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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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Assessment and mapping of structural parameters in forest landscapes based on highly detailed three-dimensional remote sensing dataтезисы доклада Тезисы
- Авторы: Medvedev Andrey, Telnova Natalia, Kudikov Arseny, Alekseenko Natalia, Grozdov Yaroslav
- Сборник: Landscape Science and Landscape Ecology:Considering Responses to Global Challenges. 1 st International IALE-Russia online conference Moscow 14-18 September 2020 Book of Abstracts
- Тезисы
- Год издания: 2020
- Место издания: Lomonosov Moscow State University Moscow
- Первая страница: 15
- Последняя страница: 15
- Аннотация: The algorithms based on highly detailed remote sensing data for quantitative estimates of various structural and functional parameters of forest landscapes at the levels of sample plots as well as for individual trees are actively developing since the mid-2000s. Nowadays one of the most effective and cost-efficient solution for remote assessment, monitoring and prediction of basic forest stands variables is becoming the use of digital air (UAV) photogrammetry data allowing to reconstruct and accurately analyze the three-dimensional structure of forest stands from individual trees and sample plots to landscape level. We present elaborated approaches to the acquisition and preprocessing of UAV optical images and video frames data to produce highly detailed three-dimensional models characterizing both vertical and horizontal structure of forest stands in different landscapes conditions. The more crucial among these models are photogrammetric point clouds and resulted from their filtering and classification canopy height models (CHM). We have tested elaborated approaches and data processing flowcharts for the northern boreal sparse forests at the Kola Peninsula, for planted deciduous and pine stands in the low mountainous region of Central Caucasus as well as for abandoned agricultural lands with fast tree overgrowth in the landscape zone of broad-leaf forests, central part of European Russia. Several algorithms of automated segmentation and classification have been developed and validated to directly identify and map such basic characteristics at the levels of sample plots and whole stands as the distribution of trees heights and diameters, forest canopy closure, density of trees in stands. We also demonstrate how the obvious and known limitation of UAV photogrammetry revealed in dense forest stands – the significant lack of data under the upper tree canopy – can be overcome with combining multi-temporal UAV data (i.e. for leaf-on and leaf-off conditions) or simultaneous survey of lower canopies and ground at the same plots from the terrestrial laser scanner.
- Добавил в систему: Тельнова Наталья Олеговна