Mapping and Assessment of the Cenotic Diversity of the Forests of the Moscow Region

IF 1 4区 环境科学与生态学 Q4 ECOLOGY
T. V. Chernenkova, I. P. Kotlov, N. G. Belyaeva, Ye. G. Suslova, O. V. Morozova
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引用次数: 0

Abstract

The growing population density of large metropolitan areas means an increase in ecological and social importance of the forest cover’s biodiversity. The lack of up-to-date cartographic materials makes it difficult to assess the quality of the natural environment and to preserve valuable natural objects while taking into account the conditions of habitats and types of land use. The aim of this work was to identify and map the cenotic diversity of the forest cover of the Moscow region. To study the spatial structure of communities, remote data (Sentinel-2A, PALSAR radar images), digital relief models (DRM SRTM) in combination with ground survey data were used. To compensate for the scarce and uneven distribution of field data, the training sample alignment approach was used with the selection of the optimal modelling algorithm (“random forest”). Cartographic models have been developed for the modern phytocenotic diversity of the Moscow region’s forest cover, for thematic units of the formation (11 classes) and group of associations (31 classes) ranks, accompanied by a detailed legend. Statistical methods and the digital format of the cartographic materials determine the approach’s adaptability and the necessary updating of the materials. The proposed mapping technique and the performed assessment of the typological diversity of the forests can be used to create a spatial basis for monitoring the biodiversity of the forests in the Moscow region and the urban forests of Moscow.

Abstract Image

莫斯科地区森林物种多样性的绘图和评估
摘要 大城市人口密度的增加意味着森林植被生物多样性的生态和社会重要性的增加。由于缺乏最新的制图资料,很难对自然环境质量进行评估,也很难在考虑栖息地条件和土地利用类型的同时保护有价值的自然对象。这项工作的目的是确定和绘制莫斯科地区森林植被的岑岭多样性。为了研究群落的空间结构,使用了遥感数据(哨兵-2A、PALSAR 雷达图像)、数字地形模型(DRM SRTM)以及地面勘测数据。为了弥补实地数据稀缺和分布不均的问题,采用了训练样本排列法,并选择了最佳建模算法("随机森林")。为莫斯科地区森林植被的现代植物区系多样性、形成(11 个等级)和联合(31 个等级)等级的主题单位开发了制图模型,并附有详细图例。统计方法和制图资料的数字格式决定了该方法的适应性和必要的资料更新。建议的制图技术和对森林类型多样性的评估可用来为监测莫斯科地区和莫斯科城市森林的生物多样性奠定空间基础。
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来源期刊
Russian Journal of Ecology
Russian Journal of Ecology 环境科学-生态学
CiteScore
1.50
自引率
18.20%
发文量
40
审稿时长
6 months
期刊介绍: The Russian Journal of Ecology publishes completed original studies in all branches of theoretical and experimental ecology, reviews, articles on topics currently in debate, and information on new methods of research.
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