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Change Detection in the Amazon Rainforest with Radiometric Rotation Technique RCEN Multi-spectral Case Study: Guarayos - Bolivia

机译:通过辐射旋转技术改变检测亚马逊雨林,RCEN多光谱案例研究:Guarayos - 玻利维亚

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A working group of three institutions was set up to develop this study: University of Applied Sciences Eberswalde (Germany), National Institute for Space Research (INPE, Brazil) and National Institute for Amazon Research (INPA, Brazil). The main task is to apply in the Guarayos region (Bolivia), the multi-temporal change detection algorithm "RCEN multi-spectral". The study area is located in Guarayos-Bolivia, characterized by two main high forests landscapes, "The Amazon Region" and "The Brazilian Paranaense Region"; the approach of the change detection is taken under multivariate analysis (three spectral bands), with data coming from two kinds of sensor ETM+/Landsat-7 and CCD/CBERS-2. The image detection was transformed from continuous image (floating-point) to thematic, through 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 11% of all area under study presents deforestation patterns, on the other hand the regeneration class is not significant. In conclusion the methodology has good performance and it is evolving in landscapes with high humidity complications.
机译:三个机构工作组旨在开发这项研究:应用科学大学Eberswalde(德国),国家空间研究所(Inpe,巴西)和国家亚马逊研究所(Inpa,Brazil)。主要任务是应用于瓜盖区(玻利维亚),多时间变化检测算法“rcen多光谱”。该研究区位于Guarayos-Bolivia,其特征在于两个主要的高森林景观,“亚马逊地区”和“巴西巴拉瓦纳州地区”;在多变量分析(三个光谱带)下采取变化检测的方法,其中数据来自两种传感器ETM + / Landsat-7和CCD / CBERS-2。通过切片和标记过程从连续图像(浮点)转换图像检测。因此,可以区分五个主题类别:两个与劣化相关的主题,两种有关的有关,其中包括再生和无变化之一。变更检测图显示:在研究中,在研究中的11%的研究中,在研究中的所有区域都具有遮瑕模式,另一方面,再生类不显着。总之,该方法具有良好的性能,并且在具有高湿度并发症的景观中发展。

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