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Evaluation of compositing algorithms over the Brazilian Amazon using SPOT-4 VEGETATION data

机译:使用SPOT-4 VEGETATION数据评估巴西亚马逊上的合成算法

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摘要

The main objective of this study is to evaluate several algorithms to produce monthly composite images of the VEGETATION sensor onboard SPOT-4 over the Brazilian Amazon. The ability of the commonly used Normalized Difference Vegetation Index maximum value composite (MNDVI) and other compositing algorithms (i.e. one- and/or two-step algorithms), in terms of reducing the presence of clouds and cloud shadows and assessing spatial coherence of the composite images was tested. Among the one-step algorithms, the Soil Adjusted Vegetation Index maximum value composite (MSAVI), the minimum value composite of the red band (mRed) and the minimum value composite of the red band with an additional temporal persistence condition (mRedtp) were also analysed. The two-step algorithms included MNDVI or MSAVI followed by the minimum value of the viewing zenith angle, and mRed followed by MNDVI or by MSAVI. These eight compositing algorithms were used to produce monthly (August 2000) composite images of four regions (200 km x 200 km) representative of different landscape structures in the Brazilian Amazon. The results show that none of the compositing algorithms consistently performs best over all the regions. However, at this stage of the assessment, mRedMNDVI and mRedMSAVI are good candidates for SPOT-4 VGT monthly compositing over the Brazilian Amazon.
机译:这项研究的主要目的是评估几种算法,以产生巴西亚马逊上SPOT-4上的VEGETATION传感器的月度合成图像。常用归一化植被指数最大值组合(MNDVI)和其他合成算法(即一步和/或两步算法)在减少云和云影的存在以及评估云的空间连贯性方面的能力测试了合成图像。在单步算法中,还包括土壤调整植被指数最大值组合(MSAVI),红色带的最小值组合(mRed)和具有附加时间持久性条件(mRedtp)的红色带的最小值组合。分析。两步算法包括MNDVI或MSAVI,其后是视天顶角的最小值; mRed,其后是MNDVI或MSAVI。这八种合成算法用于生成代表巴西亚马逊地区不同景观结构的四个区域(200 km x 200 km)的月度(2000年8月)复合图像。结果表明,没有一种合成算法能够在所有区域上始终保持最佳性能。但是,在评估的这一阶段,mRedMNDVI和mRedMSAVI是在巴西亚马逊上进行SPOT-4 VGT月度合成的不错选择。

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