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UID:pretalx-foss4g-2024-GSAVCT@talks.staging.osgeo.org
DTSTART;TZID=-03:20241204T164500
DTEND;TZID=-03:20241204T171500
DESCRIPTION:Community standards are specifications that are created through
  informal organization and are then widely adopted by a larger group. The 
 STAC specification and Cloud-Optimized GeoTIFFs are examples of community 
 specifications that have become de facto standards for geospatial interope
 rability. This talk will examine how the process of developing community s
 tandards differs from traditional standards development and how to drive a
 doption. Numerous examples of successful community standards will be prese
 nted.\n\nIn addition\, we will provide a case study of a current effort - 
 that of STAPI - a specification for satellite tasking\, or more specifical
 ly\, an API for how users can order data from the future from satellite pl
 atforms. We have been spearheading an effort to develop such a specificati
 on and after two sprints we presented at the last FOSS4G in Kosovo.  This 
 prompted a third sprint in Europe\, bringing together an even larger commu
 nity.  Working with government groups\, commercial satellite operators\, a
 nd data integrators\, these sprints have worked toward developing a specif
 ication as well as implementations for several commercial providers\, as w
 ell as ordering APIs for public datasets.\n\nThis talk will dive into what
  worked for STAC and other community standards and how we are taking those
  lessons to develop a standardized way for collecting future geospatial da
 ta.
DTSTAMP:20260516T140317Z
LOCATION:Room II
SUMMARY:Community Standards and Satellite Tasking - Matthew Hanson\, Jarret
 t Keifer
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/GSAVCT/
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UID:pretalx-foss4g-2024-W898HE@talks.staging.osgeo.org
DTSTART;TZID=-03:20241205T100000
DTEND;TZID=-03:20241205T103000
DESCRIPTION:Over the past few years\, the STAC community has witnessed an h
 uge increase in adoption and implementation across various sectors. With i
 ts focus on interoperability and extensibility\, STAC has successfully add
 ressed the long-standing challenge of data fragmentation in the geospatial
  domain. By providing a unified framework for describing and accessing geo
 spatial assets\, STAC has empowered users to effortlessly discover and ana
 lyze vast amounts of Earth observation data.\n\nMoreover\, the emergence o
 f an open-source ecosystem around STAC has been instrumental in its widesp
 read adoption. A myriad of tools and libraries have been developed\, enabl
 ing seamless integration of STAC into existing geospatial workflows. These
  tools encompass data providers\, data processors\, visualization platform
 s\, and more\, fostering a vibrant community-driven approach to solving co
 mplex geospatial challenges.\n\nThis presentation will provide insights in
 to the current state of the STAC specification\, including changes in 1.1 
 and the current set of STAC extensions with guidance on the use of extensi
 ons based on their maturity. In addition\, we will provide an overview of 
 the current STAC ecosystem\, with a focus on the Python projects available
  in the stac-utils GitHub organization.
DTSTAMP:20260516T140317Z
LOCATION:Room I
SUMMARY:The State of STAC - Matthew Hanson
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/W898HE/
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UID:pretalx-foss4g-2024-3EWQR9@talks.staging.osgeo.org
DTSTART;TZID=-03:20241205T111500
DTEND;TZID=-03:20241205T114500
DESCRIPTION:Every geospatial project begins with a quest for answers. Large
  Language Models (LLMs) are revolutionizing how we can directly understand
  user needs through techniques like natural language to data structure con
 version. Over the couple years\, we have been exploring how AI could be us
 ed for working with geospatial data. What started as figuring out how to u
 se natural language to make STAC queries to find public data has led to mu
 ch more\, including natural language geocoding to contextual image searchi
 ng of public data such as NAIP and Sentinel-2.\n\nIn this talk we will exp
 lore how AI can be used to help automate some of geospatial’s most tedio
 us tasks using open data\, and how open vision models can be combined to c
 reate powerful tools for search & discovery of earth imagery.\n\nThis talk
  will include an overview of AI for use in geospatial analysis\, with a fo
 cus on using open data and open models. We will show some live demos to cr
 eate accurate AOIs with natural language\, as well as for advanced searchi
 ng of landscape features in public datasets. Additionally we will give an 
 overview of techniques like Retrieval Augmented Generation and LLM Agents 
 and the potential for how these may be used to transform geospatial data s
 cience.
DTSTAMP:20260516T140317Z
LOCATION:Room I
SUMMARY:GeoAI for all: Helping answer the most common questions in geo - Ma
 tthew Hanson
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/3EWQR9/
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