## 1 Introduction  
Terrestrial net primary productivity (NPP) is one of the most important ecosystem variables that have been studied extensively during the last 40 years [1]. It is a fundamental ecological variable, not only because it measures the terrestrial carbon dioxide assimilation, but it also indicates the type (e.g., crops, forests) of the land surface area and status of a wide range of ecological processes. Practical considerations for estimating NPP exist in its utility to measure crop yield, forest productivity and other economically and socially significant products of vegetation origin. Determining the trend and variability of terrestrial NPP and its response to climate change is critical for understanding the potential carbon cycle changes in response to temperature, precipitation and other factors such as CO\({}_{2}\) fertilization. Modern ecology relies heavily on experiments, both in laboratory and in field settings. However, true global measurements could only be made using satellite remote sensing which provides large sample sizes. Global ecosystem models provide the basis for computing a satellite-based estimate of NPP. These models range from simple ones based on light use efficiency (LUE) to more mechanistic models based on \"Soil-Vegetation-Atmospheric-Transfer\" (SVAT) schemes designed to capture variability in biospheric processes. LUE-based models are less complex and easily use remotely sensed data and map primary productivity of the terrestrial biosphere over large areas. Satellite data-driven LUE models such as C-Fix [2], Carnegie-AMES-Stanford-Approach (CASA) [3], Global Production Efficiency Model (GLO-PEM) [4], Simple Diagnostic Biosphere Model (SDBM) [5], Terrestrial Uptake and Release of Carbon (TURC) [6] and Moderate Resolution Imaging Spectroradiometer (MODIS) NPP algorithm [7; 8; 9] have been developed to produce spatiotemporal pattern of NPP over continents or global land surface. Estimates of daily gross primary productivity (GPP) and annual net primary productivity (NPP) at the 1-km spatial resolution are now produced operationally for the global terrestrial surface using imagery fromthe MODIS sensor [9]. NPP products can also be derived from process-based SVAT schemes [10]. Investigation of vegetation responses to climatic changes using climatic data and satellite observations of vegetation activity for 1982-1999 [8] indicated that the global NPP increased by 6% (3.4 peta grams of carbon (PgC) over 18 years). The largest increase was in tropical ecosystems where Amazon rain forests accounted for 42% of the global increase, owing mainly to decreased cloud cover and the resulting increase in solar radiation [8]. In qualitative agreement with these results, using satellite observation and the GLO-PEM model for 1981-2000, an increasing trend in terrestrial NPP that was superimposed on large seasonal and interannual variations was found in another study [11]. However, estimates for the recent period 2000-2009 [12] suggest a reduction in the global NPP of 0.55 PgC. Large-scale droughs have been cited as the likely cause during this period. A drying trend in the southern hemisphere was found to be associated with a decreased NPP in that area which counteracted the increased NPP in the northern hemisphere. Estimates of NPP for India vary widely depending on the observational data and the terrestrial carbon cycle model used. For 1980, the annual NPP is estimated at 1.24 PgC, based on observed carbon inventory data in various ecosystems [13]; for the mid-eighties, it is approximately 1.32-1.59 PgC [14]. Another study [15], using 10-day global NDVI (Normalized Difference Vegetation Index) composites along with C-Fix model for June 1998-May 1999 has estimated a value of 2.18 PgC. The estimate of NPP for India using the CASA model is 1.57 PgC for 2003, which is slightly higher than the estimates by the C-Fix (1.45 PgC) and MODIS NPP algorithms (1.30 PgC) for the same period [16].