Estimating forest canopy cover using Landsat7 ETM+ data
The remotely sensed data is one of the most rapid methods for providing thematic maps in natural resources, especially forest. By combining ETM+ data and ground observation data, we can have access to thematic maps of forest such as canopy cover map, that it can be used in forest ecological studies...
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| Format: | Article |
| Language: | fas |
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Research Institute of Forests and Rangelands of Iran
2005-09-01
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| Series: | تحقیقات جنگل و صنوبر ایران |
| Subjects: | |
| Online Access: | http://ijfpr.areeo.ac.ir/article_108501_06b4fe394974ee5dc5d88858d2670b3b.pdf |
| _version_ | 1818932627246153728 |
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| author | Khosro Mirakhorlou Manoochehr Amani |
| author_facet | Khosro Mirakhorlou Manoochehr Amani |
| author_sort | Khosro Mirakhorlou |
| collection | DOAJ |
| description | The remotely sensed data is one of the most rapid methods for providing thematic maps in natural resources, especially forest. By combining ETM+ data and ground observation data, we can have access to thematic maps of forest such as canopy cover map, that it can be used in forest ecological studies and forest management and improvement. The research was conducted to evaluate and investigate the possibility of using Landsat7 ETM+ data for developing forest canopy cover density map at four classes in four sites of Caspian Forests of Iran. Based on OIF index and statistical analysis of the ETM+ data, Color composite 3, 4, 5 were selected for unsupervised and supervised classifications. Ground observation information was collected from 282 plots (150*150m), using unsupervised map as a primary map. Finally, combining the ETM+ data and the ground information, using supervised classification method, canopy cover map was achieved at four classes (5-30%, 31-50%, 51-80%, 81-100%). Evaluation of the canopy cover density percentage showed that the overall accuracy of the canopy cover percentage map developed by the Landsat7 ETM+ data and average accuracy, producer's and user's accuracy were: 85.43, 84.7 and 82.68 percent, respectively. |
| first_indexed | 2024-12-20T04:35:29Z |
| format | Article |
| id | doaj.art-37b6b82256414734b8cd79f00dfc7a2f |
| institution | Directory Open Access Journal |
| issn | 1735-0883 2383-1146 |
| language | fas |
| last_indexed | 2024-12-20T04:35:29Z |
| publishDate | 2005-09-01 |
| publisher | Research Institute of Forests and Rangelands of Iran |
| record_format | Article |
| series | تحقیقات جنگل و صنوبر ایران |
| spelling | doaj.art-37b6b82256414734b8cd79f00dfc7a2f2022-12-21T19:53:17ZfasResearch Institute of Forests and Rangelands of Iranتحقیقات جنگل و صنوبر ایران1735-08832383-11462005-09-01133342313108501Estimating forest canopy cover using Landsat7 ETM+ dataKhosro Mirakhorlou0Manoochehr Amani1Members of Scientific Board, Research Institute of Forests and RangelandsMembers of Scientific Board, Research Institute of Forests and RangelandsThe remotely sensed data is one of the most rapid methods for providing thematic maps in natural resources, especially forest. By combining ETM+ data and ground observation data, we can have access to thematic maps of forest such as canopy cover map, that it can be used in forest ecological studies and forest management and improvement. The research was conducted to evaluate and investigate the possibility of using Landsat7 ETM+ data for developing forest canopy cover density map at four classes in four sites of Caspian Forests of Iran. Based on OIF index and statistical analysis of the ETM+ data, Color composite 3, 4, 5 were selected for unsupervised and supervised classifications. Ground observation information was collected from 282 plots (150*150m), using unsupervised map as a primary map. Finally, combining the ETM+ data and the ground information, using supervised classification method, canopy cover map was achieved at four classes (5-30%, 31-50%, 51-80%, 81-100%). Evaluation of the canopy cover density percentage showed that the overall accuracy of the canopy cover percentage map developed by the Landsat7 ETM+ data and average accuracy, producer's and user's accuracy were: 85.43, 84.7 and 82.68 percent, respectively.http://ijfpr.areeo.ac.ir/article_108501_06b4fe394974ee5dc5d88858d2670b3b.pdfCanopy CoverClassificationsatellite dataTraining sampleAccuracy assessmentCaspian forests |
| spellingShingle | Khosro Mirakhorlou Manoochehr Amani Estimating forest canopy cover using Landsat7 ETM+ data تحقیقات جنگل و صنوبر ایران Canopy Cover Classification satellite data Training sample Accuracy assessment Caspian forests |
| title | Estimating forest canopy cover using Landsat7 ETM+ data |
| title_full | Estimating forest canopy cover using Landsat7 ETM+ data |
| title_fullStr | Estimating forest canopy cover using Landsat7 ETM+ data |
| title_full_unstemmed | Estimating forest canopy cover using Landsat7 ETM+ data |
| title_short | Estimating forest canopy cover using Landsat7 ETM+ data |
| title_sort | estimating forest canopy cover using landsat7 etm data |
| topic | Canopy Cover Classification satellite data Training sample Accuracy assessment Caspian forests |
| url | http://ijfpr.areeo.ac.ir/article_108501_06b4fe394974ee5dc5d88858d2670b3b.pdf |
| work_keys_str_mv | AT khosromirakhorlou estimatingforestcanopycoverusinglandsat7etmdata AT manoochehramani estimatingforestcanopycoverusinglandsat7etmdata |