The awareness of global changes and the relevance of local actions encourage local agencies to la... more The awareness of global changes and the relevance of local actions encourage local agencies to lay an active role in building strategies for Climate Change adaptation and mitigation. The implementation of effective policies for a specific region requires a detailed knowledge of the territory, of its potentiality and problems. In this context Tuscany Region financed in 2004 the Kyoto Observatory project for monitoring carbon balance at regional and local scale. The balance provides periodical information about CO2 emissions of main sectors and carbon sequestration by forest ecosystems. Measures of forest sink are based on a multi-scale approach, from towers and airborne flux measurements to the application of regional biogeochemical models. The methodology of sink measurement, developed integrating state-of-the-art science and technologies, has been transferred to the Tuscany Regional Administration, enabling a timely operational monitoring of carbon balance at municipal scale thanks...
Aim This paper investigates the use of an ecosystem simulation model, FOREST-BGC, to estimate the... more Aim This paper investigates the use of an ecosystem simulation model, FOREST-BGC, to estimate the main ecophysiological processes (transpiration and photosynthesis) of Mediterranean coastal forest areas using remotely sensed data.
... Fabio Maselli1, Marta Chiesi1, Luca Fibbi1, Marco Moriondo1 and Marco Bindi2 ... R. Benesperi... more ... Fabio Maselli1, Marta Chiesi1, Luca Fibbi1, Marco Moriondo1 and Marco Bindi2 ... R. Benesperi, G. Ferretti, S. Benucci, S. Turrini, PL di Tommaso, M. Signorini, E. Bargelli, U. Miniati, C. Farioli, V. de Dominicis, S. Casini, A. Chiarucci, PE Tomei, M. Ansaldi, S. Maccioni, E. Guazzi ...
ABSTRACT A method has been recently presented to predict the net primary production NPP of Medite... more ABSTRACT A method has been recently presented to predict the net primary production NPP of Mediterranean forests by integrating conventional and remote-sensing data. This method was based on the use of two models, C-Fix and BIOME-BGC, whose outputs are combined with estimates of stem volume and tree age to predict the NPP of the examined ecosystems. This article investigates the possibility of deriving these two forest attributes from airborne high-resolution lidar data. The research was carried out in the San Rossore pine forest, a test site in Central Italy where several investigations have been conducted. First, estimates of stand stem volume and tree age were obtained from lidar data by application of a simplified method based on existing literature and a few ground measurements. The accuracy of these stand attributes was assessed by comparison with the independent ground data derived from a recent forest inventory. Next, the stem volume and tree age estimates were used to drive the NPP modelling strategy, whose outputs were evaluated against the inventory measurements of current annual increment CAI. The simplified lidar data processing method produces stand stem volume and tree age estimates having moderate accuracy, which are useful to feed the modelling strategy and predict CAI at a stand level. This method's success raises the possibility of integrating ecosystem modelling techniques and lidar data for the simulation of net forest carbon fluxes.
Analysis of Multi-Temporal Remote Sensing Images - Proceedings of the First International Workshop on Multitemp 2001, 2002
SIMULATION OF FOREST ECOSYSTEM PROCESSES BY THE ANALYSIS OF MULTITEMPORAL NOAA-AVHRR NDVI IMAGES ... more SIMULATION OF FOREST ECOSYSTEM PROCESSES BY THE ANALYSIS OF MULTITEMPORAL NOAA-AVHRR NDVI IMAGES MARTA CHIESI, LAURA ... 8. Rapetti F., Vittorini S.(1995)," Carta climatica della Toscana centro-settentrionale, centro-meridionale ed insulare", CNR ...
This paper builds on previous work by our research group which demonstrated the applicability of ... more This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.
This letter presents the application of a recently developed methodology to predict the net prima... more This letter presents the application of a recently developed methodology to predict the net primary production (NPP) of a Mediterranean pine forest in San Rossore, Central Italy. The methodology is based on the use of two models, C-Fix and BIOME-BGC, whose outputs ...
The current work deals with the use in a Mediterranean environment of a simulation model of fores... more The current work deals with the use in a Mediterranean environment of a simulation model of forest ecosystem processes which was originally created for temperate areas (FOREST-BGC). The model was calibrated and applied on two deciduous forest stands in Tuscany (Central Italy) by using conventional and remote sensing data as inputs. First, information on the two stands needed to initialise the model was derived from different sources, while meteorological data were extrapolated from a nearby station by an existing procedure (MT-Clim). Temporal profiles of leaf area index (LAI) were then derived both from direct ground measurement and from the processing of NOAA-AVHRR NDVI data. The model was calibrated using stand transpiration values obtained for 1997 by a sap flow method. Next, its performances were tested against the same transpiration values measured in 1998. The results obtained indicate that FOREST-BGC is capable of simulating water fluxes of Mediterranean forests when suitable LAI profiles are considered. Moreover, the derivation of these profiles from NDVI data can improve the model performance probably due to an enhanced consideration of the effects of the typical Mediterranean summer water stress. These results support the final objective of the work, which is the development of a procedure capable of integrating conventional and remote sensing data to operationally simulate water and carbon fluxes on a regional scale.
ABSTRACT pastoral resources in mountain areas. The utility of multispectral images was evacuate t... more ABSTRACT pastoral resources in mountain areas. The utility of multispectral images was evacuate to produce thematic cartography of the studied pastures and to determine their pastoral value, a useful parameter for management purposes. Data collected by the multispectral ASTER sensor, with a 15 m spatial resolution in the VISNIR, 30 m in the SWIR, and 90 m in TIR, and the MODIS sensor, with a daily temporal step and a 250 m spatial resolution, were used. The images are classified using a maximum likelihood algorithm, while multivariate locally calibrated regression is applied to extend the pastoral value over the whole area. Results show a low capability of the satellite images in discriminating the different pasture vegetation types, whereas the assessment of pastoral value produces more promising achievements (r = 0.647;, RMSE = 6.99).
Integrazione di dati meteorologici, pedologici e telerilevati per la stima del bilancio idrico di... more Integrazione di dati meteorologici, pedologici e telerilevati per la stima del bilancio idrico di aree semi-naturali Riassunto La stima del bilancio idrico di una regione è fondamentale per la programmazione e la gestione delle risorse idriche sul territorio, sia esso semi-naturale che agrario. Recentemente è stato messo a punto dall'IBIMET-CNR un metodo operativo, basato sull'utilizzo di dati telerilevati, per stimare l'evapotraspirazione reale (ET A), uno dei termini più importanti del bilancio idrico. L'unione di tale stima con informazioni relative ai suoli ricavabili dalla Banca Dati dei suoli di Regione Toscana realizzata dal Consorzio LaMMA, quali la profondità del suolo esplorabile da parte delle radici, la capacità di campo ed il punto di appassimento, permette di arrivare a stimare il contenuto idrico del suolo. Una valutazione preliminare di questa metodologia è stata effettuata confrontando le stime ottenute con misure di contenuto idrico del suolo raccol...
The current work presents the testing of a modeling strategy that has been recently developed to ... more The current work presents the testing of a modeling strategy that has been recently developed to simulate the gross and net carbon fluxes of Mediterranean forest ecosystems. The strategy is based on the use of a NDVI-driven parametric model, C-Fix, and of a biogeochemical model, BIOME-BGC, whose outputs are combined to simulate the behavior of forest ecosystems at different development stages. The performances of the modeling strategy are evaluated in three Italian study sites (San Rossore, Lecceto and Pianosa), where carbon fluxes are being measured through the eddy correlation technique. These sites are characterized by variable Mediterranean climates and are covered by different types of forest vegetation (pine wood, Holm oak forest and Macchia, respectively). The results of the tests indicate that the modeling strategy is generally capable of reproducing monthly GPP and NEE patterns in all three study sites. The highest accuracy is obtained in the most mature, homogenous pine wood of San Rossore, while the worst results are found in the Lecceto forest, where there are the most heterogeneous terrain, soil and vegetation conditions. The main error sources are identified in the inaccurate definition of the model inputs, particularly those regulating the site water budgets, which exert a strong control on forest productivity during the Mediterranean summer dry season. In general, the incorporation of NDVI-derived fAPAR estimates corrects for most of these errors and renders the forest flux simulations more stable and accurate.
Aircraft eddy covariance technique is a modern and powerful means to directly measure net ecosyst... more Aircraft eddy covariance technique is a modern and powerful means to directly measure net ecosystem exchange (NEE) over relatively large land areas. The NEE measurements taken by a specifically developed aircraft platform (Sky Arrow ERA) over a transect in Central Italy during an 18-month period are used to validate a recently proposed modeling strategy. The strategy is based on the integration of the outputs from a NDVI-driven parametric model, C-Fix, and a model of ecosystem processes, BIOME-BGC, and can simulate both gross and net land carbon fluxes over different spatial and temporal scales. The application of this strategy to 1-km resolution ground and remotely sensed data descriptive of the study area enables the production of NEE estimates comparable to the aircraft measurements. The agreement between the two data series is high, especially when averaging the modeling outputs over areas consistent with the Sky Arrow footprint (i.e. 1-2 pixels apart from the flight line). Fractional forest cover and NDVI are the two model driving variables which explain most spatial variability of the aircraft NEE measurements. The modeling strategy yields the best performances for spring-summer seasons, when vegetation photosynthetic and respiratory processes are higher and easier to simulate. These performances are finally commented with specific emphasis on the contribution brought by remote sensing information.
& Context Forest ecosystem carbon uptake is heavily affected by increasing drought in the Mediter... more & Context Forest ecosystem carbon uptake is heavily affected by increasing drought in the Mediterranean region. & Aims The objectives of this study were to assess the capacity of a modified 3-PG model to capture temporal variation in gross primary productivity (GPP), and ecosystem net carbon uptake (NEE) in two Mediterranean forest types. & Methods The model was upgraded from a monthly (3-PG) to a daily time step (3-PG day ), and a soil water balance routine was included to better represent soil water availability. The model was evaluated against seasonal GPP and NEE dynamics from eddy covariance measurements. & Results Simulated and measured soil water content values were congruent throughout the study period for both forest types. 3-PG day effectively described the following: GPP and NEE seasonal patterns; the transition of forest ecosystems from carbon sink to carbon source; however, the model overestimated diurnal ecosystem respiration values and failed to predict ecosystem respiration peaks. & Conclusions The model served as a rather effective tool to represent seasonal variation in gross primary productivity, and ecosystem net carbon uptake under Mediterranean droughtprone conditions. However, its semi-empirical nature and the simplicity inherent in the original model formulation are obstacles preventing the model working well for short-term daily predictions.
The current paper presents the development and testing of a multi-step methodology which integrat... more The current paper presents the development and testing of a multi-step methodology which integrates remotely sensed and ancillary data to estimate olive (Olea europaea L.) fruit yield in Tuscany (Central Italy). The processing of very high resolution (Ikonos) and high resolution (Landsat ETM+) images provides a map of olive tree canopy cover fraction for all Tuscany olive yards, which is used to extract olive tree NDVI values from MODIS imagery. The combination of these values with standard meteorological data within a modified parametric model (C-Fix) enables the prediction of daily olive tree gross primary production (GPP) for ten years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009). These GPP estimates are then joint to the respiration estimates of a bio-geochemical model (BIOME-BGC) to simulate olive tree net primary production (NPP). The NPP accumulated over proper periods of the ten growing seasons is finally converted into olive fruit yield, whose accuracy is assessed through comparison with provincial statistics. The methodology is only partly capable of capturing spatial and temporal olive fruit yield variability at province level, but can accurately reproduce inter-year yield variation over the entire region. The paper concludes with a discussion of the results achieved and with considerations on the research prospects.
The awareness of global changes and the relevance of local actions encourage local agencies to la... more The awareness of global changes and the relevance of local actions encourage local agencies to lay an active role in building strategies for Climate Change adaptation and mitigation. The implementation of effective policies for a specific region requires a detailed knowledge of the territory, of its potentiality and problems. In this context Tuscany Region financed in 2004 the Kyoto Observatory project for monitoring carbon balance at regional and local scale. The balance provides periodical information about CO2 emissions of main sectors and carbon sequestration by forest ecosystems. Measures of forest sink are based on a multi-scale approach, from towers and airborne flux measurements to the application of regional biogeochemical models. The methodology of sink measurement, developed integrating state-of-the-art science and technologies, has been transferred to the Tuscany Regional Administration, enabling a timely operational monitoring of carbon balance at municipal scale thanks...
Aim This paper investigates the use of an ecosystem simulation model, FOREST-BGC, to estimate the... more Aim This paper investigates the use of an ecosystem simulation model, FOREST-BGC, to estimate the main ecophysiological processes (transpiration and photosynthesis) of Mediterranean coastal forest areas using remotely sensed data.
... Fabio Maselli1, Marta Chiesi1, Luca Fibbi1, Marco Moriondo1 and Marco Bindi2 ... R. Benesperi... more ... Fabio Maselli1, Marta Chiesi1, Luca Fibbi1, Marco Moriondo1 and Marco Bindi2 ... R. Benesperi, G. Ferretti, S. Benucci, S. Turrini, PL di Tommaso, M. Signorini, E. Bargelli, U. Miniati, C. Farioli, V. de Dominicis, S. Casini, A. Chiarucci, PE Tomei, M. Ansaldi, S. Maccioni, E. Guazzi ...
ABSTRACT A method has been recently presented to predict the net primary production NPP of Medite... more ABSTRACT A method has been recently presented to predict the net primary production NPP of Mediterranean forests by integrating conventional and remote-sensing data. This method was based on the use of two models, C-Fix and BIOME-BGC, whose outputs are combined with estimates of stem volume and tree age to predict the NPP of the examined ecosystems. This article investigates the possibility of deriving these two forest attributes from airborne high-resolution lidar data. The research was carried out in the San Rossore pine forest, a test site in Central Italy where several investigations have been conducted. First, estimates of stand stem volume and tree age were obtained from lidar data by application of a simplified method based on existing literature and a few ground measurements. The accuracy of these stand attributes was assessed by comparison with the independent ground data derived from a recent forest inventory. Next, the stem volume and tree age estimates were used to drive the NPP modelling strategy, whose outputs were evaluated against the inventory measurements of current annual increment CAI. The simplified lidar data processing method produces stand stem volume and tree age estimates having moderate accuracy, which are useful to feed the modelling strategy and predict CAI at a stand level. This method's success raises the possibility of integrating ecosystem modelling techniques and lidar data for the simulation of net forest carbon fluxes.
Analysis of Multi-Temporal Remote Sensing Images - Proceedings of the First International Workshop on Multitemp 2001, 2002
SIMULATION OF FOREST ECOSYSTEM PROCESSES BY THE ANALYSIS OF MULTITEMPORAL NOAA-AVHRR NDVI IMAGES ... more SIMULATION OF FOREST ECOSYSTEM PROCESSES BY THE ANALYSIS OF MULTITEMPORAL NOAA-AVHRR NDVI IMAGES MARTA CHIESI, LAURA ... 8. Rapetti F., Vittorini S.(1995)," Carta climatica della Toscana centro-settentrionale, centro-meridionale ed insulare", CNR ...
This paper builds on previous work by our research group which demonstrated the applicability of ... more This paper builds on previous work by our research group which demonstrated the applicability of a parametric model, Modified C-Fix, for the monitoring of Mediterranean forests. Specifically, the model is capable of combining ground and remote sensing data to estimate forest gross primary production (GPP) on various spatial and temporal scales. Modified C-Fix is currently applied to all Italian forest areas using a previously produced data set of meteorological data and NDVI imagery descriptive of a ten-year period (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008). The obtained GPP estimates are further elaborated to derive forest net primary production (NPP) averages for 20 Italian Regions. Such estimates, converted into current annual increment of standing volume (CAI) through the use of specific coefficients, are compared to the data of a recent national forest inventory (INFC). The results obtained indicate that the modelling approach tends to overestimate the ground CAI values for all forest types. The correction of a drawback in the current model implementation leads to reduce this overestimation to about 9% of the INFC increments. The possible origins of this overestimation are investigated by examining the results of previous studies and of older forest inventories. The implications of using different NPP estimation methods are finally discussed in view of assessing the forest carbon budget on a national basis.
This letter presents the application of a recently developed methodology to predict the net prima... more This letter presents the application of a recently developed methodology to predict the net primary production (NPP) of a Mediterranean pine forest in San Rossore, Central Italy. The methodology is based on the use of two models, C-Fix and BIOME-BGC, whose outputs ...
The current work deals with the use in a Mediterranean environment of a simulation model of fores... more The current work deals with the use in a Mediterranean environment of a simulation model of forest ecosystem processes which was originally created for temperate areas (FOREST-BGC). The model was calibrated and applied on two deciduous forest stands in Tuscany (Central Italy) by using conventional and remote sensing data as inputs. First, information on the two stands needed to initialise the model was derived from different sources, while meteorological data were extrapolated from a nearby station by an existing procedure (MT-Clim). Temporal profiles of leaf area index (LAI) were then derived both from direct ground measurement and from the processing of NOAA-AVHRR NDVI data. The model was calibrated using stand transpiration values obtained for 1997 by a sap flow method. Next, its performances were tested against the same transpiration values measured in 1998. The results obtained indicate that FOREST-BGC is capable of simulating water fluxes of Mediterranean forests when suitable LAI profiles are considered. Moreover, the derivation of these profiles from NDVI data can improve the model performance probably due to an enhanced consideration of the effects of the typical Mediterranean summer water stress. These results support the final objective of the work, which is the development of a procedure capable of integrating conventional and remote sensing data to operationally simulate water and carbon fluxes on a regional scale.
ABSTRACT pastoral resources in mountain areas. The utility of multispectral images was evacuate t... more ABSTRACT pastoral resources in mountain areas. The utility of multispectral images was evacuate to produce thematic cartography of the studied pastures and to determine their pastoral value, a useful parameter for management purposes. Data collected by the multispectral ASTER sensor, with a 15 m spatial resolution in the VISNIR, 30 m in the SWIR, and 90 m in TIR, and the MODIS sensor, with a daily temporal step and a 250 m spatial resolution, were used. The images are classified using a maximum likelihood algorithm, while multivariate locally calibrated regression is applied to extend the pastoral value over the whole area. Results show a low capability of the satellite images in discriminating the different pasture vegetation types, whereas the assessment of pastoral value produces more promising achievements (r = 0.647;, RMSE = 6.99).
Integrazione di dati meteorologici, pedologici e telerilevati per la stima del bilancio idrico di... more Integrazione di dati meteorologici, pedologici e telerilevati per la stima del bilancio idrico di aree semi-naturali Riassunto La stima del bilancio idrico di una regione è fondamentale per la programmazione e la gestione delle risorse idriche sul territorio, sia esso semi-naturale che agrario. Recentemente è stato messo a punto dall'IBIMET-CNR un metodo operativo, basato sull'utilizzo di dati telerilevati, per stimare l'evapotraspirazione reale (ET A), uno dei termini più importanti del bilancio idrico. L'unione di tale stima con informazioni relative ai suoli ricavabili dalla Banca Dati dei suoli di Regione Toscana realizzata dal Consorzio LaMMA, quali la profondità del suolo esplorabile da parte delle radici, la capacità di campo ed il punto di appassimento, permette di arrivare a stimare il contenuto idrico del suolo. Una valutazione preliminare di questa metodologia è stata effettuata confrontando le stime ottenute con misure di contenuto idrico del suolo raccol...
The current work presents the testing of a modeling strategy that has been recently developed to ... more The current work presents the testing of a modeling strategy that has been recently developed to simulate the gross and net carbon fluxes of Mediterranean forest ecosystems. The strategy is based on the use of a NDVI-driven parametric model, C-Fix, and of a biogeochemical model, BIOME-BGC, whose outputs are combined to simulate the behavior of forest ecosystems at different development stages. The performances of the modeling strategy are evaluated in three Italian study sites (San Rossore, Lecceto and Pianosa), where carbon fluxes are being measured through the eddy correlation technique. These sites are characterized by variable Mediterranean climates and are covered by different types of forest vegetation (pine wood, Holm oak forest and Macchia, respectively). The results of the tests indicate that the modeling strategy is generally capable of reproducing monthly GPP and NEE patterns in all three study sites. The highest accuracy is obtained in the most mature, homogenous pine wood of San Rossore, while the worst results are found in the Lecceto forest, where there are the most heterogeneous terrain, soil and vegetation conditions. The main error sources are identified in the inaccurate definition of the model inputs, particularly those regulating the site water budgets, which exert a strong control on forest productivity during the Mediterranean summer dry season. In general, the incorporation of NDVI-derived fAPAR estimates corrects for most of these errors and renders the forest flux simulations more stable and accurate.
Aircraft eddy covariance technique is a modern and powerful means to directly measure net ecosyst... more Aircraft eddy covariance technique is a modern and powerful means to directly measure net ecosystem exchange (NEE) over relatively large land areas. The NEE measurements taken by a specifically developed aircraft platform (Sky Arrow ERA) over a transect in Central Italy during an 18-month period are used to validate a recently proposed modeling strategy. The strategy is based on the integration of the outputs from a NDVI-driven parametric model, C-Fix, and a model of ecosystem processes, BIOME-BGC, and can simulate both gross and net land carbon fluxes over different spatial and temporal scales. The application of this strategy to 1-km resolution ground and remotely sensed data descriptive of the study area enables the production of NEE estimates comparable to the aircraft measurements. The agreement between the two data series is high, especially when averaging the modeling outputs over areas consistent with the Sky Arrow footprint (i.e. 1-2 pixels apart from the flight line). Fractional forest cover and NDVI are the two model driving variables which explain most spatial variability of the aircraft NEE measurements. The modeling strategy yields the best performances for spring-summer seasons, when vegetation photosynthetic and respiratory processes are higher and easier to simulate. These performances are finally commented with specific emphasis on the contribution brought by remote sensing information.
& Context Forest ecosystem carbon uptake is heavily affected by increasing drought in the Mediter... more & Context Forest ecosystem carbon uptake is heavily affected by increasing drought in the Mediterranean region. & Aims The objectives of this study were to assess the capacity of a modified 3-PG model to capture temporal variation in gross primary productivity (GPP), and ecosystem net carbon uptake (NEE) in two Mediterranean forest types. & Methods The model was upgraded from a monthly (3-PG) to a daily time step (3-PG day ), and a soil water balance routine was included to better represent soil water availability. The model was evaluated against seasonal GPP and NEE dynamics from eddy covariance measurements. & Results Simulated and measured soil water content values were congruent throughout the study period for both forest types. 3-PG day effectively described the following: GPP and NEE seasonal patterns; the transition of forest ecosystems from carbon sink to carbon source; however, the model overestimated diurnal ecosystem respiration values and failed to predict ecosystem respiration peaks. & Conclusions The model served as a rather effective tool to represent seasonal variation in gross primary productivity, and ecosystem net carbon uptake under Mediterranean droughtprone conditions. However, its semi-empirical nature and the simplicity inherent in the original model formulation are obstacles preventing the model working well for short-term daily predictions.
The current paper presents the development and testing of a multi-step methodology which integrat... more The current paper presents the development and testing of a multi-step methodology which integrates remotely sensed and ancillary data to estimate olive (Olea europaea L.) fruit yield in Tuscany (Central Italy). The processing of very high resolution (Ikonos) and high resolution (Landsat ETM+) images provides a map of olive tree canopy cover fraction for all Tuscany olive yards, which is used to extract olive tree NDVI values from MODIS imagery. The combination of these values with standard meteorological data within a modified parametric model (C-Fix) enables the prediction of daily olive tree gross primary production (GPP) for ten years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009). These GPP estimates are then joint to the respiration estimates of a bio-geochemical model (BIOME-BGC) to simulate olive tree net primary production (NPP). The NPP accumulated over proper periods of the ten growing seasons is finally converted into olive fruit yield, whose accuracy is assessed through comparison with provincial statistics. The methodology is only partly capable of capturing spatial and temporal olive fruit yield variability at province level, but can accurately reproduce inter-year yield variation over the entire region. The paper concludes with a discussion of the results achieved and with considerations on the research prospects.
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