Determining the effect of spatial resolution in land use classification using optical aerial imagery

Unmanned Aircraft System (UAS), a low cost and time efficient remote sensing platform, can help public agencies obtain useful urban aerial imagery of cities and update land use information frequently, especially in natural colour bands. In this paper, a decision tree based land use classification approach using optical aerial imagery is proposed. First, land cover information is extracted through the Maximum Likelihood Classifier and tabulated with an Ownership parcel map. Second, a decision tree is generated to establish the relationship between land cover and land use. Taking advantage of the geometric characteristics of parcels, an organized land use parcel map is produced. Afterwards, by resampling the aerial imagery from 20 cm, 50 cm and 100 cm resolution, effects of spatial resolution in this classification approach are discussed and determined. This land use classification method is flexible and can be widely used in urban planning and landscape monitoring.