Accuracy of crop-shelter thematic maps: A case study of maps obtained by spectral and textural classification of high-resolution satellite images

Accuracy assessment procedures are usually recommended in land-use/land-cover change studies to ascertain the quality of thematic maps produced by means of automated image classification methods. In this regard, the error matrix and accompanying accuracy measures (AMs) are widely used. Concerning thematic maps of crop-shelter coverage (CSC), high-resolution remote sensing images have been found to be suitable for the automated classification of greenhouses and several methodologies have been developed. However, methods to report the thematic map accuracy derived from these classifications still need to be standardized. Therefore, this study was undertaken with the aim to provide guidelines for determining a set of AMs suitable to report the accuracy of CSC thematic maps produced at local scale. In the case study, QuickBird RGB-band layers were combined with textural information computed on degraded QuickBird panchromatic layer to perform CSC supervised classifications in a study area located in South-Eastern Sicily (Italy) where protected cultivation is widespread. Statistical tests were performed on a number of AMs computed on the error matrices obtained from the automated image classifications of three different areas selected within the study area. The results of this study showed that user's accuracy was not influenced by the area selection and, therefore, can be used to report the accuracy of CSC thematic maps obtained by automated image classifications of other areas located within the study area. All the obtained classifications differed from a random one; and the use of textural information generally improved classifications' accuracy in comparison to that obtained by using only RGB-band layers.