A dynamic spatial model of shifting cultivation in the highlands of Guinea, West Africa
Identifieur interne : 000E20 ( Istex/Corpus ); précédent : 000E19; suivant : 000E21A dynamic spatial model of shifting cultivation in the highlands of Guinea, West Africa
Auteurs : Peter T. Gilruth ; Stuart E. Marsh ; Robert ItamiSource :
- Ecological Modelling [ 0304-3800 ] ; 1995.
Abstract
A dynamic spatial model of tropical deforestation and land-use change was developed from remotely sensed data for the Fouta Djallon mountain range in the Republic of Guinea, West Africa. The objective was to simulate patterns of forest clearing for shifting cultivation in terms of farmers' selection behavior for new fields based on topography and proximity to villages. Data describing the current and historic condition of the vegetation cover and land use for a watershed in Guinea were derived from aerial photography and ground sampling. Maps of these conditions were prepared and entered in a geographic information system (GIS) together with topographic data. From these data, maps of secondary variables (slope, village proximity, site productivity, and labor) were derived using the spatial operators contained in the GIS. These variables were ranked for agricultural preference and then combined following a pair-wise hierarchy to generate a composite agricultural site-preference map. Shifting agriculture was simulated by running the model through 18 iterations on a two-year time increment which corresponds to the typical duration of cultivation for any one field. An empirically derived number of cells from the agricultural site-preference map were converted from forest to active farms for each iteration to simulate deforestation. Different variable combinations and underlying assumptions of model logic were tested to determine influence on simulation results. To validate the model, the spatial characteristics of the projected landscape were compared with land-use data collected in 1989, using tests for (1) size and distribution of agricultural sites, (2) image similarity (Kappa test), and (3) physical characteristics (slope and distance from population centers) of the site. Although the model did not simulate the farmers' selection behavior for topography and village proximity successfully, test results with individual variables suggest that site productivity as determined by the length of fallow is a critical variable in the site selection process. Thus, aside from documenting the dynamics of shifting cultivation, this model allows planners to evaluate alternative strategies of land-use conversion with a graphic display of zones of potential hazards. Finally, the data contained in the GIS serve as a structure for monitoring long-term change in the region.
Url:
DOI: 10.1016/0304-3800(93)E0145-S
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The objective was to simulate patterns of forest clearing for shifting cultivation in terms of farmers' selection behavior for new fields based on topography and proximity to villages. Data describing the current and historic condition of the vegetation cover and land use for a watershed in Guinea were derived from aerial photography and ground sampling. Maps of these conditions were prepared and entered in a geographic information system (GIS) together with topographic data. From these data, maps of secondary variables (slope, village proximity, site productivity, and labor) were derived using the spatial operators contained in the GIS. These variables were ranked for agricultural preference and then combined following a pair-wise hierarchy to generate a composite agricultural site-preference map. Shifting agriculture was simulated by running the model through 18 iterations on a two-year time increment which corresponds to the typical duration of cultivation for any one field. An empirically derived number of cells from the agricultural site-preference map were converted from forest to active farms for each iteration to simulate deforestation. Different variable combinations and underlying assumptions of model logic were tested to determine influence on simulation results. To validate the model, the spatial characteristics of the projected landscape were compared with land-use data collected in 1989, using tests for (1) size and distribution of agricultural sites, (2) image similarity (Kappa test), and (3) physical characteristics (slope and distance from population centers) of the site. Although the model did not simulate the farmers' selection behavior for topography and village proximity successfully, test results with individual variables suggest that site productivity as determined by the length of fallow is a critical variable in the site selection process. Thus, aside from documenting the dynamics of shifting cultivation, this model allows planners to evaluate alternative strategies of land-use conversion with a graphic display of zones of potential hazards. Finally, the data contained in the GIS serve as a structure for monitoring long-term change in the region.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>Peter T. Gilruth</name><affiliations><json:string>Arizona Remote Sensing Center, Office of Arid Lands Studies, University of Arizona, 845 N. Park, Tucson, AZ 85719, USA</json:string></affiliations></json:item><json:item><name>Stuart E. Marsh</name><affiliations><json:string>Arizona Remote Sensing Center, Office of Arid Lands Studies, University of Arizona, 845 N. 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An empirically derived number of cells from the agricultural site-preference map were converted from forest to active farms for each iteration to simulate deforestation. Different variable combinations and underlying assumptions of model logic were tested to determine influence on simulation results. To validate the model, the spatial characteristics of the projected landscape were compared with land-use data collected in 1989, using tests for (1) size and distribution of agricultural sites, (2) image similarity (Kappa test), and (3) physical characteristics (slope and distance from population centers) of the site. Although the model did not simulate the farmers' selection behavior for topography and village proximity successfully, test results with individual variables suggest that site productivity as determined by the length of fallow is a critical variable in the site selection process. 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Park, Tucson, AZ 85719, USA</affiliation></author><author xml:id="author-2"><persName><forename type="first">Stuart E.</forename><surname>Marsh</surname></persName><affiliation>Arizona Remote Sensing Center, Office of Arid Lands Studies, University of Arizona, 845 N. Park, Tucson, AZ 85719, USA</affiliation></author><author xml:id="author-3"><persName><forename type="first">Robert</forename><surname>Itami</surname></persName><affiliation>School of Environmental Planning, University of Melbourne, Parkville, Vic. 3052, Australia</affiliation></author></analytic><monogr><title level="j">Ecological Modelling</title><title level="j" type="abbrev">ECOMOD</title><idno type="pISSN">0304-3800</idno><idno type="PII">S0304-3800(00)X0022-1</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1995"></date><biblScope unit="volume">79</biblScope><biblScope unit="issue">1–3</biblScope><biblScope unit="page" from="179">179</biblScope><biblScope unit="page" to="197">197</biblScope></imprint></monogr><idno type="istex">293BD8FF539FEE12312A633C39F0A5B4BE9BB600</idno><idno type="DOI">10.1016/0304-3800(93)E0145-S</idno><idno type="PII">0304-3800(93)E0145-S</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>1995</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>A dynamic spatial model of tropical deforestation and land-use change was developed from remotely sensed data for the Fouta Djallon mountain range in the Republic of Guinea, West Africa. The objective was to simulate patterns of forest clearing for shifting cultivation in terms of farmers' selection behavior for new fields based on topography and proximity to villages. Data describing the current and historic condition of the vegetation cover and land use for a watershed in Guinea were derived from aerial photography and ground sampling. Maps of these conditions were prepared and entered in a geographic information system (GIS) together with topographic data. From these data, maps of secondary variables (slope, village proximity, site productivity, and labor) were derived using the spatial operators contained in the GIS. These variables were ranked for agricultural preference and then combined following a pair-wise hierarchy to generate a composite agricultural site-preference map. Shifting agriculture was simulated by running the model through 18 iterations on a two-year time increment which corresponds to the typical duration of cultivation for any one field. An empirically derived number of cells from the agricultural site-preference map were converted from forest to active farms for each iteration to simulate deforestation. Different variable combinations and underlying assumptions of model logic were tested to determine influence on simulation results. To validate the model, the spatial characteristics of the projected landscape were compared with land-use data collected in 1989, using tests for (1) size and distribution of agricultural sites, (2) image similarity (Kappa test), and (3) physical characteristics (slope and distance from population centers) of the site. Although the model did not simulate the farmers' selection behavior for topography and village proximity successfully, test results with individual variables suggest that site productivity as determined by the length of fallow is a critical variable in the site selection process. Thus, aside from documenting the dynamics of shifting cultivation, this model allows planners to evaluate alternative strategies of land-use conversion with a graphic display of zones of potential hazards. Finally, the data contained in the GIS serve as a structure for monitoring long-term change in the region.</p></abstract><textClass><keywords scheme="keyword"><list><head>Keywords</head><item><term>Cultivation systems</term></item><item><term>Deforestation</term></item><item><term>Spatial dynamics</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1995">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/293BD8FF539FEE12312A633C39F0A5B4BE9BB600/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"></istex:docType><istex:document><converted-article version="4.5.2" docsubtype="fla"><item-info><jid>ECOMOD</jid><aid>93E0145S</aid><ce:pii>0304-3800(93)E0145-S</ce:pii><ce:doi>10.1016/0304-3800(93)E0145-S</ce:doi><ce:copyright type="unknown" year="1995"></ce:copyright></item-info><head><ce:title>A dynamic spatial model of shifting cultivation in the highlands of Guinea, West Africa</ce:title><ce:author-group><ce:author><ce:given-name>Peter T.</ce:given-name><ce:surname>Gilruth</ce:surname><ce:cross-ref refid="COR1"><ce:sup>∗</ce:sup></ce:cross-ref><ce:cross-ref refid="AFF1"><ce:sup>a</ce:sup></ce:cross-ref><ce:cross-ref refid="FN1"><ce:sup>1</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>Stuart E.</ce:given-name><ce:surname>Marsh</ce:surname><ce:cross-ref refid="AFF1"><ce:sup>a</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>Robert</ce:given-name><ce:surname>Itami</ce:surname><ce:cross-ref refid="AFF2"><ce:sup>b</ce:sup></ce:cross-ref></ce:author><ce:affiliation id="AFF1"><ce:label>a</ce:label><ce:textfn>Arizona Remote Sensing Center, Office of Arid Lands Studies, University of Arizona, 845 N. Park, Tucson, AZ 85719, USA</ce:textfn></ce:affiliation><ce:affiliation id="AFF2"><ce:label>b</ce:label><ce:textfn>School of Environmental Planning, University of Melbourne, Parkville, Vic. 3052, Australia</ce:textfn></ce:affiliation><ce:correspondence id="COR1"><ce:label>∗</ce:label><ce:text>Corresponding author.</ce:text></ce:correspondence><ce:footnote id="FN1"><ce:label>1</ce:label><ce:note-para>Present address: United Nations Development Program, 304 East 45th St., Room FF-954, New York, NY 10017, USA.</ce:note-para></ce:footnote></ce:author-group><ce:date-received day="20" month="7" year="1992"></ce:date-received><ce:date-accepted day="15" month="12" year="1993"></ce:date-accepted><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>A dynamic spatial model of tropical deforestation and land-use change was developed from remotely sensed data for the Fouta Djallon mountain range in the Republic of Guinea, West Africa. The objective was to simulate patterns of forest clearing for shifting cultivation in terms of farmers' selection behavior for new fields based on topography and proximity to villages. Data describing the current and historic condition of the vegetation cover and land use for a watershed in Guinea were derived from aerial photography and ground sampling. Maps of these conditions were prepared and entered in a geographic information system (GIS) together with topographic data. From these data, maps of secondary variables (slope, village proximity, site productivity, and labor) were derived using the spatial operators contained in the GIS. These variables were ranked for agricultural preference and then combined following a pair-wise hierarchy to generate a composite agricultural site-preference map. Shifting agriculture was simulated by running the model through 18 iterations on a two-year time increment which corresponds to the typical duration of cultivation for any one field. An empirically derived number of cells from the agricultural site-preference map were converted from forest to active farms for each iteration to simulate deforestation. Different variable combinations and underlying assumptions of model logic were tested to determine influence on simulation results. To validate the model, the spatial characteristics of the projected landscape were compared with land-use data collected in 1989, using tests for (1) size and distribution of agricultural sites, (2) image similarity (Kappa test), and (3) physical characteristics (slope and distance from population centers) of the site. Although the model did not simulate the farmers' selection behavior for topography and village proximity successfully, test results with individual variables suggest that site productivity as determined by the length of fallow is a critical variable in the site selection process. Thus, aside from documenting the dynamics of shifting cultivation, this model allows planners to evaluate alternative strategies of land-use conversion with a graphic display of zones of potential hazards. Finally, the data contained in the GIS serve as a structure for monitoring long-term change in the region.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Cultivation systems</ce:text></ce:keyword><ce:keyword><ce:text>Deforestation</ce:text></ce:keyword><ce:keyword><ce:text>Spatial dynamics</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>A dynamic spatial model of shifting cultivation in the highlands of Guinea, West Africa</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>A dynamic spatial model of shifting cultivation in the highlands of Guinea, West Africa</title></titleInfo><name type="personal"><namePart type="given">Peter T.</namePart><namePart type="family">Gilruth</namePart><affiliation>Arizona Remote Sensing Center, Office of Arid Lands Studies, University of Arizona, 845 N. Park, Tucson, AZ 85719, USA</affiliation><description>Corresponding author.</description><description>Present address: United Nations Development Program, 304 East 45th St., Room FF-954, New York, NY 10017, USA.</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Stuart E.</namePart><namePart type="family">Marsh</namePart><affiliation>Arizona Remote Sensing Center, Office of Arid Lands Studies, University of Arizona, 845 N. Park, Tucson, AZ 85719, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Robert</namePart><namePart type="family">Itami</namePart><affiliation>School of Environmental Planning, University of Melbourne, Parkville, Vic. 3052, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">1995</dateIssued><copyrightDate encoding="w3cdtf">1995</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">A dynamic spatial model of tropical deforestation and land-use change was developed from remotely sensed data for the Fouta Djallon mountain range in the Republic of Guinea, West Africa. The objective was to simulate patterns of forest clearing for shifting cultivation in terms of farmers' selection behavior for new fields based on topography and proximity to villages. Data describing the current and historic condition of the vegetation cover and land use for a watershed in Guinea were derived from aerial photography and ground sampling. Maps of these conditions were prepared and entered in a geographic information system (GIS) together with topographic data. From these data, maps of secondary variables (slope, village proximity, site productivity, and labor) were derived using the spatial operators contained in the GIS. These variables were ranked for agricultural preference and then combined following a pair-wise hierarchy to generate a composite agricultural site-preference map. Shifting agriculture was simulated by running the model through 18 iterations on a two-year time increment which corresponds to the typical duration of cultivation for any one field. An empirically derived number of cells from the agricultural site-preference map were converted from forest to active farms for each iteration to simulate deforestation. Different variable combinations and underlying assumptions of model logic were tested to determine influence on simulation results. To validate the model, the spatial characteristics of the projected landscape were compared with land-use data collected in 1989, using tests for (1) size and distribution of agricultural sites, (2) image similarity (Kappa test), and (3) physical characteristics (slope and distance from population centers) of the site. Although the model did not simulate the farmers' selection behavior for topography and village proximity successfully, test results with individual variables suggest that site productivity as determined by the length of fallow is a critical variable in the site selection process. Thus, aside from documenting the dynamics of shifting cultivation, this model allows planners to evaluate alternative strategies of land-use conversion with a graphic display of zones of potential hazards. Finally, the data contained in the GIS serve as a structure for monitoring long-term change in the region.</abstract><subject><genre>Keywords</genre><topic>Cultivation systems</topic><topic>Deforestation</topic><topic>Spatial dynamics</topic></subject><relatedItem type="host"><titleInfo><title>Ecological Modelling</title></titleInfo><titleInfo type="abbreviated"><title>ECOMOD</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">199505</dateIssued></originInfo><identifier type="ISSN">0304-3800</identifier><identifier type="PII">S0304-3800(00)X0022-1</identifier><part><date>199505</date><detail type="volume"><number>79</number><caption>vol.</caption></detail><detail type="issue"><number>1–3</number><caption>no.</caption></detail><extent unit="issue pages"><start>1</start><end>296</end></extent><extent unit="pages"><start>179</start><end>197</end></extent></part></relatedItem><identifier type="istex">293BD8FF539FEE12312A633C39F0A5B4BE9BB600</identifier><identifier type="DOI">10.1016/0304-3800(93)E0145-S</identifier><identifier type="PII">0304-3800(93)E0145-S</identifier><recordInfo><recordContentSource>ELSEVIER</recordContentSource></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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