Monitoring and modeling spatial and temporal patterns of grassland dynamics using time-series MODIS NDVI with climate and stocking data.

Li, Z., Huffman, E.C., McConkey, B.G., and Townley-Smith, L. (2013). "Monitoring and modeling spatial and temporal patterns of grassland dynamics using time-series MODIS NDVI with climate and stocking data.", Remote Sensing of Environment, 138, pp. 232-244. doi : 10.1016/j.rse.2013.07.020  Access to full text

Abstract

Degradation of grassland has become a worldwide environmental concern. This study examined temporal and spatial patterns of grassland potential productivity dynamics between 2000 and 2010 within community pastures (CPs) in Saskatchewan Canada. Data used in the study included Moderate-resolution Imaging Spectroradiometer (MODIS) 250 m time-series NDVI, accumulated precipitation (A-PPT) from September to August and annual stocking intensity (SI). We conducted Mann–Kendall analysis on grassland growing season NDVI (GS-NDVI), A-PPT and SI to demonstrate spatial variation in their temporal trends at local and regional scales. We developed both global Ordinary Linear Square (OLS) and Geographically Weighted Regression (GWR) models to analyze the impacts of climate variation and human activities such as grazing practice on potential pasture productivity from both temporal and spatial contexts. Results show that grasslands in most CPs had increasing trends in GS-NDVI for the time period, and no significantly decreasing trend was found over all CPs at the regional or ecoregional scales. A-PPT itself accounted for over 96% of inter-annual variation in grassland NDVI. At the regional level, the temporal trends in A-PPT and stocking intensity were more significant factors in accounting for spatial variation of NDVI than were A-PPT and SI per se. Results show that the past adopted grazing intensities did not significantly influence grassland potential productivity at either temporal or spatial scales in the study area.

Date modified: