Geospatial analysis of change in net primary productivity, 1998-2013, Inner Mongolian Desert steppe region, China

Abstract

Net primary productivity (NPP) is a quantitative measure of the carbon absorption by plants per unit time and space. The NPP is a key indicator to evaluate the productivity of vegetation communities in the natural environment. Consistent data on terrestrial NPP are urgently needed to constrain model estimates of carbon fluxes and hence to refine our understanding of ecosystem responses to climate change. It could also be an indicator to represent certain land cover characteristics. This study analyzed NPP changes from 1998 to 2013 in the Inner Mongolian Desert Steppe region of China through estimation of annual NPP using multiyear 10-day SPOT VEGETATION NDVI data and meteorological observation data from 1998 to 2013 by using a modified Carnegie-Ames-Stanford Approach (CASA) model. ArcGIS and ENVI software was used for spatial data processing; NPP inversion was performed and an integrated program was used for the modified CASA model. We also used related spatial information technologies, such as geographic information system, global navigation satellite system and remote sensing technology, to determine some 1 km2 random sampling pixels and regularly selected four 1m2 quadrats in each pixel, and we measured aboveground net primary productivity (ANPP) for accuracy assessment of modelled NPP. The final results show that the NPP had many obvious geospatial changes during the period from 1998 to 2013 in the Inner Mongolian Desert Steppe region.