2019
DOI: 10.26848/rbgf.v11.6.p2057-2066
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Simulation of changes in land-use/land cover on wetlands through CA-Markov model

Abstract: A B S T R A C TLand use/land cover modeling is extremely important to land planners, since it allows creating projects and scenarios with possible future threats to ecosystems. Thus, the aim of the present study was to apply the CA-Marvok model to simulate the land use and land cover for the year 2030 in the environmental protection area of the Banhado Grande (EPABG), Brazil. Thus, two images Landsat 5 TM and 8 OLI from 2007 and 2017 were classified. The CA-Markov model was applied through the Land Change Mode… Show more

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“…Akin et al used the CA-Markov model to simulate the dynamics of land use change in Mediterranean coastal wetlands, and found that the rapid development of agricultural activities led to significant habitat loss in ecologically sensitive areas [35]. Simioni et al [36] applied the CA-Markov model to simulate land use and land cover in the Banhado Grande Wetland Reserve, Brazil, in 2030, and found that the increase in soybean cultivation posed a threat to the wetland ecosystem. Zhang et al [37] used CA-Markov models and multi-scenario simulations to predict the future wetland evolution of nearly 30 wetlands in Guangxi, revealing future directions.…”
Section: Introductionmentioning
confidence: 99%
“…Akin et al used the CA-Markov model to simulate the dynamics of land use change in Mediterranean coastal wetlands, and found that the rapid development of agricultural activities led to significant habitat loss in ecologically sensitive areas [35]. Simioni et al [36] applied the CA-Markov model to simulate land use and land cover in the Banhado Grande Wetland Reserve, Brazil, in 2030, and found that the increase in soybean cultivation posed a threat to the wetland ecosystem. Zhang et al [37] used CA-Markov models and multi-scenario simulations to predict the future wetland evolution of nearly 30 wetlands in Guangxi, revealing future directions.…”
Section: Introductionmentioning
confidence: 99%