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UID:pretalx-foss4g-2024-GSBMGK@talks.staging.osgeo.org
DTSTART;TZID=-03:20241205T121500
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DESCRIPTION:Over the past 30 years\, Argentina has experienced changes in i
 ts agricultural and urban development model that have drastically altered 
 land use practices and patterns. (Palmisano\, 2018\; Pintos and Narodowski
 \, 2012)\n\nThese changes have been associated with flooding in several re
 gions (Pal et al.\, 2021\; Pattison and Lane\, 2012). In particular\, the 
 Lujan River basin has historically experienced extreme events.\n\nIn the g
 lobal scale\, prevails the expansion of capitalism by a process of accumul
 ation by dispossession\,  characterized by land privatization\, expulsion 
 of farmers\, conversion or suppression of rights to the commons (Harvey\, 
 2004).\n\nThe analysis of these changes in landuse requires information ty
 pically obtained from remote sensing\, that is validated and complemented 
 with sampling programs. The development of an updated landuse map is a bas
 ic tool to study territorial phenomena such as flooding events or land use
  change. Such a methodology would allow the information to be compared wit
 h previously collected data at different scales and time periods.\n\nBut g
 eographic information\, its format\, or processing tools do not generally 
 allow for its reuse or improvement\, and are not necessarily openly/freely
  available. This type of data can be considered a digital commons and can 
 be the subject of mercantilization processes. In fact\, publicly produced 
 information and processing tools should be publicly available to enforce k
 nowledge construction. (Arsanjani\, 2015\; Duféal and Noucher 2017).\n\nO
 penStreetMap is the main framework for volunteered geographic information\
 , and because it constitutes a standardized database\, it also allows to b
 e a preferred repository for contributions originating from research progr
 ams of universities and public organizations.. Recently has been registere
 d as a public good by an agency affiliated to the United Nations (https://
 blog.openstreetmap.org/2024/02/05/osm-named-as-a-digital-public-good-by-un
 -affiliated-agency/)\n\nData contributed to OSM has already been used to c
 reate and validate land use and land cover maps in various regions (Arsanj
 ani et al.\, 2013\; Shultz et al.\, 2017).\n\nIn Argentina\,  the local co
 mmunity of OSM users has added a significant amount of geographic informat
 ion that could be used for land use analysis\, which could be further expa
 nded\, especially in non-urban areas.\nSince 2016\, land use data in the m
 iddle basin of the Lujan river have been added to OSM as part of projects 
 conducted by the National University of Lujan. Land use was visually asses
 sed using satellite imagery and representative polygons were added with ap
 propriate tags. Geometries were added preferably as multipolygons. Boundar
 ies were drawn to avoid sharing nodes with the road and rail network.\n\nT
 he aim of this work is to present the development of an R package for the 
 analysis of landuse data contributed to OSM. Subsequently\, the goal is to
  increase the contribution of publicly generated information and its analy
 sis tools in an open access format\, such as those provided by OSM and R (
 R Core Team\, 2023).\n\nThe package can be installed from its github repos
 itory https://github.com/aduhour/osmlanduseR.\n\nThe package is in an earl
 y stage of development and the features included are aimed at 1) download 
 a set of land use related data from OSM using the overpass API. 2) Remove 
 overlaps and measure polygon area. 3) Classify polygons by mapping OSM tag
 s to user-defined classes that can be assimilated to Corine Land Cover cla
 sses or the FAO Land Cover Classification System (Schultz et al.\, 2017\; 
 Volante 2009) 4) Create a land use classification map.\n\n\nReferences\n\n
 Arsanjani\, A. J.\; Helbich\, M.\; Bakillah\, M.\; Hagenauer\, J. & Zipf\,
  A. 2013.Toward mapping land-use patterns from volunteered geographic info
 rmation. International Journal of Geographical Information Science.\n\nArs
 anjani\, J. J.\; Zipf\, 2015. A.\; Mooney\, P. & Helbich\, M. (Eds.) OpenS
 treetMap in GIScience\nSpringer. \n\nDuféal\, M. and Noucher\, M. 2017. D
 es TIC au TOC. Contribuer à OpenStreetMap: entre commun numérique et uto
 pie cartographique. Communs urbains et équipements numériques\, 31 \n\nH
 arvey\, D.\, 2004. The ‘new’ imperialism: Accumulation by dispossessio
 n. Socialist Register 40\,\n63–87\n\nPal\, S.\, Dominguez\, F.\, Bollatt
 i\, P.\, Oncley\, S. P.\, Yang\, Y.\, Alvarez\, J.\, and Garcia\, C. M. (2
 021). Investigating the effects of land use change on subsurface\, surface
 \, and atmospheric branches of the hydrologic cycle fin central argentina.
  Water Resources Research\, 57(11)\n\nPalmisano\, T.\, 2018. Tierras de al
 guien. Teseo. URL: https://www.teseopress.com/tierrasdealguien.\n\nPattiso
 n\, I. and Lane\, S. N. (2012). The link between land-use management and f
 luvial flood risk: a chaotic conception? Progress in Physical Geography\, 
 36(1):72–92.\n\nPintos\, P. and Narodowski\, P. (Eds.)\, 2012. La privat
 opía sacrílega. Efectos del urbanismo privado en humedales de la cuenca 
 baja del río Luján. 1era ed.\, Imago Mundi.\n\nR Core Team. 2023 R: A La
 nguage and Environment for Statistical Computing. R Foundation for  Statis
 tical Computing\, Vienna\, Austria. <https://www.R-project.org/>.\n\nSchul
 tz\, M.\; Vossa\, J.\; Auera\, M.\; Carterb\, S. and Zipf\, A. 2017. Open 
 land cover from OpenStreetMap and remote sensing. International Journal of
  Applied Earth Observationd and Geoinformation.\n\nVolante\, J. N. 2009. M
 onitoreo de la Cobertura y el Uso del Suelo a partir de sensores remotos. 
 Instituto Nacional de Tecnología Agropecuaria\, Instituto Nacional de Tec
 nología Agropecuaria.
DTSTAMP:20260504T204155Z
LOCATION:Room V
SUMMARY:osmlanduseR: An R package for the analysis of landuse data contribu
 ted to OpenStreetMap - Andrés Esteban Duhour
URL:https://talks.staging.osgeo.org/foss4g-2024/talk/GSBMGK/
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