# Creating a Regional MODIS Satellite-Driven Net Primary Production Dataset for European Forests
## 1 Introduction  
Net primary production (NPP), the difference between Gross Primary Production (GPP) and plant autotrophic respiration, is the net carbon or biomass fixed by vegetation through photosynthesis. NPP represents the allocation rate of photosynthetic products into plant biomass and can be used to measure the quantity of goods provided to society by ecosystems [1; 2; 3]. NPP of forest ecosystems is essential to estimate the potential supply of biomass for bioenergy, fiber and timber supply. NPP is also a key variable to assess environmental change impacts on ecosystems [4] since any variation in the growing conditions influences the carbon cycle due to changes in carbon uptake and/or respiration. As interest grows in utilizing forests for a \"bio-based economy\" [5; 6], more accurate and realistic forest productivity estimates become increasingly important. In addition, competing forest ecosystem services, such as biodiversity or and nature conservation, need to be considered to ensure sustainable use of our forests and to avoid unsustainable over-exploitation of renewable resources. Within the EU-28 160.9 million ha or 37.9% of the total land area are covered with forests [7]. These forests provide resources for the timber industry, the energy sector (24.3% of the energy in the EU-28 is generated from renewable sources of which 64.2% consists of forest biomass and waste [8]), but also for non-timber ecosystem services such as clean air, water, biodiversity or protection against natural hazards. Accurate and consistent forest information is a precondition for assessing the production and harvesting potential of forest resources in Europe. There are conceptually different data sources and methods to assess forest productivity like:  
1. The MODIS algorithm MOD17 uses remotely sensed satellite-data and climate data to predict spatially and temporally continuous NPP and GPP (Gross Primary Production or carbon assimilation) based on an ecophysiological modelling approach [2]. In addition to satellite reflectance data and climate data, it requires the biophysical properties of land cover types, which are stored in the Biome Property Look-Up Tables (BPLUT) [9]. 2. National forest inventory data can be used to assess the timber volume stocks as well as volume increment and removal, if repeated observations are available [10]. This terrestrial bottom-up approach collects forest information by measuring sample plots arranged on a systematic grid design across larger areas. In combination with biomass expansion factors or biomass functions, volume or tree information can be converted into biomass or carbon estimates to account for differences in wood densities, the carbon fraction and different allocation into compartments [11; 12]. 3. Flux towers record the gas-exchange in plant-atmosphere interactions [13], which can be used to derive GPP from Net Ecosystem exchange (NEE). NEE is estimated using eddy covariance data, climate measurements and other ancillary data [14]. Net Primary Production (NPP) from (i) top-down satellite-driven MOD17 algorithm and (ii) bottom-up NPP estimates using terrestrial forest inventory data were compared in a pilot study for Austria on national scale [15]. Top-down and bottom-up refer to the level of scaling of the primary recorded information (for MOD17 1-km remote sensing products and for Terrestrial NPP single tree observations). Our definition for top-down differs from traditional carbon cycle modelling [16]. This study wants to extend and test this concept for Europe on a continental scale. For this purpose, we obtain two wall-to-wall spatially-explicit and consistent MODIS NPP datasets by acquiring the global dataset using global climate driver and by creating a regional dataset MODIS EURO using 1-km European climate data. We evaluate these two datasets by comparing with the NPP derived from forest inventory data from 12 European countries.