Improved Textural Built-Up Presence Index for Automatic Recognition of Human Settlements in Arid Regions With Scattered Vegetation

The so-called PANTEX methodology for the automatic recognition of built-up areas is based on analysis of image textural measures extracted using anisotropic rotation-invariant gray-level co-occurrence matrix (GLCM) statistics . These measures may overestimate the built-up areas in case of presence of scattered trees having the same spatial pattern of settlements. This overestimation is especially remarkable in case of bright soil background as in desert areas. In this paper we compare two options able to reduce this problem. One method is based on the subtraction of the vegetated areas from the built-up areas detected using the PANTEX index. The other method is based on the introduction of a morphological filtering step that pre-selects the image information to be ingested by the textural analysis phase. The test presented here uses multispectral Quick Bird satellite data input at the spatial resolution of 2.4 meters. In the selected test area, the application of the standard PANTEX procedure achieves the overall accuracy of 67.92%. The improvement of the procedure using the vegetation index achieves the accuracy of 70.37%, while the improvement based on morphological filtering achieves the accuracy of 88.69%, with an increase respect to the standard procedure of 2.44% and 20.76%, respectively.