期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII-B8
页码：1027-1030
出版社：Copernicus Publications
摘要：The main task is to apply in the Araucaria angustifolia (Brazilian pine) biome, the multi-temporal change detection algorithm "RCNA multi-spectral", using TM/Landsat-7 and CCD/CBERS-2 images. The study area is located in Central-South Paraná State, characterized by remnants of Mixed Ombrophilous Forest formations and by a traditional agricultural and cattle raising activities. The approach of change detection is based on the multivariate analysis (two spectral bands), with data from two sensor systems TM/Landsat image (8 th Aug., 1999) and CCD/CBERS-2 (8 th Aug., 2006). The multi-spectral RCNA is based in angular parameters, those angles are calculated in function of the axis formed by the straight line of regression of those points labeled in the field survey as no-change.The image for detection was transformed from a continuous image (floating-point) to thematic, through a slicing and labeling process. Hence it is possible to discriminate five thematic classes: two related to degradation, two referring to regeneration and one of no-change. The change detection map shows: in the timeframe studied 10.6 % of all area under study presents degradation patterns, derived from the clearcut activity, followed by changes of land use, with the complete removal the Mixed Ombrophilous Forest. In conclusion, we found out that the application of both multi-sensor and multi-spectral RCNA technique in Brazilian Pine landscape is robust and that the complex radiometric correction is not necessary. This simplifies the operational use of RCNA technique, demonstrating that the results can be adapted, considering the complexity of the area under study
