Climate and physiological controls of vegetation gross primary production (GPP) vary in space and... more Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited (F c ) and radiationlimited (Fr) assimilation rate. F c is estimated from canopy conductance while Fr is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO 2 concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy-and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r 2 = 0.72, root mean square error, RMSE = 2.48 μmol C m 2 s −1 , relative percentage error, RPE = −11%), over 8-day periods (r 2 = 0.78 RMSE = 2.09 μmol C m 2 s −1 ,RPE = −10%), over months (r 2 = 0.79, RMSE = 1.93 μmol C m 2 s −1 , RPE = −9%) and over years (r 2 = 0.54, RMSE = 1.62 μmol C m 2 s −1 , RPE = −9%). Using the model we estimated global GPP of 107 Pg C y −1 for 2000-2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome-or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration.
Unha das actividades do IBADER é a publicación e difusión de información científica e técnica sob... more Unha das actividades do IBADER é a publicación e difusión de información científica e técnica sobre o medio rural desde unha perspectiva pluridisciplinar. Con este obxectivo publícase a revista Recursos Rurais orientada a fortalecer as sinerxías entre colectivos vinculados ao I+D+I no ámbito da conservación e xestión da Biodiversidade e do Medio Ambiente dos espacios rurais, os Sistemas de Produción Agrícola, Gandeira, Forestal e a Planificación do Territorio, tendentes a propiciar o Desenvolvemento Sostible dos recursos naturais.
Forest fires play a critical role in landscape transformation, vegetation succession, soil degrad... more Forest fires play a critical role in landscape transformation, vegetation succession, soil degradation and air quality. Improvements in fire risk estimation are vital to reduce the negative impacts of fire, either by lessen burn severity or intensity through fuel management, or by aiding the natural vegetation recovery using post-fire treatments. This paper presents the methods to generate the input variables and the risk integration developed within the Firemap project (funded under the Spanish Ministry of Science and Technology) to map wildland fire risk for several regions of Spain. After defining the conceptual scheme for fire risk assessment, the paper describes the methods used to generate the risk parameters, and presents proposals for their integration into synthetic risk indices. The generation of the input variables was based on an extensive use of geographic information system and remote sensing technologies, since the project was intended to provide a spatial and temporal assessment of risk conditions. All variables were mapped at 1 km 2 spatial resolution, and were integrated into a web-mapping service system. This service was active in the summer of 2007 for semi-operational testing of end-users. The paper also presents the first validation results of the danger index, by comparing temporal trends of different danger components and fire occurrence in the different study regions.
... METHODOLOGY Quercus ilex SPECIFIC LUT Marta Yebra, Angela De Santis and Emilio Chuvieco Depar... more ... METHODOLOGY Quercus ilex SPECIFIC LUT Marta Yebra, Angela De Santis and Emilio Chuvieco Department of Geography. University of Alcalá. Madrid. Spain. ... Journal of Geophysical Research - Biosciences, 111. Yebra, M., Chuvieco, E., & Riaño, D. (2007). ...
... Department of Geography, University of Alcalá, Calle Colegios 2, 28801 Alcalá de Henares (Mad... more ... Department of Geography, University of Alcalá, Calle Colegios 2, 28801 Alcalá de Henares (Madrid-Spain), [email protected], marta.yebra@uah ... Laboratory radiometry experimentation at leaf level was performed with Cork oak (Quercus suber) (a Mediterranean ...
... Marta Yebra, Angela De Santis & Emilio Chuvieco Department of Geography, University o... more ... Marta Yebra, Angela De Santis & Emilio Chuvieco Department of Geography, University of Alcalá, Calle Colegios 2, Alcalá de Henares, Madrid 28801, Spain. ... 2003). Others have relied upon experimental data in controlled conditions (Riaño et al. 2005). ...
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation me... more We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the Penman-Monteith (PM) equation was inverted to obtain surface conductance (G s ), for dry plant canopies. The G s values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-G s approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R 2 ) across all sites, with an average RMSE = 38 W m −2 and R 2 = 0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE = 60 W m −2 and R 2 = 0.22, while the EF regressions an average RMSE = 42 W m −2 and R 2 = 0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE > 44 W m −2 and R 2 b 0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE = 28.4 W m −2 , R 2 = 0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE = 23.8 W m −2 and R 2 = 0.68), cropland (RMSE = 29.2 W m −2 and R 2 = 0.86) and woody savannas (RMSE = 25.4 W m −2 and R 2 = 0.82), while the VI-based crop coefficient (K c ) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE = 27 W m −2 and R 2 = 0.7 in both cases). Using the ensemble-average of ET as estimated using NDVI, EVI and K c we computed global grids of dry canopy conductance (G c ) from which annual statistics were extracted to characterise different functional types. The resulting G c values can be used to parameterize land surface models.
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation me... more We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the Penman-Monteith (PM) equation was inverted to obtain surface conductance (G s ), for dry plant canopies. The G s values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-G s approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R 2 ) across all sites, with an average RMSE = 38 W m −2 and R 2 = 0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE = 60 W m −2 and R 2 = 0.22, while the EF regressions an average RMSE = 42 W m −2 and R 2 = 0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE > 44 W m −2 and R 2 b 0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE = 28.4 W m −2 , R 2 = 0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE = 23.8 W m −2 and R 2 = 0.68), cropland (RMSE = 29.2 W m −2 and R 2 = 0.86) and woody savannas (RMSE = 25.4 W m −2 and R 2 = 0.82), while the VI-based crop coefficient (K c ) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE = 27 W m −2 and R 2 = 0.7 in both cases). Using the ensemble-average of ET as estimated using NDVI, EVI and K c we computed global grids of dry canopy conductance (G c ) from which annual statistics were extracted to characterise different functional types. The resulting G c values can be used to parameterize land surface models.
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation me... more We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the Penman-Monteith (PM) equation was inverted to obtain surface conductance (G s ), for dry plant canopies. The G s values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-G s approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R 2 ) across all sites, with an average RMSE = 38 W m −2 and R 2 = 0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE = 60 W m −2 and R 2 = 0.22, while the EF regressions an average RMSE = 42 W m −2 and R 2 = 0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE > 44 W m −2 and R 2 b 0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE = 28.4 W m −2 , R 2 = 0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE = 23.8 W m −2 and R 2 = 0.68), cropland (RMSE = 29.2 W m −2 and R 2 = 0.86) and woody savannas (RMSE = 25.4 W m −2 and R 2 = 0.82), while the VI-based crop coefficient (K c ) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE = 27 W m −2 and R 2 = 0.7 in both cases). Using the ensemble-average of ET as estimated using NDVI, EVI and K c we computed global grids of dry canopy conductance (G c ) from which annual statistics were extracted to characterise different functional types. The resulting G c values can be used to parameterize land surface models.
Climate and physiological controls of vegetation gross primary production (GPP) vary in space and... more Climate and physiological controls of vegetation gross primary production (GPP) vary in space and time. In many ecosystems, GPP is primary limited by absorbed photosynthetically-active radiation; in others by canopy conductance. These controls further vary in importance over daily to seasonal time scales. We propose a simple but effective conceptual model that estimates GPP as the lesser of a conductance-limited (F c ) and radiationlimited (Fr) assimilation rate. F c is estimated from canopy conductance while Fr is estimated using a light use efficiency model. Both can be related to vegetation properties observed by optical remote sensing. The model has only two fitting parameters: maximum light use efficiency, and the minimum achieved ratio of internal to external CO 2 concentration. The two parameters were estimated using data from 16 eddy covariance flux towers for six major biomes including both energy-and water-limited ecosystems. Evaluation of model estimates with flux tower-derived GPP compared favourably to that of more complex models, for fluxes averaged; per day (r 2 = 0.72, root mean square error, RMSE = 2.48 μmol C m 2 s −1 , relative percentage error, RPE = −11%), over 8-day periods (r 2 = 0.78 RMSE = 2.09 μmol C m 2 s −1 ,RPE = −10%), over months (r 2 = 0.79, RMSE = 1.93 μmol C m 2 s −1 , RPE = −9%) and over years (r 2 = 0.54, RMSE = 1.62 μmol C m 2 s −1 , RPE = −9%). Using the model we estimated global GPP of 107 Pg C y −1 for 2000-2011. This value is within the range reported by other GPP models and the spatial and inter-annual patterns compared favourably. The main advantages of the proposed model are its simplicity, avoiding the use of uncertain biome-or land-cover class mapping, and inclusion of explicit coupling between GPP and plant transpiration.
Unha das actividades do IBADER é a publicación e difusión de información científica e técnica sob... more Unha das actividades do IBADER é a publicación e difusión de información científica e técnica sobre o medio rural desde unha perspectiva pluridisciplinar. Con este obxectivo publícase a revista Recursos Rurais orientada a fortalecer as sinerxías entre colectivos vinculados ao I+D+I no ámbito da conservación e xestión da Biodiversidade e do Medio Ambiente dos espacios rurais, os Sistemas de Produción Agrícola, Gandeira, Forestal e a Planificación do Territorio, tendentes a propiciar o Desenvolvemento Sostible dos recursos naturais.
Forest fires play a critical role in landscape transformation, vegetation succession, soil degrad... more Forest fires play a critical role in landscape transformation, vegetation succession, soil degradation and air quality. Improvements in fire risk estimation are vital to reduce the negative impacts of fire, either by lessen burn severity or intensity through fuel management, or by aiding the natural vegetation recovery using post-fire treatments. This paper presents the methods to generate the input variables and the risk integration developed within the Firemap project (funded under the Spanish Ministry of Science and Technology) to map wildland fire risk for several regions of Spain. After defining the conceptual scheme for fire risk assessment, the paper describes the methods used to generate the risk parameters, and presents proposals for their integration into synthetic risk indices. The generation of the input variables was based on an extensive use of geographic information system and remote sensing technologies, since the project was intended to provide a spatial and temporal assessment of risk conditions. All variables were mapped at 1 km 2 spatial resolution, and were integrated into a web-mapping service system. This service was active in the summer of 2007 for semi-operational testing of end-users. The paper also presents the first validation results of the danger index, by comparing temporal trends of different danger components and fire occurrence in the different study regions.
... METHODOLOGY Quercus ilex SPECIFIC LUT Marta Yebra, Angela De Santis and Emilio Chuvieco Depar... more ... METHODOLOGY Quercus ilex SPECIFIC LUT Marta Yebra, Angela De Santis and Emilio Chuvieco Department of Geography. University of Alcalá. Madrid. Spain. ... Journal of Geophysical Research - Biosciences, 111. Yebra, M., Chuvieco, E., & Riaño, D. (2007). ...
... Department of Geography, University of Alcalá, Calle Colegios 2, 28801 Alcalá de Henares (Mad... more ... Department of Geography, University of Alcalá, Calle Colegios 2, 28801 Alcalá de Henares (Madrid-Spain), [email protected], marta.yebra@uah ... Laboratory radiometry experimentation at leaf level was performed with Cork oak (Quercus suber) (a Mediterranean ...
... Marta Yebra, Angela De Santis & Emilio Chuvieco Department of Geography, University o... more ... Marta Yebra, Angela De Santis & Emilio Chuvieco Department of Geography, University of Alcalá, Calle Colegios 2, Alcalá de Henares, Madrid 28801, Spain. ... 2003). Others have relied upon experimental data in controlled conditions (Riaño et al. 2005). ...
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation me... more We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the Penman-Monteith (PM) equation was inverted to obtain surface conductance (G s ), for dry plant canopies. The G s values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-G s approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R 2 ) across all sites, with an average RMSE = 38 W m −2 and R 2 = 0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE = 60 W m −2 and R 2 = 0.22, while the EF regressions an average RMSE = 42 W m −2 and R 2 = 0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE > 44 W m −2 and R 2 b 0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE = 28.4 W m −2 , R 2 = 0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE = 23.8 W m −2 and R 2 = 0.68), cropland (RMSE = 29.2 W m −2 and R 2 = 0.86) and woody savannas (RMSE = 25.4 W m −2 and R 2 = 0.82), while the VI-based crop coefficient (K c ) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE = 27 W m −2 and R 2 = 0.7 in both cases). Using the ensemble-average of ET as estimated using NDVI, EVI and K c we computed global grids of dry canopy conductance (G c ) from which annual statistics were extracted to characterise different functional types. The resulting G c values can be used to parameterize land surface models.
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation me... more We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the Penman-Monteith (PM) equation was inverted to obtain surface conductance (G s ), for dry plant canopies. The G s values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-G s approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R 2 ) across all sites, with an average RMSE = 38 W m −2 and R 2 = 0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE = 60 W m −2 and R 2 = 0.22, while the EF regressions an average RMSE = 42 W m −2 and R 2 = 0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE > 44 W m −2 and R 2 b 0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE = 28.4 W m −2 , R 2 = 0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE = 23.8 W m −2 and R 2 = 0.68), cropland (RMSE = 29.2 W m −2 and R 2 = 0.86) and woody savannas (RMSE = 25.4 W m −2 and R 2 = 0.82), while the VI-based crop coefficient (K c ) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE = 27 W m −2 and R 2 = 0.7 in both cases). Using the ensemble-average of ET as estimated using NDVI, EVI and K c we computed global grids of dry canopy conductance (G c ) from which annual statistics were extracted to characterise different functional types. The resulting G c values can be used to parameterize land surface models.
We compared estimates of actual evapotranspiration (ET) produced with six different vegetation me... more We compared estimates of actual evapotranspiration (ET) produced with six different vegetation measures derived from the MODerate resolution Imaging Spectroradiometer (MODIS) and three contrasting estimation approaches using measurements from eddy covariance flux towers at 16 FLUXNET sites located over six different land cover types. The aim was to assess optimal approaches in using optical remote sensing to estimate ET. The first two approaches directly regressed various MODIS vegetation indices (VIs) and products such as leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR) with ET and evaporative fraction (EF). In the third approach, the Penman-Monteith (PM) equation was inverted to obtain surface conductance (G s ), for dry plant canopies. The G s values were then regressed against the MODIS data products and used to parameterize the PM equation for retrievals of ET. Jack-Knife cross-validation was used to evaluate the various regression models against observed ET. The PM-G s approach provided the lowest root mean square error (RMSE), and highest determination coefficients (R 2 ) across all sites, with an average RMSE = 38 W m −2 and R 2 = 0.72. Direct regressions of observed ET against the VIs resulted in an average RMSE = 60 W m −2 and R 2 = 0.22, while the EF regressions an average RMSE = 42 W m −2 and R 2 = 0.64. The MODIS LAI and fPAR product produced the poorest estimates of ET (RMSE > 44 W m −2 and R 2 b 0.6); while the VIs each performed best for some of the land cover types. The enhanced vegetation index (EVI) produced the best ET estimates for evergreen needleleaf forest (RMSE = 28.4 W m −2 , R 2 = 0.66). The normalized difference vegetation index (NDVI) best estimated ET in grassland (RMSE = 23.8 W m −2 and R 2 = 0.68), cropland (RMSE = 29.2 W m −2 and R 2 = 0.86) and woody savannas (RMSE = 25.4 W m −2 and R 2 = 0.82), while the VI-based crop coefficient (K c ) yielded the best estimates for evergreen and deciduous broadleaf forests (RMSE = 27 W m −2 and R 2 = 0.7 in both cases). Using the ensemble-average of ET as estimated using NDVI, EVI and K c we computed global grids of dry canopy conductance (G c ) from which annual statistics were extracted to characterise different functional types. The resulting G c values can be used to parameterize land surface models.
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