# Remote Sensing and Bio-Geochemical Modeling of Forest Carbon Storage in Spain
## 3 Study Area and Data
### Data Used for the NPP Modeling
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Forest Type** & \(h\) **(m)** & \(T\) (\({}^{\circ}\)C)** & \(R_{\text{g}}\) **(M) m\({}^{-2}\)** & **PRE (mm)** & **PET (mm)** \\ \hline \multirow{2}{*}{**EBF**} & 584 & 14.53 & 5725 & 711 & 1193 \\  & (335) & (1.97) & (666) & (300) & (235) \\ \hline \multirow{2}{*}{**LDBF**} & 520 & 12.73 & 4863 & 1084 & 910 \\  & (186) & (0.97) & (524) & (307) & (139) \\ \hline \multirow{2}{*}{**HDBF**} & 1099 & 11.48 & 5272 & 850 & 936 \\  & (205) & (1.19) & (420) & (267) & (118) \\ \hline \multirow{2}{*}{**LENF**} & 484 & 14.38 & 5586 & 714 & 1153 \\  & (223) & (1.68) & (635) & (360) & (209) \\ \hline \multirow{2}{*}{**HENF**} & 1198 & 12.53 & 5742 & 604 & 1089 \\  & (290) & (1.54) & (348) & (183) & (165) \\ \hline \hline \end{tabular} \({}^{1}\)\(h\) is the elevation from sea level, \(T\) is the average mean annual air temperature, \(R_{\text{g}}\) is the average annual incoming global solar radiation, PRE is the average annual precipitation, and PET is the average annual potential evapotranspiration. Averages refer to the period considered in the present study (2005-2012) and were calculated from the datasets described in Section 3.3. Standard deviations are expressed between brackets.  
\end{table} 
Table 2: Descriptive information of the forest types considered in the present study 1. Figure 2: (**a**) Forest type map of peninsular Spain. OSA, NC, EBF, LDBF, HDBF, LENF, and HENF refer respectively to out of the study area, non-classified, evergreen broadleaved forest, low altitude deciduous broadleaved forest, high altitude deciduous broadleaved forest, low altitude evergreen needleleaved forest, and high altitude evergreen needleleaved forest. (**b**) Average annual (period 2005–2012) forest gross primary production (GPP) obtained using Equation (1). (**c**) Forest GSV produced as summarized in Section 3.3[28] and aggregated at 1-km spatial resolution. MODIS products MCD43A1 and MCD43A2 [41] for the period 2005-2012 were retrieved from the online Reverb, courtesy of the NASA EOSDIS Land Processes Distributed Active Archive Center, USGS/Earth Resources Observation and Science Center, Sioux Falls, South Dakota (reverb.echo.nasa.gov). MCD43A1 is a 500-m spatial resolution 8-day composite containing the BRDF parameters \(k_{0}\), \(k_{1}\), and \(k_{2}\). \(f_{\text{APAR}}\) was computed through the methodology reported in [30] from the BRDF parameters contained in MCD43A1 images (see Section 2), which were previously reprojected to a regular latitude/longitude 1-km spatial resolution grid. A noise-reduction and gap-filling method dependent on the quality of the measurements [42] was applied, and the 8-day\(f_{\text{APAR}}\) was linearly interpolated to obtain daily images. Soil texture (clay, sand, and silt content) maps [25] were downloaded from the European Soil Database ([[http://esdac.jrc.ec.europa.eu/resource-type/european-soil-database-soil-properties](http://esdac.jrc.ec.europa.eu/resource-type/european-soil-database-soil-properties)]([http://esdac.jrc.ec.europa.eu/resource-type/european-soil-database-soil-properties](http://esdac.jrc.ec.europa.eu/resource-type/european-soil-database-soil-properties))) and reprojected to regular longitude/latitude 1-km spatial resolution grids comprising the study area. A 1-km spatial resolution rooting depth map was obtained from a calibration of Biome-BGC in the study area. Daily GPP was first calculated using a production efficiency model optimized for the study area [8] in four sites where EC towers were placed. Several daily GPP series were also simulated using Biome-BGC for the same sites and varying the rooting depth. Both series were compared, and the optimum rooting depth was chosen as the one that resulted in the minimum root mean square error between them. After ascertaining that this methodology improved the accuracy of GPP simulated using Biome-BGC by comparing to EC-derived GPP, the methodology was extended to the whole study area and the rooting depth map was obtained.