响应面光谱-时相分析用于检测巴西亚马逊地区的森林砍伐

M. P. Mello, F. Martins, L. Sato, R. Cantinho, D. A. Aguiar, B. Rudorff, Rafael Santos
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引用次数: 5

摘要

响应面光谱-时间分析(STARS)利用拟合响应面利用多光谱和多时间信息,用于描述巴西亚马逊地区的森林砍伐模式。STARS是在2003年8月至2004年8月采集的21张无云影像(8天构图)的MODIS数据集上进行的。由STARS得到的多系数图像(MCI)被用作三种分类器的输入属性:基于实例的k -最近邻(IBK)、决策树(DT)和神经网络(NN)。IBK分类器在检测森林砍伐和指示森林砍伐时期(年初或年末)方面的准确率最高(K=0.93)。结果表明,STARS有望描述随时间的光谱变化模式,从而检测巴西亚马逊地区发生的森林砍伐过程。
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Spectral-Temporal Analysis by Response Surface applied to detect deforestation in the Brazilian Amazon
Spectral-Temporal Analysis by Response Surface (STARS), which exploits both multispectral and multitemporal information using fitted response surfaces, was used to describe deforestation patterns in the Brazilian Amazon. The STARS was conducted upon a MODIS dataset formed by 21 selected cloud free images (eight days composition) acquired from August 2003 to August 2004. The Multi-Coefficient Image (MCI) resulted from the STARS was used as input attributes for the three tested classifiers: Instance Based K-nearest neighbor (IBK), Decision Tree (DT) and Neural Network (NN). The IBK classifier presented the highest accuracy (K=0.93) in detecting deforestation also indicating the deforestation period (early or late in the year). The results showed that the STARS is promising to describe spectral change patterns over time, allowing detection of the deforestation process which occurs in the Brazilian Amazon.
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