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UID:pretalx-foss4g-2022-DUB7EE@talks.staging.osgeo.org
DTSTART;TZID=CET:20220825T141500
DTEND;TZID=CET:20220825T144500
DESCRIPTION:The MapWithAI RapiD editor for OpenStreetMap offers a variety o
 f open data to improve OpenStreetMap. This web-based map editor presents t
 he user with various sources of open data to validate and add to OpenStree
 tMap\, including MapWithAI roads\, Microsoft buildings\, and various open 
 datasets shared via Esri. \n\nIn addition to these past data offerings\, t
 he user can now validate and add sidewalks and crosswalks derived from bot
 h Mapillary street-level imagery\, as well as derived from various organiz
 ations who provide footway open data. Finally\, Mapillary point data deriv
 ed from imagery can also now be verified and directly converted into map d
 ata\, thanks to a more efficient and rapid workflow. \n\nWe will explore a
 ll that open data available in the RapiD editor\, with a specific focus on
  how footways are generated from Mapillary\, validated from open datasets\
 , conflated against existing OpenStreetMap data\, and presented to the use
 r for improved maps of pedestrian walkability.
DTSTAMP:20260404T012002Z
LOCATION:Modulo 0
SUMMARY:Open Data in OpenStreetMap’s RapiD Editor - Christopher Beddow
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/DUB7EE/
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UID:pretalx-foss4g-2022-7UAP8S@talks.staging.osgeo.org
DTSTART;TZID=CET:20220825T153000
DTEND;TZID=CET:20220825T153500
DESCRIPTION:Mapping is time-consuming and requires a high volume of a workf
 orce when it comes to keep maps up to date periodically. This brings the n
 eed of finding alternative approaches to keep maps up to date. Mobile mapp
 ing is the process of collecting geospatial data from a mobile vehicle usi
 ng a 360º camera\, laser scanner\, GPS/IMU positioning system\, and other
  sensors. \n\nMany devices now include a geotag for every photo captured\,
  and GPS accuracy can	have major effects on the quality of street-level im
 agery and derived data. Join us in an exploration of the different accurac
 y levels of GPS-enabled cameras\, where we will take a look at how differe
 nt devices compare\, and what varied levels of GPS accuracy look like both
  for image location and for data extracted using computer vision and struc
 ture from motion.\n\nUnderstanding the differences between devices is an i
 mportant step in planning street-level imagery capture\, as it will align 
 your expectations with the advantages and limitations of the hardware you 
 use. We tested various devices and will share the results of our investiga
 tion\, with the aim of equipping you to capture street-level imagery with 
 the tools and methods that fit your needs.
DTSTAMP:20260404T012002Z
LOCATION:Modulo 0
SUMMARY:The most accurate cameras to generate map data from street-level im
 agery - Christopher Beddow\, Said Turksever\, Edoardo Neerhut
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/7UAP8S/
END:VEVENT
BEGIN:VEVENT
UID:pretalx-foss4g-2022-S99HMM@talks.staging.osgeo.org
DTSTART;TZID=CET:20220826T100000
DTEND;TZID=CET:20220826T103000
DESCRIPTION:Mapillary is the platform that makes street-level images and ma
 p data available to scale and automate mapping. There are many tools avail
 able within Mapillary’s ecosystem\, as well as many real world use cases
  where Mapillary can have an impact. In this talk\, we will give an overvi
 ew of the state of the Mapillary platform in 2022. This will include a loo
 k at compatible camera devices\, upload methods\, data and imagery managem
 ent\, download methods\, integrations\, and stories about users who apply 
 Mapillary to solve a challenge. \n\nYou should walk away from this talk kn
 owing how you want to use Mapillary to improve maps important to you\, and
  what tools you need to get started.\n\nIf you are interested in improving
  OpenStreetMap\, contributing to open data\, capturing imagery in your com
 munity\, or leveraging Mapillary street-level imagery and GIS data into yo
 ur professional work\, this talk is for you. No coding or technical experi
 ence is necessary\, and the tools and features available can be adapted to
  any skill level. Join us!
DTSTAMP:20260404T012002Z
LOCATION:Room Verde
SUMMARY:How to Mapillary - Getting started with Street-level Mapping - Chri
 stopher Beddow
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/S99HMM/
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