When we examine the National Land Cover Database 2006 (NLCD 2006) in a small scale, we find out that there are only 4.5 ha (50 pixels) of emergent herbaceous wetlands in Athens-Clarke County, Georgia. In order to testify that it is not simply due to mapping error or uncertainty, we propose a geographic knowledge discovery (GKD) process based on NLCD. The GKD process consists of data preparation, data preprocessing, feature extraction and knowledge consolidation. A case study ?What geomorphological characteristics accommodate emergent herbaceous wetlands in North Georgia? is presented to illustrate the process. Geomorphological characteristics refer to digital elevation model (DEM) and eight DEM-derived variables, which are proxies to geomorphological conditions. Geographic data are inherently spatial dependent and heterogeneous and such properties are considered in data preparation. In feature extraction, the goal of the study and the nature of the data are taken into consideration to select a suitable algorithm. In knowledge consolidation, three steps of validation ? with statistics, cross-validation and field survey ? are presented. The proposed methods can be extended to GKD from NLCD for other purposes. The GKD results testify that the small area of emergent herbaceous wetlands in Athens-Clarke County, Georgia, is not due to mapping error or uncertainty. The case study also proves that See5 algorithm performs very well to extract the learned knowledge. The procedure that we propose with NLCD can be applied to other environmental monitoring purpose.