Analysis of the Land Use and Cover Changes in the Metropolitan Area of Tepic-Xalisco (1973–2015) through Landsat Images

Armando Avalos Jiménez, Fernando Flores Vilchez, Oyolsi Nájera González and Susana M. L. Marceleño Flores
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Armando Avalos Jiménez: Posgrado en Ciencias Biológico Agropecuarias, Unidad Académica de Agricultura, Universidad Autónoma de Nayarit (Autonomous University of Nayarit), Carretera Tepic-Compostela Km 9, Xalisco C.P. 63780, Nayarit, México
Fernando Flores Vilchez: Secretaría de Investigación y Posgrado, Universidad Autónoma de Nayarit, Ciudad de la Cultura s/n, Col. Centro, Tepic C.P. 63000, Nayarit, Mexico
Oyolsi Nájera González: Secretaría de Investigación y Posgrado, Universidad Autónoma de Nayarit, Ciudad de la Cultura s/n, Col. Centro, Tepic C.P. 63000, Nayarit, Mexico
Susana M. L. Marceleño Flores: Secretaría de Investigación y Posgrado, Universidad Autónoma de Nayarit, Ciudad de la Cultura s/n, Col. Centro, Tepic C.P. 63000, Nayarit, Mexico

Sustainability, 2018, vol. 10, issue 6, 1-15

Abstract: Land use and cover changes (LUCC) have been identified as one of the main causes of biodiversity loss and deforestation in the world. Fundamentally, the urban land use has replaced agricultural and forest cover causing loss of environmental services. Monitoring and quantifying LUCC are essential to achieve a proper land management. The objective of this study was to analyze the LUCC in the metropolitan area of Tepic-Xalisco during the period 1973–2015. To find the best fit and obtain the different land use classes, supervised classification techniques were applied using Maximum Likelihood Classification (MLC), Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs). The results were validated with control points (ground truth) through cross tabulation. The best results were obtained from the SVMs method with kappa indices above 85%. The transition analysis infers that urban land has grown significantly during 42 years, increasing 62 km 2 and replacing agricultural areas at a rate of 1.48 km 2 /year. Forest loss of 5.78 km 2 annually was also identified. The results show the different land uses distribution and the dynamics developed in the past. This information may be used to simulate future LUCC and modeling different scenarios.

Keywords: Maximum Likelihood Classification; Support Vector Machines; Artificial Neural Networks; significant transitions; urban growth; Nayarit (Mexico) (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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