Integrating Multi-source Information via Fuzzy Classification Method for Wetland Grass Mapping

Late greening vegetation has been regarded as significant indicator of flood recessional wetlands ecosystem in the Poyang lake natural reserve (PLNNR). Mapping the wetlands, especially the distribution of late greening grassland is of great importance for PLNNR managers and decision makers either for ecosystem dynamic monitoring or habitat sustainability assessment. The aim of this paper is to explore the use of fuzzy classification methods to map wetlands land cover and to better represent the vegetation landscape. The proposed fuzzy rule-based system integrates information on NDVI, wetness and elevation and expert knowledge about vegetation growth condition and phenology. Nine types of land covers were classified, with four belonging to wetland vegetation. A traditional error matrix analysis has been used for accuracy assessment. The results show that fuzzy classification provides more detailed information on the possibility of vegetation presence, rather than presence/absence information obtained from a crisp classification. Fuzzy classification thus best represents vague objects and is less sensitive to poor data quality. * Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.