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3 resultados encontrados para: AUTOR: Klepeis, P.
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Land system science axiomatically addresses social–environmental systems by integrating the dynamics of land uses (social) and land covers (environment), invariably including the use of remote sensing data and often, spatially explicit models of land change. This kind of research is illustrated through the Southern Yucatán Peninsular Region project (1997–2008) aimed at understanding, predicting, and projecting spatially explicit land change in a region with juxtaposed land uses-agriculture and a biosphere reserve. The successes of the project, its contributions to contemporary land system science, and the organizational mechanisms that fostered the research are identified as well as various corrections, which if applied, may have refined and extended the project's goals. Overall, the project demonstrates the kind of integrated research required to advance understanding of a social-environment system and the team-based methods used in the process.


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Subsistence sustained: swidden or milpa cultivation
Klepeis, Peter (autor) ; Vance, Colin James (autor) ; Keys, Eric (autor) ; Macario Mendoza, Pedro A. (autor) ; Turner II, Billie Lee (autor) ;
Clasificación: AR/633.15097264 / S9
Contenido en: Integrated land-change science and tropical deforestation in the southern Yucatán: final frontiers / edited by B. L. Turner II, Jacqueline Geoghegan and David R. Foster Oxford, England, United Kingdom : Oxford University Press, 2004 páginas 189-206 ISBN:0-19-924530-4 :: 978-0-19-924530-7
Bibliotecas: Campeche , Chetumal , San Cristóbal
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SIBE Campeche
ECO040006388 (Disponible)
Disponibles para prestamo: 1
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SIBE Chetumal
51927-30 (Disponible)
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SIBE San Cristóbal
51927-20 (Disponible)
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- Artículo con arbitraje
Modeling tropical deforestation in the southern Yucatán peninsular region: comparing survey and satellite data
Geoghegan, Jacqueline ; Cortina Villar, Héctor Sergio (coaut.) (1960-) ; Klepeis, Peter (coaut.) ; Macario Mendoza, Pedro A. (coaut.) ; Ogneva Himmelberger, Yelena A. (coaut.) ; Roy Chowdhury, Rinku (coaut.) ; Turner II, Billie Lee (coaut.) ; Vance, Colin (coaut.) ;
Clasificación: AR/333.75137 / M6
Contenido en: Agriculture, Ecosystems and Environment Vol. 85, no. 1-3 (June 2001), p. 25-46 ISSN: 0167-8809
Bibliotecas: Campeche , San Cristóbal
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SIBE Campeche
ECO040001672 (Disponible)
Disponibles para prestamo: 1
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SIBE San Cristóbal
ECO010005133 (Disponible)
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Resumen en: Inglés |
Resumen en inglés

This paper presents some initial modeling results from a large, interdisciplinary research project underway in the southern Yucatán peninsular region. The aims of the project are: to understand, through individual household surveywork, the behavioral and structural dynamics that influence land managers’ decisions to deforest and intensify land use; model these dynamics and link their outcomes directly to satellite imagery; model from the imagery itself; and, determine the robustness of modeling to and from the satellite imagery. Two complementary datasets, one from household survey data on agricultural practices including information on socio-economic factors and the second from satellite imagery linked with aggregate government census data, are used in two econometric modeling approaches. Both models test hypotheses concerning deforestation during different time periods in the recent past in the region. The first uses the satellite data, other spatial environmental variables, and aggregate socio-economic data (e.g., census data) in a discrete-choice (logit) model to estimate the probability that any particular pixel in the landscape will be deforested, as a function of explanatory variables. The second model uses the survey data in a cross-sectional regression (OLS) model to ask questions about the amount of deforestation associated with each individual farmer and to explain these choices as a function of individual socio-demographic, market, environmental, and geographic variables. In both cases, however, the choices of explanatory variables are informed by social science theory as to what are hypothesized to affect the deforestation decision (e.g., in a von Thünen model, accessibility is hypothesized to affect choice; in a Ricardian model, land quality; in a Chayanovian model, consumer–labor ratio).

The models ask different questions using different data, but several broad comparisons seem useful. While most variables are statistically significant in the discrete choice model, none of the location variables are statistically significant in the continuous model. Therefore, while location affects the overall probability of deforestation, it does not appear to explain the total amount of deforestation on a given location by an individual.