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Spatial mapping of vegetation based on out-of-box vegetation indices

机译:基于盒外植被指数的植被空间映射

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The infrastructures of power grid can be easily damaged by fire disasters. Monitoring the spatial variations in the vegetation fraction is significant to predicate the probability of a fire disaster. While each vegetation indices(VI) computing method tends to suit some problem better than others, and typically have different parameters and configurations to be adjusted before achieving optimal performance on a dataset, we focus on conjunction with many types of traditional VIs' computing methods to improve their performance. Experimental results show that the accuracy of vegetation fraction estimation based on our method is higher than by using any single vegetation indices.
机译:电网的基础设施可以被消防灾害易于损坏。 监测植被分数的空间变化是显着的,以谓火灾灾害的概率。 虽然每个植被指数(VI)计算方法往往会比其他植被指数更好地适应一些问题,并且通常在在数据集上实现最佳性能之前进行不同的参数和配置,我们专注于许多类型的传统VIS计算方法。 提高他们的表现。 实验结果表明,基于我们方法的植被分数估计的准确性高于使用任何单一植被指数。

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