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Assessment of the Forest Disturbances Rate Caused by Windthrow Using Remote Sensing Techniques

机译:利用遥感技术评估风灾引起的森林干扰率

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Change detection using multi-temporal satellite images data is an important domain with various applications in forestry and can allow an evaluation of areas extended to the same spatial temporal scale. The focus of the study is to assess the changes occurring after catastrophic wind events using Landsat time series data. Estimates of disturbance rates are derived using 8 sample sites selected across the Apuseni Mountains during 2000-2014 periods. Multi-temporal analysis on annual basis has detected the patterns of the changing forest ecosystem and the trends that are occurring and give more accurate results. The satellite images have been calibrated and the root mean square error has been made The satellite images preprocessing is made in order to transform the DN values into the surface reflectance. The approach requires images during the peak growing season. Local knowledge and available ancillary data about windthrow occurrence are required in order to fully understand the nature of these trends. The statistical algorithms are applied to characterize the magnitude of the disturbance. We found evidence of systematic change in the forest ecosystem of the Apuseni Mountains by analyzing multi-temporal surface data. The accuracy of forest disturbance detection diminishes with the decrease of the temporal resolution. Therefore, the approach described in this paper demonstrates that the Landsat time series data can be used operationally for assessing forest cover changes analysis after a windthrow occurrence across a large area.
机译:使用多时相卫星图像数据进行变化检测是林业中各种应用的重要领域,并且可以评估扩展到相同空间时标的区域。该研究的重点是使用Landsat时间序列数据评估灾难性风灾后发生的变化。使用2000-2014年期间在Apuseni山中选择的8个采样点得出干扰率的估计值。每年进行的多时相分析已发现了不断变化的森林生态系统的模式和正在发生的趋势,并给出了更准确的结果。已对卫星图像进行了校准,并进行了均方根误差。对卫星图像进行了预处理,以便将DN值转换为表面反射率。该方法需要在高峰生长季节拍摄图像。为了充分了解这些趋势的本质,需要有关风灾发生的本地知识和可用的辅助数据。应用统计算法来表征干扰的大小。通过分析多时相地表数据,我们发现了Apuseni山区森林生态系统发生系统变化的证据。森林干扰检测的准确性随着时间分辨率的降低而降低。因此,本文中描述的方法证明了Landsat时间序列数据可用于在大面积发生风灾后评估森林覆盖变化分析。

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