ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION

This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individua...

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Main Authors: SHUKHRAT SHOKIROV, GÉZA KIRÁLY
Format: Article
Language:English
Published: Debrecen University Press. 2016-10-01
Series:Acta Geographica Debrecina. Landscape & Environment Series
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author SHUKHRAT SHOKIROV
GÉZA KIRÁLY
author_facet SHUKHRAT SHOKIROV
GÉZA KIRÁLY
author_sort SHUKHRAT SHOKIROV
collection DOAJ
description This study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.
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institution DOAJ
issn 1789-4921
1789-7556
language English
publishDate 2016-10-01
publisher Debrecen University Press.
record_format Article
series Acta Geographica Debrecina. Landscape & Environment Series
spelling doaj-art-73025afa4b1046978c4eb62f41fc4af72025-08-20T03:19:03ZengDebrecen University Press.Acta Geographica Debrecina. Landscape & Environment Series1789-49211789-75562016-10-0110289100DOI:10.21120/LE/10/2/4ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTIONSHUKHRAT SHOKIROV0 GÉZA KIRÁLYshukhrat811@gmail.comThis study evaluated the use of 40 cm spatial resolution aerial images for individual tree crown delineation, forest type classification, health estimation and clear-cut area detection in Fenyőfő forest reserves in 2012 and 2015 years. Region growing algorithm was used for segmentation of individual tree crowns. Forest type (coniferous/deciduous trees) were distinguished based on the orthomosaic images and segments. Research also investigated the height of individual trees, clear-cut areas and cut crowns between 2012 and 2015 years using Canopy Height Models. Results of the research were examined based on the field measurement data. According to our results, we achieved 75.2% accuracy in individual tree crown delineation. Heights of tree crowns have been calculated with 88.5% accuracy. This study had promising result in clear cut area and individual cut crown detection. Overall accuracy of classification was 77.2%, analysis showed that coniferous tree type classification was very accurate, but deciduous tree classification had a lot of omission errors. Based on the results and analysis, general information about forest health conditions has been presented. Finally, strengths and limitations of the research were discussed and recommendations were given for further research.Aerial imageryCanopy Height Model (CHM)Object Based Image Analysis (OBIA
spellingShingle SHUKHRAT SHOKIROV
GÉZA KIRÁLY
ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION
Acta Geographica Debrecina. Landscape & Environment Series
Aerial imagery
Canopy Height Model (CHM)
Object Based Image Analysis (OBIA
title ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION
title_full ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION
title_fullStr ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION
title_full_unstemmed ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION
title_short ANALYSIS OF MULTITEMPORAL AERIAL IMAGES FOR FENYŐFŐ FOREST CHANGE DETECTION
title_sort analysis of multitemporal aerial images for fenyofo forest change detection
topic Aerial imagery
Canopy Height Model (CHM)
Object Based Image Analysis (OBIA
work_keys_str_mv AT shukhratshokirov analysisofmultitemporalaerialimagesforfenyofoforestchangedetection
AT gezakiraly analysisofmultitemporalaerialimagesforfenyofoforestchangedetection