Image segmentation is basic task of object-based image analysis (OBIA). The result is the creation of image objects defined as individual areas with shape and spectral homogeneity, which one may recognize as segments or patches in the landscape.Image object is characterized by several features defined based on layer values, texture, shape and context of the object. OBIA applies an integration approach for information extraction including provision of units, regionalization, classification and interpretation. Basically image objects have spectral, shape, and hierarchical characteristics. These characteristic attributes are called features. Features are used as source of information to define the inclusion or exclusion parameters used to classify image objects. In practice, image analyst require trial and error to justify an optimum scale for multiresolution segmentation. The main objective was to examine an optimum scale of multiresolution segmentation for applying to pan-sharpened Landsat-8 data for land use and land cove (LULC) classification under OBIA. The study area covers the dominant forest land part of Wang Nam Khieo and agricultural land part of Pak thong Chai districts of Nakhon Ratchasima province (Figure 1).