END:VEVENT
END:VCALENDAR