This paper presents the results of a change-detection study of the historical agricultural terraced landscape in “Costa Viola” (Calabria, South Italy). During the last century, because of the loss of economic competitiveness, it has undergone progressive abandonment, followed by landscape degradation. Taking into consideration the very steep slopes of Costa Viola and the need to analyse with high precision the historical evolution of the terraced landscape, research methods were implemented coupling advanced geomatic techniques with in situ detailed surveys. Based on historical aerial photographs, orthophotos, and numeric cartography, we analysed the land use/land cover change in the period 1955–2014 using photogrammetric and geoprocessing techniques, focusing particularly on trajectories in agricultural terraces. Area covered by active terraces decreased dramatically between 1955 and 2014, from 813.25 to 118.79 ha (−85.4%). The implemented spatial database was built in a free open-source software taking into consideration spatial accuracies and completeness. Spatial comparison among land use/land cover maps was carried out using a postclassification comparison technique that can provide complete cross-tabulation matrices. These data were compared with socio-economic statistics concerning demography and trends of farms with vineyards. The evolutionary dynamics of the active agricultural terraces were also analysed trough the definition of 6 types of spatio-temporal patterns recognised in the analysed period. These methods allowed to highlight the ongoing dynamics of abandonment of agricultural terraces in relation to their main causes and effects. Although tailored for the specific case study, they can be applied to many other terraced agricultural landscapes presenting similar characteristics and problems

Abandonment of traditional terraced landscape: A change detection approach (a case study in Costa Viola, Calabria, Italy)

Modica G
;
Praticò S;Di Fazio S
2017

Abstract

This paper presents the results of a change-detection study of the historical agricultural terraced landscape in “Costa Viola” (Calabria, South Italy). During the last century, because of the loss of economic competitiveness, it has undergone progressive abandonment, followed by landscape degradation. Taking into consideration the very steep slopes of Costa Viola and the need to analyse with high precision the historical evolution of the terraced landscape, research methods were implemented coupling advanced geomatic techniques with in situ detailed surveys. Based on historical aerial photographs, orthophotos, and numeric cartography, we analysed the land use/land cover change in the period 1955–2014 using photogrammetric and geoprocessing techniques, focusing particularly on trajectories in agricultural terraces. Area covered by active terraces decreased dramatically between 1955 and 2014, from 813.25 to 118.79 ha (−85.4%). The implemented spatial database was built in a free open-source software taking into consideration spatial accuracies and completeness. Spatial comparison among land use/land cover maps was carried out using a postclassification comparison technique that can provide complete cross-tabulation matrices. These data were compared with socio-economic statistics concerning demography and trends of farms with vineyards. The evolutionary dynamics of the active agricultural terraces were also analysed trough the definition of 6 types of spatio-temporal patterns recognised in the analysed period. These methods allowed to highlight the ongoing dynamics of abandonment of agricultural terraces in relation to their main causes and effects. Although tailored for the specific case study, they can be applied to many other terraced agricultural landscapes presenting similar characteristics and problems
change-detection analyses
historical aerial photographs
landscape trajectories
spatio-temporal patterns (STePs),
terraced landscape
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/4735
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