  In this paper we propose the use of multiple local binary patterns(LBPs) to
effectively classify land use images. We use the UC Merced 21 class land use
image dataset. Task is challenging for classification as the dataset contains
intra class variability and inter class similarities. Our proposed method of
using multi-neighborhood LBPs combined with nearest neighbor classifier is able
to achieve an accuracy of 77.76%. Further class wise analysis is conducted and
suitable suggestion are made for further improvements to classification
accuracy.
