This study outlines a method for generating automated micro-landform map of a alluvial plain by combining Shuttle Radar Topographic Mission Digital Elevation Model (SRTM DEM) and satellite. Average elevation and channel feature extracted from DEM are associated with soil moist condition (thresholds of Modified Normalized Difference Water Index – MNDWI) from remotely sensed images based on a logic rule. This process is conducted in GRASS GIS. Although SRTM DEM is pretty good for landform mapping by digital terrain analyses, it is rather useful for landform types (mountain, hill, plain, etc.) or micro-landform in high relief areas. It is hard to isolate micro-landforms in alluvial plain (flat and low relief) by only SRTM DEM whereas satellite images provide land surface characteristics (moist condition, etc.) that are close related to micro-landform formation. Another merit of this automated method in comparison of manual method is time-saving, objective process and result and simple for editing. Although, theoretically, manual mapping by aerial photos and topographic maps combined with field survey is definitely more accurate; factually it is quite subjectively relied on human interpretation. Meanwhile automated mapping process is rather objective, as a result create more accurate boundaries of landform objects of some units (terraces, sand dunes) but less detailed in other units (natural levees). A case study is in the alluvial plain of the Vu Gia-Thu Bon river, central Vietnam.