Land Cover Classification in Qinling Mountains in China, using Time-Series MODIS NDVI Data

A new classification logic for land cover at regional scale is proposed. The critical features of this classification are that: it is based on spectrum (color) and primary attributes of plant-canopy structure, that are important to globe change modeling and can be measured in the field for validation or/and by remote sensing; according to the phonological difference among broadly defined vegetation, some typical land cover is easily distinguished by using the characteristics of land cover with the change of seasons; mixed land cover is differentiated by its constituent characteristics and influence on land surface processes. A first test of this logic for the middle Qinling mountains in Shanxi province, China is presented based on time-series MODIS 250 m NDVI imageries. Seven basic classes and eleven sub-classes were identified and mapped for the study area. The overall classification accuracy equals to 74.41% and overall kappa statistics 66.65%.