摘要：The detection of alterations in land use and cover is an operation in Remote Sensing which adds a time dimension to the analysis of information in images. This is done when images are compared, by groups of two, at certain space and time, looking for spectral responses stored in pairs of homologous pixels, through the application of thresholds which lead to the differentiation between change and non-change. A point-to-point, or instant-to-instant analysis, permits to infer on the amount and quality of alterations detected in a region, during a certain period. The comparative analysis between two or more of these results, via a time series of images, informs on the dynamics of transformations in other aspects, as topology, intensity, kind of change (substitution or conversion), and change rate. Several techniques are available to detect alterations in land use and cover, from digital images collected by orbital sensors. Two larger groups can be highlighted: pre-classification techniques, and post-classification techniques. They differ basically on over which products the thresholds defining changes are applied, these products being either thematic ones for image classification, or the image itself. This work uses detection techniques based on image subtraction in post-classification with the Maximum Likelihood. The objective is to estimate the sensitivity and adequacy of these techniques for the detection and analysis of changes in land use and cover during two comparison periods: the first one is from 1988 to 2001; the second, from 2001 to 2006. Besides, the whole 18-years period is studied to detect tendencies of the transformation of the region. The study area is at the Campanha Sul region, at Rio Grande do Sul State, Brazil. It is largely rural, heterogeneous and dynamic, since during the period covered (1988-2006), large estates where either converted into smaller properties, family-managed, through an intensive policy of agrarian reform (from the mid-eighties to the mid-nineties), or, more recently, by industrial-style cultures of forests to serve the paper industry. The results allowed comparing the different treatments and to verify the accuracy of detections. The main difficulties were the phenological cycles, the various phases of long-cycle artificial forests, and cloud-covered areas. It was not possible to clearly define the better or more accurate technique; this definition depends of specific objectives, of the scale and nature of the study region, and of the classes of change being analyzed, besides of the quality of available images.
