PROGRESS IN GEOGRAPHY ›› 2006, Vol. 25 ›› Issue (6): 21-32.doi: 10.11820/dlkxjz.2006.06.003

• Original Articles • Previous Articles     Next Articles

The Methods of Simulating Vegetation Growing Season Based on NOAA NDVI

WANG Hong,LI Xiaobing,YING Ge,WANG Dandan,LONG Huiling   

  1. College of Resources Science and Technology, Beijing Normal University, Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing 100875| China
  • Received:2006-04-01 Revised:2006-08-01 Online:2006-11-25 Published:2006-11-25


In recent years, estimating vegetation growing season on large scale has become a sig-nificant scientific field in global climate change studies. NOAA/AVHRR NDVI provides important means of research on temporal and spatial variability of vegetation growing season. This paper has summarized, compared and analyzed methods of estimating beginning, end, length of vegetation growing season on the basis of NDVI: NDVI threshold, NDVI time series analysis, combination of frequency distribution pattern of plant phenology with NDVI, principal component analysis, curves fitting model and so on. Influenced by different factors, each method has different limitations in application. Therefore, it is necessary to seek better methods for determining interannual and regional distribution variability of vegetation growing season. And on the basis of previous studies, growing season of grassland in Xilinhaote from 1991 to 1999 is estimated by NDVI threshold method, smoothed moving average, the greatest change slope, and curves fitting model. Then the results were verified with grassland greenup by field survey. Results shows that, combining with field surveying data, grassland greeup with better accuracy is acquired with NDVI threshold method, and curves fitting model can be applied to monitoring vegetation growing season on large scale. However, it is difficult for actual curves to match the simulated curves. Therefore, it is very important to choose appropriate fitting curves for subsequent studies. Furthermore, it is necessary to carry out further research on interannual variability of vegetation growing season.

Key words: NDVI, temporal and spatial variability, vegetation growing season