Search results for “Principal component analysis (PCA)

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Agronomy Research Open Access

Mapping and Characterizing the Green Belt of Córdoba: Land Dynamics and the Urban-Rural Transformation Process

Jun 2019 DOI 10.14302/issn.2639-3166.jar-19-2785
A. Mari NicolásCorresponding author Instituto Nacional de Tecnología Agropecuaria – Agencia de Extensión Rural Cruz del Eje

In Córdoba, Argentina, the peri-urban horticulture is in conflict with industrial agriculture and urban development. This problem is partly due to urban expansion to rural areas occurred in the last years and to monoculture farming, which has replaced traditional fruit and vegetable cropping in the region. This transformation process has raised concern about the current and future availability of productive sectors that can sustain food supply within the city boundaries and its immediate surroundings as well as about the loss of ecosystem services associated with peri-urban natural environments. Although these dynamic processes are well known, they have not been described or quantified in Córdoba. Baseline information about land use and its dynamics in productive areas or about number of producers is insufficient and/or out of date. At O-AUPA (Spanish acronym for Observatory of Urban and Peri-urban Agriculture and Agroecology) different mapping strategies are developed to contribute to the understanding of the land dynamics in the Green Belt of Córdoba (GBC) and the rural environments surrounding the city. In this work, we present a method based on the use of remote sensing and geographical information systems to characterize urban, peri-urban and rural areas of Córdoba city with the aim of evaluating the temporal dynamics of urban growth and the current state of land use and cover. We mapped and quantified the urban growth between 1974 and 2014, and evaluated land use in peri-urban and rural areas in 2015. We used satellite information from Landsat TM 5 to map the urban growth via a principal component analysis (PCA) and SPOT 5 imagery to characterize the current land use and land cover with the support vector machine classification algorithm. The results show an urban area growth of 46.5% over almost 40 years within the boundaries of the Capital department. Farm plot size increased, showing a concentration of land ownership, implying a reduced number of producers. Evidence indicates the importance of defining land planning guidelines that limit the advance of the urban frontier to valuable agricultural systems, ensure diversification of productive activities and protect and develop the fresh food production systems at the local level.

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