The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach

The optimal computational capability for analyzing multispectral aerial images e.g. for fine-scale tree species mapping is often considerably constrained by their enormous data volume. This may be mainly reflected in a reduction in the speed of data processing as well as in their archiving. This res...

Full description

Bibliographic Details
Main Authors: Omid Refieyan, Ali Asghar Darvishsefat
Format: Article
Language:fas
Published: Research Institute of Forests and Rangelands of Iran 2014-03-01
Series:تحقیقات جنگل و صنوبر ایران
Subjects:
Online Access:http://ijfpr.areeo.ac.ir/article_9062_4fd2d25f430af3f9ced7bb217171cda3.pdf
id doaj-fc067c837c0b42b8a9e2b65fea6cd52c
record_format Article
spelling doaj-fc067c837c0b42b8a9e2b65fea6cd52c2020-11-25T00:41:11ZfasResearch Institute of Forests and Rangelands of Iranتحقیقات جنگل و صنوبر ایران1735-08832383-11462014-03-0122112113210.22092/ijfpr.2013.90629062The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approachOmid Refieyan0Ali Asghar Darvishsefat1Assistant Professor, Department of Environmental Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran.Professor, Department of Forestry and Forest Economics, University of Tehran, Karaj, Iran.The optimal computational capability for analyzing multispectral aerial images e.g. for fine-scale tree species mapping is often considerably constrained by their enormous data volume. This may be mainly reflected in a reduction in the speed of data processing as well as in their archiving. This research was conducted to explore the effect of alterations in spatial and radiometric resolutions in the quality of object-based tree species classification by UltraCamD aerial images. The study was conducted in three different study sites. Segmentation was firstly implemented on the original images featuring spatial and radiometric resolution of 7 cm and 8-bit, respectively. The optimum segmentation result was then classified. Following this, rescaling in spatial (to 14, 21, 28, 35 and 42 cm pixel size) and radiometric (16-bit to 8-bit) resolutions were conducted, which was followed by classification of the resulted images using the similar segmentation, input bands, features and training and validation data. Based on the conducted accuracy assessment of the resulted classified images, the accuracy was shown to reduce along with a decrease in the radiometric resolution for all of the three areas. However, the trend was shown to be non-uniform when reducing the spatial resolution of the input data. It is concluded that a downscaling of the pixel size down to 4 times coarser than the original pixel size does not notably affect the classification of even-aged or homogeneous forests, while it should be merely conducted with caution in case of natural stands encompassing undisturbed, heterogeneous and diverse groups of species.http://ijfpr.areeo.ac.ir/article_9062_4fd2d25f430af3f9ced7bb217171cda3.pdfUltraCamDimage segmentationobject-based classificationspatial and radiometric resolution
collection DOAJ
language fas
format Article
sources DOAJ
author Omid Refieyan
Ali Asghar Darvishsefat
spellingShingle Omid Refieyan
Ali Asghar Darvishsefat
The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
تحقیقات جنگل و صنوبر ایران
UltraCamD
image segmentation
object-based classification
spatial and radiometric resolution
author_facet Omid Refieyan
Ali Asghar Darvishsefat
author_sort Omid Refieyan
title The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
title_short The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
title_full The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
title_fullStr The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
title_full_unstemmed The effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
title_sort effect of spatial and radiometric resolutions of aerial images for tree species classification by object-based approach
publisher Research Institute of Forests and Rangelands of Iran
series تحقیقات جنگل و صنوبر ایران
issn 1735-0883
2383-1146
publishDate 2014-03-01
description The optimal computational capability for analyzing multispectral aerial images e.g. for fine-scale tree species mapping is often considerably constrained by their enormous data volume. This may be mainly reflected in a reduction in the speed of data processing as well as in their archiving. This research was conducted to explore the effect of alterations in spatial and radiometric resolutions in the quality of object-based tree species classification by UltraCamD aerial images. The study was conducted in three different study sites. Segmentation was firstly implemented on the original images featuring spatial and radiometric resolution of 7 cm and 8-bit, respectively. The optimum segmentation result was then classified. Following this, rescaling in spatial (to 14, 21, 28, 35 and 42 cm pixel size) and radiometric (16-bit to 8-bit) resolutions were conducted, which was followed by classification of the resulted images using the similar segmentation, input bands, features and training and validation data. Based on the conducted accuracy assessment of the resulted classified images, the accuracy was shown to reduce along with a decrease in the radiometric resolution for all of the three areas. However, the trend was shown to be non-uniform when reducing the spatial resolution of the input data. It is concluded that a downscaling of the pixel size down to 4 times coarser than the original pixel size does not notably affect the classification of even-aged or homogeneous forests, while it should be merely conducted with caution in case of natural stands encompassing undisturbed, heterogeneous and diverse groups of species.
topic UltraCamD
image segmentation
object-based classification
spatial and radiometric resolution
url http://ijfpr.areeo.ac.ir/article_9062_4fd2d25f430af3f9ced7bb217171cda3.pdf
work_keys_str_mv AT omidrefieyan theeffectofspatialandradiometricresolutionsofaerialimagesfortreespeciesclassificationbyobjectbasedapproach
AT aliasghardarvishsefat theeffectofspatialandradiometricresolutionsofaerialimagesfortreespeciesclassificationbyobjectbasedapproach
AT omidrefieyan effectofspatialandradiometricresolutionsofaerialimagesfortreespeciesclassificationbyobjectbasedapproach
AT aliasghardarvishsefat effectofspatialandradiometricresolutionsofaerialimagesfortreespeciesclassificationbyobjectbasedapproach
_version_ 1725286821820104704