IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES

Due to many problems such as diseases and pests, low fertility, and dehydration, trees need immediate actions to be taken in time of need. Since they are an important source of fruit, food, and nutrients consumed by humans, keeping track of the trees in orchards is a crucial issue in recent years. T...

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Main Author: H. Haddadi Amlashi
Format: Article
Language:English
Published: Copernicus Publications 2023-01-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-4-W1-2022/249/2023/isprs-annals-X-4-W1-2022-249-2023.pdf
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author H. Haddadi Amlashi
author_facet H. Haddadi Amlashi
author_sort H. Haddadi Amlashi
collection DOAJ
description Due to many problems such as diseases and pests, low fertility, and dehydration, trees need immediate actions to be taken in time of need. Since they are an important source of fruit, food, and nutrients consumed by humans, keeping track of the trees in orchards is a crucial issue in recent years. Today, drones equipped with multispectral cameras are used in precision agriculture, especially for monitoring and controlling trees. For this cause, two citrus orchards in Iran with an area of 9.2 and 2.67 hectares and a resolution of 3.6 and 0.68 cm were selected for the study area. In this study, First, tree extraction was conducted using four algorithms namely Local maxima, Image binarization, valley following, and watershed segmentation, and a proposed method that is based on the improvement of the watershed algorithm. This method achieved an overall accuracy of 87% and 81% in the two study regions which was higher than common methods. Secondly, the effect of the number of spectral bands on the accuracy of tree extraction was investigated. As a result, by adding of Red-Edge and NIR bands, the accuracy increased by about 5% and 7%. Therefore, experts suggested using NIR and Red-Edge bands besides RGB bands.
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spelling doaj.art-04480475e49e42faafa650fe1f83fabb2023-01-14T11:09:09ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502023-01-01X-4-W1-202224925410.5194/isprs-annals-X-4-W1-2022-249-2023IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGESH. Haddadi Amlashi0University of Tehran, Faculty of Geospatial Engineering, Tehran, IranDue to many problems such as diseases and pests, low fertility, and dehydration, trees need immediate actions to be taken in time of need. Since they are an important source of fruit, food, and nutrients consumed by humans, keeping track of the trees in orchards is a crucial issue in recent years. Today, drones equipped with multispectral cameras are used in precision agriculture, especially for monitoring and controlling trees. For this cause, two citrus orchards in Iran with an area of 9.2 and 2.67 hectares and a resolution of 3.6 and 0.68 cm were selected for the study area. In this study, First, tree extraction was conducted using four algorithms namely Local maxima, Image binarization, valley following, and watershed segmentation, and a proposed method that is based on the improvement of the watershed algorithm. This method achieved an overall accuracy of 87% and 81% in the two study regions which was higher than common methods. Secondly, the effect of the number of spectral bands on the accuracy of tree extraction was investigated. As a result, by adding of Red-Edge and NIR bands, the accuracy increased by about 5% and 7%. Therefore, experts suggested using NIR and Red-Edge bands besides RGB bands.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-4-W1-2022/249/2023/isprs-annals-X-4-W1-2022-249-2023.pdf
spellingShingle H. Haddadi Amlashi
IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES
title_full IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES
title_fullStr IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES
title_full_unstemmed IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES
title_short IMPROVED WATERSHED SEGMENTATION ALGORITHM FOR TREE CROWNS EXTRACTION FROM MULTI-SPECTRAL UAV-BASED AERIAL IMAGES
title_sort improved watershed segmentation algorithm for tree crowns extraction from multi spectral uav based aerial images
url https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/X-4-W1-2022/249/2023/isprs-annals-X-4-W1-2022-249-2023.pdf
work_keys_str_mv AT hhaddadiamlashi improvedwatershedsegmentationalgorithmfortreecrownsextractionfrommultispectraluavbasedaerialimages