Abstract
The Normalized Difference Vegetation Index (NDVI) is one of the typical indicators of terrestrial vegetation productivity. But it becomes difficult to acquire NDVI when it has the influence of clouds. Toward the acquisition of exact NDVI, it is necessary to estimate NDVI removed the influence of clouds. In this paper, first we investigated the relationship between NDVI and climate parameters by using observed precipitation, solar radiation, average air temperature, minimum air temperature and Growing Degree Days (GDD) data sets collected from 85 stations in Japan. It was found that the most significant correlation existed between NDVI and accumulated average air temperature, and the maximum average correlation coefficient was 0.93. Second, we formulated logistic and double-exponential function models for estimating NDVI by using accumulated average air temperature in 1999 and 2000. A double-exponential function model could formulate with more sufficient accuracy, and the average coefficient of determination was 0.89. As a result of comparing annual NDVI of observed and estimated in 2001, average RMSE (Root Mean Square Error) was 0.0589.
