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UID:pretalx-foss4g-2022-7WJNCB@talks.staging.osgeo.org
DTSTART;TZID=CET:20220824T141500
DTEND;TZID=CET:20220824T144500
DESCRIPTION:GeoPandas is one of the core packages in the Python ecosystem t
 o work with geospatial vector data. By combining the power of several open
  source geo tools (GEOS/Shapely\, GDAL/fiona\, PROJ/pyproj) and extending 
 the pandas data analysis library to work with geographic objects\, it is d
 esigned to make working with geospatial data in Python easier. GeoPandas e
 nables you to easily do operations in Python that would otherwise require 
 desktop applications like QGIS or a spatial database such as PostGIS.\n\nT
 his talk will give an overview of recent developments in the GeoPandas com
 munity\, both in the project itself as in the broader ecosystem of package
 s on which GeoPandas depends or that extend GeoPandas. We will highlight s
 ome changes and new features in recent GeoPandas versions\, such as the ne
 w interactive explore() visualisation method\, improvements in joining bas
 ed on proximity\, better IO options for PostGIS and Apache Parquet and Fea
 ther files\, and others. But some of the important improvements coming to 
 GeoPandas are happening in other packages. The Shapely 2.0 release is near
 ing completion\, and will provide fast vectorized versions of all its geos
 patial functionalities. This will help to substantially improve the perfor
 mance of GeoPandas. In the area of reading and writing traditional GIS fil
 es using GDAL\, the pyogrio package is being developed to provide a speed-
 up on that front. Another new project is dask-geopandas\, which is merging
  the geospatial capabilities of GeoPandas with the scalability of Dask. Th
 is way\, we can achieve parallel and distributed geospatial operations.
DTSTAMP:20260403T193900Z
LOCATION:Room Limonaia
SUMMARY:State of GeoPandas and friends - Joris van den Bossche
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/7WJNCB/
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UID:pretalx-foss4g-2022-BSY973@talks.staging.osgeo.org
DTSTART;TZID=CET:20220825T100000
DTEND;TZID=CET:20220825T100500
DESCRIPTION:The Apache Arrow (https://arrow.apache.org/) project specifies 
 a standardized language-independent columnar memory format. It enables sha
 red computational libraries\, zero-copy shared memory\, streaming messagin
 g and interprocess communication without serialization overhead\, etc. Now
 adays\, Apache Arrow is supported by many programming languages. \n\nGeosp
 atial data often comes in tabular format\, with one (or multiple) column w
 ith feature geometries and additional columns with feature attributes. Thi
 s is a perfect match for Apache Arrow. Defining a standard and efficient w
 ay to store geospatial data in the Arrow memory layout (https://github.com
 /geopandas/geo-arrow-spec/) can help interoperability between different to
 ols and enables us to tap into the full Apache Arrow ecosystem:\n\n- Effic
 ient\, columnar data formats. Apache Arrow contains an implementation of t
 he Apache Parquet file format\, and thus gives us access to GeoParquet (ht
 tps://github.com/opengeospatial/geoparquet) and functionalities to interac
 t with this format in partitioned and/or cloud datasets.\n- The Apache Arr
 ow project includes several mechanisms for fast data exchange (the IPC mes
 sage format and Arrow Flight for transferring data between processes and m
 achines\; the C Data Interface for zero-copy sharing of data between indep
 endent runtimes running in the same process). Those mechanisms can make it
  easier to efficiently share data between GIS tools such as GDAL and QGIS 
 and bindings in Python\, R\, Rust\, with web-based applications\, etc.\n- 
 Several projects in the Apache Arrow community are working on high-perform
 ance query engines for computing on in-memory and bigger-than-memory data.
  Being able to store geospatial data in Arrow will make it possible to ext
 end those engines with spatial queries.
DTSTAMP:20260403T193900Z
LOCATION:Room 4
SUMMARY:Geospatial and Apache Arrow: accelerating geospatial data exchange 
 and compute - Joris van den Bossche
URL:https://talks.staging.osgeo.org/foss4g-2022/talk/BSY973/
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