首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Using the Landsat record to detect forest-cover changes during and after the collapse of the Soviet Union in the temperate zone of European Russia
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Using the Landsat record to detect forest-cover changes during and after the collapse of the Soviet Union in the temperate zone of European Russia

机译:使用Landsat记录检测苏联在欧洲俄罗斯温带地区崩溃期间及之后的森林覆盖变化

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The political breakdown of the Soviet Union in 1991 provides a rare case of drastic changes in social and economic conditions, and as such a great opportunity to investigate the impacts of socioeconomic changes on the rates and patterns of forest harvest and regrowth. Our goal was to characterize forest-cover changes in the temperate zone of European Russia between 1985 and 2010 in 5-year increments using a stratified random sample of 12 Landsat footprints. We used Support Vector Machines and post-classification comparison to monitor forest area, disturbance and reforestation. Where image availability was sub-optimal, we tested whether winter images help to improve classification accuracy. Our approach yielded accurate mono-temporal maps (on average > 95% overall accuracy), and change maps (on average 93.5%). The additional use of winter imagery improved classification accuracy by about 2%. Our results suggest that Russia's temperate forests underwent substantial changes during the observed period. Overall, forested areas increased by 4.5%, but the changes in forested area varied over time: a decline in forest area between 1990 and 1995 (-1%) was followed by an increase in overall forest area in recent years (+1.4%, 2005-2010), possibly caused in part by forest regrowth on abandoned farmlands. Disturbances varied greatly among administrative regions, suggesting that differences in socioeconomic conditions strongly influence disturbance rates. While portions of Russia's temperate forests experienced high disturbance rates, overall forest area is expanding. Our use of a stratified random sample of Landsat footprints, and of summer and winter images, allowed us to characterize forest dynamics across a large region over a long time period, emphasizing the value of winter imagery in the free Landsat archives, especially for study areas where data availability is limited.
机译:1991年苏联的政治崩溃提供了罕见的社会和经济状况急剧变化的案例,因此,这是一个很好的机会来研究社会经济变化对森林采伐和再生的速度和方式的影响。我们的目标是使用12个Landsat足迹的分层随机样本,以1985年至2010年之间的5年增量描述欧洲俄罗斯温带地区的森林覆盖变化。我们使用支持向量机和分类后比较来监视森林面积,干扰和重新造林。在图像可用性次优的地方,我们测试了冬季图像是否有助于提高分类准确性。我们的方法产生了准确的单时态图(平均总准确度> 95%)和变更图(平均93.5%)。冬季图像的额外使用将分类准确性提高了约2%。我们的结果表明,在观察期内,俄罗斯的温带森林发生了重大变化。总体而言,森林面积增加了4.5%,但森林面积的变化随时间变化:1990年至1995年之间的森林面积减少(-1%),随后是近年来的总体森林面积增加(+ 1.4%, 2005-2010年),部分原因可能是废弃农田的森林再生。行政区域之间的干扰差异很大,这表明社会经济条件的差异会极大地影响干扰率。尽管俄罗斯温带森林的部分地区遭受了高干扰,但总体森林面积却在扩大。我们对Landsat足迹的分层随机样本以及夏季和冬季图像的使用,使我们能够在很长一段时间内表征大区域的森林动态,强调冬季图像在免费Landsat档案中的价值,尤其是对于研究区域数据可用性有限的地方。

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