The study shows results deriving from a remote sensing analysis to map abandoned olive groves in the Montalbano area (Provinces of Florence, Prato and Pistoia in Tuscany Region, about 19,000 ha) coupled with modelling analysis so as to assess the mitigation potential of olive grove restoration and recover under a climate change perspective. Over the last decades, the olive orchards of Montalbano (mainly concentrated across marginal rural lands) are experiencing a large abandonment which in turn is determining a progressive decline of the historic Tuscan agricultural landscape. Changes in olive tree cultivation over the last 60 years were determined through a visual interpretation overlaying historical aerial photos (1954) and recent ones (2013). Lands which could be potentially restored to olive tree cultivation (i.e. arable lands, forests, shrubs, etc.) were also mapped. Results indicated that large areas of olive groves - currently classified as olive groves in the Corine Land Cover map (2012 updated to 2016 by the Regional Administration) - are with a very low plant density (likely semi-abandoned). To better estimate these areas having the potential to be restored with additional olive trees plantations, a geographically weighted regression approach was applied using NDVI (calculated from Landsat 8 OLI multiband scene) and local topography (i.e. elevation and slope) as predictor variables of plant density. Moreover, potential mitigation capacity of olive orchards cultivation was examined through the application of the DayCent geochemical model (Parton et al., 1994) under a typical agricultural management currently adopted in the area. Results indicated that about 908 ha out of 4,900 ha have been abandoned from 1954, and among them 406 ha of lands could be restored. The weighted multi-regression approach, providing optimal performances in predicting olive planting density (r=0.83**, RMSE =41.15 trees/ha) was applied over the entire study area and according to results, only 4.3% of olive groves denoted an economically sustainable plant density (> 300 trees/ha) in the study area. Results from DayCent simulations evidenced notable mitigation potential of high density orchards. In the specific, organic farming systems are able to sequester a higher amount of atmospheric C (up to 5.26 ton C/ha year) with respect to conventional (up to 4.47 ton C/ha year), arable lands (up to 0,50 ton C/ha year) or lands under shrub encroachment (4.19 ton C/ha year). This means that recovering all the olive groves under abandonment of the Montalbano area with a high planting density (>300 trees/ha) could stock 26,300 ton C/ year, compensating CO2 emissions due to about 31,000 habitants living in the Metropolitan area of Florence.

A remote sensing analysis to recover abandoned olive grove systems leveraging climate change mitigation / Camilla Dibari, Marco Moriondo, Sergi Costafreda-Aumedes, Lorenzo Brilli, Andrea Triossi, Marco Bindi. - ELETTRONICO. - (2018), pp. 97-98. (Intervento presentato al convegno From space to land management, remote sensing technologies supporting sustainable development and natural resource management tenutosi a Firenze nel 4-6 Luglio 2018).

A remote sensing analysis to recover abandoned olive grove systems leveraging climate change mitigation

Camilla Dibari
Membro del Collaboration Group
;
Marco Moriondo
Membro del Collaboration Group
;
Sergi Costafreda-Aumedes
Membro del Collaboration Group
;
Lorenzo Brilli
Membro del Collaboration Group
;
TRIOSSI, ANDREA
Membro del Collaboration Group
;
Marco Bindi
Membro del Collaboration Group
2018

Abstract

The study shows results deriving from a remote sensing analysis to map abandoned olive groves in the Montalbano area (Provinces of Florence, Prato and Pistoia in Tuscany Region, about 19,000 ha) coupled with modelling analysis so as to assess the mitigation potential of olive grove restoration and recover under a climate change perspective. Over the last decades, the olive orchards of Montalbano (mainly concentrated across marginal rural lands) are experiencing a large abandonment which in turn is determining a progressive decline of the historic Tuscan agricultural landscape. Changes in olive tree cultivation over the last 60 years were determined through a visual interpretation overlaying historical aerial photos (1954) and recent ones (2013). Lands which could be potentially restored to olive tree cultivation (i.e. arable lands, forests, shrubs, etc.) were also mapped. Results indicated that large areas of olive groves - currently classified as olive groves in the Corine Land Cover map (2012 updated to 2016 by the Regional Administration) - are with a very low plant density (likely semi-abandoned). To better estimate these areas having the potential to be restored with additional olive trees plantations, a geographically weighted regression approach was applied using NDVI (calculated from Landsat 8 OLI multiband scene) and local topography (i.e. elevation and slope) as predictor variables of plant density. Moreover, potential mitigation capacity of olive orchards cultivation was examined through the application of the DayCent geochemical model (Parton et al., 1994) under a typical agricultural management currently adopted in the area. Results indicated that about 908 ha out of 4,900 ha have been abandoned from 1954, and among them 406 ha of lands could be restored. The weighted multi-regression approach, providing optimal performances in predicting olive planting density (r=0.83**, RMSE =41.15 trees/ha) was applied over the entire study area and according to results, only 4.3% of olive groves denoted an economically sustainable plant density (> 300 trees/ha) in the study area. Results from DayCent simulations evidenced notable mitigation potential of high density orchards. In the specific, organic farming systems are able to sequester a higher amount of atmospheric C (up to 5.26 ton C/ha year) with respect to conventional (up to 4.47 ton C/ha year), arable lands (up to 0,50 ton C/ha year) or lands under shrub encroachment (4.19 ton C/ha year). This means that recovering all the olive groves under abandonment of the Montalbano area with a high planting density (>300 trees/ha) could stock 26,300 ton C/ year, compensating CO2 emissions due to about 31,000 habitants living in the Metropolitan area of Florence.
2018
AIT2018 Italian Society of Remote Sensing IX Conference
From space to land management, remote sensing technologies supporting sustainable development and natural resource management
Firenze
Camilla Dibari, Marco Moriondo, Sergi Costafreda-Aumedes, Lorenzo Brilli, Andrea Triossi, Marco Bindi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1133768
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