基于陆地卫星图像的彼尔姆地区植被覆盖制图

A. Shikhov, A. Semakina
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引用次数: 0

摘要

本文讨论了基于陆地卫星的彼尔姆地区植被覆盖制图方法和结果。最初的陆地卫星图像是在2016-2020年获得的。地图构建技术是基于卫星图像的监督分类和后续的后处理。这项技术涉及使用一些其他来源,特别是基于全球陆地卫星的森林扰动、水面和可耕地以及在废弃农业土地上重新造林地区的制图结果。因此,一个空间分辨率为30米(对应于1:10万的比例)的地图已经创建。地图图例包括19个专题类,其中11个包含森林植被信息。利用基于modis的俄罗斯植被覆盖地图和彼尔姆地区两个森林的森林清查数据,对获得的数据进行了准确性评估。分类精度最高的是典型的暗针叶林和松林(根据俄罗斯植被覆盖图,分类精度约为70%,根据森林清查数据,分类精度可达75%)。落叶林的识别精度最低,因为根据分类结果,它们部分被分类为混交林(以落叶物种为主)。绘制的植被覆盖图的实际用途可能包括估计单个植被类别(特别是完整森林景观)的长期变化,或根据森林的物种组成和年龄结构进行各种计算。彼尔姆地区植被覆盖的汇编图可在https://figshare.com/s/98d29e83d1f2039b2528上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MAPPING OF THE VEGETATION COVER OF THE PERM REGION BASED ON LANDSAT SATELLITE IMAGES
The paper deals with the methodology and results of Landsat-based vegetation cover mapping for the Perm region. Initial Landsat images were obtained in 2016–2020. The map building technique is based on the supervised classification of satellite images and subsequent post-processing. This technique involves the use of a number of additional sources, in particular, the results of global-Landsat-based mapping of forest disturbances, water surface, and arable lands, as well as reforestation areas on abandoned agricultural lands. As a result, a map with a spatial resolution of 30 m (which corresponds to a scale of 1:100,000) has been created. The map legend includes 19 thematic classes, 11 of them contain information on forest vegetation. The accuracy assessment of the obtained data was carried out with the use of a MODIS-based map of the vegetation cover of Russia and also forest inventory data on two forestries of the Perm region. The highest classification accuracy is typical for dark-coniferous and pine forests (it is about 70% according to the map of the vegetation cover of Russia, and up to 75% according to the forest inventory data). Deciduous forests are recognized with the lowest accuracy since, according to the classification results, they were partly categorized as mixed forests (with a predominance of deciduous species). The practical use of the created map of the vegetation cover may include estimation of long-term changes for individual vegetation classes (in particular, for intact forest landscapes), or various calculations based on the species composition and age structure of the forests. The compiled map of the vegetation cover of the Perm region is available at https://figshare.com/s/98d29e83d1f2039b2528.
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