Assessing vegetation changes for parts of the Sudan and Chad during 2000-2010 using time series analysis of MODIS-NDVI

Phenological vegetation characteristics are valuable inputs to several ecosystem-related models: including carbon exchange and climate change. Phenological characteristics are effective measures of changes in vegetation in an area and are subject to the seasonal and inter-annual climatic variations. In arid and semi-arid ecosystems, precipitation is the main driving factor for changes in vegetation and phenological parameters. In this regard, remotely sensed vegetation indices are widely used. In the current study, time series of 16-day composite normalized difference vegetation index (NDVI) images from Moderate Resolution Imaging Spectroradiometer (MODIS) were analyzed to assess vegetation changes for parts of the Sudan and Chad (between 10o-20o Northern latitude and 23o-35o Eastern longitude) during 2000-2010. Spatial and temporal variation in NDVI and phenological (seasonality) parameters were assessed for the land cover classes shrubland, grassland, cropland and savanna. Mathematical models from TIMESAT, a program package developed for extracting seasonality parameters from a series of data captured using remote sensing techniques over time, were implemented to suppress the noisy patterns in NDVI and to extract phenological parameters. The observed changes were then explained by looking at the amount of rainfall. Even though the results cannot be generalized, majority of the cases depict an increase in the fitted NDVI, delay on the start and end of the growing seasons, shortening of growing season length, decrease in amplitude and integrals. However, statistical test outputs were not significant for most of the cases. This could be due to the effect of small sample sizes, which increase the likelihood of obtaining erroneous results and further inspection is recommended. In general, high temporal and spatial variations were evident. The temporal variation could mainly be attributed to the erratic nature of the rainfall. The spatial variation is also a factor of the strong north-south rainfall diversity. Even so, the results depict that rainfall amount only cannot explain the observed changes.