TinePerezMolowny-Horas2019
Référence
Tine, M., Perez, L., Molowny-Horas, R. (2019) Hybrid spatiotemporal simulation of future changes in open wetlands: A study of the Abitibi-Témiscamingue region, Québec, Canada. International Journal of Applied Earth Observation and Geoinformation, 74:302-313
Résumé
Among the most productive ecosystems around the world, wetlands support a wide range of biodiversity such as waterfowl, fish, amphibians, plants and many other species. They also provide ecosystem services that play important roles in relation to nutrient cycling, climate mitigation and adaptation, as well as food security. In this research, we examined and projected the spatiotemporal trends of change in open wetlands by coupling logistic regression, Markov chain methods and a multi-objective land allocation model into a hybrid geosimulation model. To study the changes in open wetlands we used multi-temporal land cover information interpreted from LANDSAT images (1985, 1995, and 2005). We predicted future spatial distributions of open wetlands in the administrative region of Abitibi-Témiscamingue, Quebec, Canada for 2015, 2025, 2035, 2045 and 2055. A comparison and assessment of the model's outcomes were performed using map-comparison techniques as well as landscape metrics. Change analysis between 1985 and 2005 showed an increase of about 63% in open wetlands, while simulation results indicated that this tendency would persist into 2055 with a continuous augmentation of open wetlands in the region. The spatial distribution of predicted trends in open wetlands could provide support to local biodiversity assessments, management and conservation planning of the open wetlands in Quebec, Canada. © 2018 Elsevier B.V.
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@ARTICLE { TinePerezMolowny-Horas2019,
AUTHOR = { Tine, M. and Perez, L. and Molowny-Horas, R. },
TITLE = { Hybrid spatiotemporal simulation of future changes in open wetlands: A study of the Abitibi-Témiscamingue region, Québec, Canada },
JOURNAL = { International Journal of Applied Earth Observation and Geoinformation },
YEAR = { 2019 },
VOLUME = { 74 },
PAGES = { 302-313 },
NOTE = { cited By 0 },
ABSTRACT = { Among the most productive ecosystems around the world, wetlands support a wide range of biodiversity such as waterfowl, fish, amphibians, plants and many other species. They also provide ecosystem services that play important roles in relation to nutrient cycling, climate mitigation and adaptation, as well as food security. In this research, we examined and projected the spatiotemporal trends of change in open wetlands by coupling logistic regression, Markov chain methods and a multi-objective land allocation model into a hybrid geosimulation model. To study the changes in open wetlands we used multi-temporal land cover information interpreted from LANDSAT images (1985, 1995, and 2005). We predicted future spatial distributions of open wetlands in the administrative region of Abitibi-Témiscamingue, Quebec, Canada for 2015, 2025, 2035, 2045 and 2055. A comparison and assessment of the model's outcomes were performed using map-comparison techniques as well as landscape metrics. Change analysis between 1985 and 2005 showed an increase of about 63% in open wetlands, while simulation results indicated that this tendency would persist into 2055 with a continuous augmentation of open wetlands in the region. The spatial distribution of predicted trends in open wetlands could provide support to local biodiversity assessments, management and conservation planning of the open wetlands in Quebec, Canada. © 2018 Elsevier B.V. },
AFFILIATION = { Laboratory of Environmental Geosimulation (LEDGE), Department of Geography, Université de Montréal, Pavillon 520, Chemin de la Côte-Sainte-Catherine, Montreal, QC H2V 2B8, Canada; CREAF, Cerdanyola del Vallès, 08193, Spain },
AUTHOR_KEYWORDS = { Logistic regression; Markov-chain; Multi-objective optimization; Open wetlands; Spatiotemporal modelling },
DOCUMENT_TYPE = { Article },
DOI = { 10.1016/j.jag.2018.10.001 },
SOURCE = { Scopus },
URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062895320&doi=10.1016%2fj.jag.2018.10.001&partnerID=40&md5=c3441f394d961a3a3eb191bc8561ab76 },
}
