Establishment and Application of the Modified Chen NDVI Model Integrated with Ground Object Classification

Heterogeneous land surface causes the scale effect of remotely sensed land surface parameters. Addressing on quantitatively describing the influence of different ground objects on scale effect of the common surface parameter normalized difference vegetation index (NDVI), the paper proposed an improved NDVI scale transformation model. The model integrated accurate classification information from medium- or high- spatial resolution remote sensing images to improve the traditional Chen NDVI scale conversion model, and showed its superiority for NDVI scale effect description. Xiamen was taken as the experimental area for the study and the conclusions could be obtained from the experimental results. Compared with the traditional Chen NDVI model with rough information, the improved Chen NDVI model incorporating fine ground information provides a finer and more quantitative description of the influence of different land types on the NDVI scale effect. Furthermore, it is found that the presence of water is the key factor underlying the NDVI scale effect. The conclusions of this study have important implications for the scale effect research of other NDVI-like surface parameters such as ratio vegetation index (RVI), normalized difference built-up index (NDBI), normalized burn ratio (NBR).