Using Radar Imagery Data to Determine Mixed Forests’ Characteristics

Implementing inventory in remote and hard-to-reach forests is rather challenging. This study develops methods for identifying the qualitative and quantitative characteristics of mixed forests using Sentinel-1 imagery. The relationships between standing volume, forest density, age, and number of tree...

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Main Authors: Viktor Sidorenkov, Iuliia Achikolova, Daniil Astapov, Oleg Ryabtsev
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Environmental Sciences Proceedings
Subjects:
Online Access:https://www.mdpi.com/2673-4931/22/1/62
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author Viktor Sidorenkov
Iuliia Achikolova
Daniil Astapov
Oleg Ryabtsev
author_facet Viktor Sidorenkov
Iuliia Achikolova
Daniil Astapov
Oleg Ryabtsev
author_sort Viktor Sidorenkov
collection DOAJ
description Implementing inventory in remote and hard-to-reach forests is rather challenging. This study develops methods for identifying the qualitative and quantitative characteristics of mixed forests using Sentinel-1 imagery. The relationships between standing volume, forest density, age, and number of trees and radar survey indicators are revealed. The results are compared with forest inventory materials for a part of the study area. For most stands, there is a similarity in the standing volume and forest density definition. The study demonstrates that it is possible to identify quantitative and qualitative forest characteristics using radar survey data.
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spelling doaj.art-4bc99a4848ae4aadbf0d9d73dc0376502023-11-17T11:00:03ZengMDPI AGEnvironmental Sciences Proceedings2673-49312022-10-012216210.3390/IECF2022-13046Using Radar Imagery Data to Determine Mixed Forests’ CharacteristicsViktor Sidorenkov0Iuliia Achikolova1Daniil Astapov2Oleg Ryabtsev3Department of Silviculture and Forest Inventory, All-Russian Research Institute for Silviculture and Mechanization of Forestry, Pushkino 141202, RussiaDepartment of Silviculture and Forest Inventory, All-Russian Research Institute for Silviculture and Mechanization of Forestry, Pushkino 141202, RussiaDepartment of Silviculture and Forest Inventory, All-Russian Research Institute for Silviculture and Mechanization of Forestry, Pushkino 141202, RussiaDepartment of Silviculture and Forest Inventory, All-Russian Research Institute for Silviculture and Mechanization of Forestry, Pushkino 141202, RussiaImplementing inventory in remote and hard-to-reach forests is rather challenging. This study develops methods for identifying the qualitative and quantitative characteristics of mixed forests using Sentinel-1 imagery. The relationships between standing volume, forest density, age, and number of trees and radar survey indicators are revealed. The results are compared with forest inventory materials for a part of the study area. For most stands, there is a similarity in the standing volume and forest density definition. The study demonstrates that it is possible to identify quantitative and qualitative forest characteristics using radar survey data.https://www.mdpi.com/2673-4931/22/1/62radar imagerysatellite surveySentinel-1forest inventoryforest characteristicsstanding volume
spellingShingle Viktor Sidorenkov
Iuliia Achikolova
Daniil Astapov
Oleg Ryabtsev
Using Radar Imagery Data to Determine Mixed Forests’ Characteristics
Environmental Sciences Proceedings
radar imagery
satellite survey
Sentinel-1
forest inventory
forest characteristics
standing volume
title Using Radar Imagery Data to Determine Mixed Forests’ Characteristics
title_full Using Radar Imagery Data to Determine Mixed Forests’ Characteristics
title_fullStr Using Radar Imagery Data to Determine Mixed Forests’ Characteristics
title_full_unstemmed Using Radar Imagery Data to Determine Mixed Forests’ Characteristics
title_short Using Radar Imagery Data to Determine Mixed Forests’ Characteristics
title_sort using radar imagery data to determine mixed forests characteristics
topic radar imagery
satellite survey
Sentinel-1
forest inventory
forest characteristics
standing volume
url https://www.mdpi.com/2673-4931/22/1/62
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