Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level

There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Land use policy 2012, Vol.29 (1), p.35-44
Hauptverfasser: Cantelaube, P., Jayet, P.A., Carré, F., Bamps, C., Zakharov, P.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 44
container_issue 1
container_start_page 35
container_title Land use policy
container_volume 29
creator Cantelaube, P.
Jayet, P.A.
Carré, F.
Bamps, C.
Zakharov, P.
description There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally.
doi_str_mv 10.1016/j.landusepol.2011.05.002
format Article
fullrecord <record><control><sourceid>proquest_hal_p</sourceid><recordid>TN_cdi_hal_primary_oai_HAL_ineris_00961771v1</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0264837711000433</els_id><sourcerecordid>888111691</sourcerecordid><originalsourceid>FETCH-LOGICAL-c493t-9bc9c200ca6a6a82c0e966c8ce3d1207db4dffa15250dbcbbb857bd6bff1936e3</originalsourceid><addsrcrecordid>eNqFkUuP1DAQhCMEEsPCb8A3LiR0O08flxXsIo3EAfZs-dHJeJTEwU4G7b_HoyA4rnywJX_VLldlGUMoELD5dC5GNdst0uLHggNiAXUBwF9kB-zaMq_bunqZHYA3Vd6Vbfs6exPjGQAagfyQDffkh6CWkzNqZNb_nmM6uHlgvmd-W5dtjWwJ_uIsWaafmJoZGT_7yRnWqzCxyVsa2VWkg1oTpFa2nogFGpyf09CRLjS-zV71aoz07u9-kz1-_fLz7iE_fr__dnd7zE0lyjUX2gjDAYxq0uq4ARJNYzpDpUUOrdWV7XuFNa_BaqO17upW20b3PYqyofIm-7jPPalRLsFNKjxJr5x8uD1KN1NwUQKIBtsWL5jwDzuevvhro7jKyUVDY8qU_BalQCFqAVg9S3Zdh4gp1ER2O2mCjzFQ_88Hgrx2Js_yf2fy2pmEOrniSfp-l_bKSzVczT7-SECdLrHlvE3E552gFOLFUZDROJoNWRfIrNJ69_wzfwBweLA6</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>888111691</pqid></control><display><type>article</type><title>Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level</title><source>PAIS Index</source><source>ScienceDirect Journals (5 years ago - present)</source><creator>Cantelaube, P. ; Jayet, P.A. ; Carré, F. ; Bamps, C. ; Zakharov, P.</creator><creatorcontrib>Cantelaube, P. ; Jayet, P.A. ; Carré, F. ; Bamps, C. ; Zakharov, P.</creatorcontrib><description>There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally.</description><identifier>ISSN: 0264-8377</identifier><identifier>EISSN: 1873-5754</identifier><identifier>DOI: 10.1016/j.landusepol.2011.05.002</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Agricultural policy ; altitude ; Climate ; Common Agricultural Policy ; Downscaling ; Economics ; Environmental Engineering ; environmental impact ; Environmental Sciences ; Farm Accountancy Data Network ; Farm-groups ; farming systems ; Farms ; issues and policy ; land cover ; Land use ; Land utilization ; Location ; Planning ; Size ; soil ; Spatial statistics</subject><ispartof>Land use policy, 2012, Vol.29 (1), p.35-44</ispartof><rights>2011 Elsevier Ltd</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c493t-9bc9c200ca6a6a82c0e966c8ce3d1207db4dffa15250dbcbbb857bd6bff1936e3</citedby><cites>FETCH-LOGICAL-c493t-9bc9c200ca6a6a82c0e966c8ce3d1207db4dffa15250dbcbbb857bd6bff1936e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.landusepol.2011.05.002$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,885,3550,4024,27865,27923,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://ineris.hal.science/ineris-00961771$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Cantelaube, P.</creatorcontrib><creatorcontrib>Jayet, P.A.</creatorcontrib><creatorcontrib>Carré, F.</creatorcontrib><creatorcontrib>Bamps, C.</creatorcontrib><creatorcontrib>Zakharov, P.</creatorcontrib><title>Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level</title><title>Land use policy</title><description>There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally.</description><subject>Agricultural policy</subject><subject>altitude</subject><subject>Climate</subject><subject>Common Agricultural Policy</subject><subject>Downscaling</subject><subject>Economics</subject><subject>Environmental Engineering</subject><subject>environmental impact</subject><subject>Environmental Sciences</subject><subject>Farm Accountancy Data Network</subject><subject>Farm-groups</subject><subject>farming systems</subject><subject>Farms</subject><subject>issues and policy</subject><subject>land cover</subject><subject>Land use</subject><subject>Land utilization</subject><subject>Location</subject><subject>Planning</subject><subject>Size</subject><subject>soil</subject><subject>Spatial statistics</subject><issn>0264-8377</issn><issn>1873-5754</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNqFkUuP1DAQhCMEEsPCb8A3LiR0O08flxXsIo3EAfZs-dHJeJTEwU4G7b_HoyA4rnywJX_VLldlGUMoELD5dC5GNdst0uLHggNiAXUBwF9kB-zaMq_bunqZHYA3Vd6Vbfs6exPjGQAagfyQDffkh6CWkzNqZNb_nmM6uHlgvmd-W5dtjWwJ_uIsWaafmJoZGT_7yRnWqzCxyVsa2VWkg1oTpFa2nogFGpyf09CRLjS-zV71aoz07u9-kz1-_fLz7iE_fr__dnd7zE0lyjUX2gjDAYxq0uq4ARJNYzpDpUUOrdWV7XuFNa_BaqO17upW20b3PYqyofIm-7jPPalRLsFNKjxJr5x8uD1KN1NwUQKIBtsWL5jwDzuevvhro7jKyUVDY8qU_BalQCFqAVg9S3Zdh4gp1ER2O2mCjzFQ_88Hgrx2Js_yf2fy2pmEOrniSfp-l_bKSzVczT7-SECdLrHlvE3E552gFOLFUZDROJoNWRfIrNJ69_wzfwBweLA6</recordid><startdate>2012</startdate><enddate>2012</enddate><creator>Cantelaube, P.</creator><creator>Jayet, P.A.</creator><creator>Carré, F.</creator><creator>Bamps, C.</creator><creator>Zakharov, P.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>7U6</scope><scope>C1K</scope><scope>SOI</scope><scope>7TQ</scope><scope>DHY</scope><scope>DON</scope><scope>1XC</scope><scope>VOOES</scope></search><sort><creationdate>2012</creationdate><title>Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level</title><author>Cantelaube, P. ; Jayet, P.A. ; Carré, F. ; Bamps, C. ; Zakharov, P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c493t-9bc9c200ca6a6a82c0e966c8ce3d1207db4dffa15250dbcbbb857bd6bff1936e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Agricultural policy</topic><topic>altitude</topic><topic>Climate</topic><topic>Common Agricultural Policy</topic><topic>Downscaling</topic><topic>Economics</topic><topic>Environmental Engineering</topic><topic>environmental impact</topic><topic>Environmental Sciences</topic><topic>Farm Accountancy Data Network</topic><topic>Farm-groups</topic><topic>farming systems</topic><topic>Farms</topic><topic>issues and policy</topic><topic>land cover</topic><topic>Land use</topic><topic>Land utilization</topic><topic>Location</topic><topic>Planning</topic><topic>Size</topic><topic>soil</topic><topic>Spatial statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cantelaube, P.</creatorcontrib><creatorcontrib>Jayet, P.A.</creatorcontrib><creatorcontrib>Carré, F.</creatorcontrib><creatorcontrib>Bamps, C.</creatorcontrib><creatorcontrib>Zakharov, P.</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Sustainability Science Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><collection>PAIS Index</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Land use policy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cantelaube, P.</au><au>Jayet, P.A.</au><au>Carré, F.</au><au>Bamps, C.</au><au>Zakharov, P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level</atitle><jtitle>Land use policy</jtitle><date>2012</date><risdate>2012</risdate><volume>29</volume><issue>1</issue><spage>35</spage><epage>44</epage><pages>35-44</pages><issn>0264-8377</issn><eissn>1873-5754</eissn><abstract>There is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.landusepol.2011.05.002</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0264-8377
ispartof Land use policy, 2012, Vol.29 (1), p.35-44
issn 0264-8377
1873-5754
language eng
recordid cdi_hal_primary_oai_HAL_ineris_00961771v1
source PAIS Index; ScienceDirect Journals (5 years ago - present)
subjects Agricultural policy
altitude
Climate
Common Agricultural Policy
Downscaling
Economics
Environmental Engineering
environmental impact
Environmental Sciences
Farm Accountancy Data Network
Farm-groups
farming systems
Farms
issues and policy
land cover
Land use
Land utilization
Location
Planning
Size
soil
Spatial statistics
title Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T09%3A55%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Geographical%20downscaling%20of%20outputs%20provided%20by%20an%20economic%20farm%20model%20calibrated%20at%20the%20regional%20level&rft.jtitle=Land%20use%20policy&rft.au=Cantelaube,%20P.&rft.date=2012&rft.volume=29&rft.issue=1&rft.spage=35&rft.epage=44&rft.pages=35-44&rft.issn=0264-8377&rft.eissn=1873-5754&rft_id=info:doi/10.1016/j.landusepol.2011.05.002&rft_dat=%3Cproquest_hal_p%3E888111691%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=888111691&rft_id=info:pmid/&rft_els_id=S0264837711000433&rfr_iscdi=true