Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis
Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate acro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2010-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2072-4292/2/12/2748/ |
| _version_ | 1819277953712783360 |
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| author | Jane Southworth Youliang Qiu Luke Rostant Sanchayeeta Adhikari Cerian Gibbes |
| author_facet | Jane Southworth Youliang Qiu Luke Rostant Sanchayeeta Adhikari Cerian Gibbes |
| author_sort | Jane Southworth |
| collection | DOAJ |
| description | Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC) for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure. |
| first_indexed | 2024-12-24T00:04:18Z |
| format | Article |
| id | doaj.art-10c8a69f193c4d44acfc321dbc2dfbfa |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-24T00:04:18Z |
| publishDate | 2010-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-10c8a69f193c4d44acfc321dbc2dfbfa2022-12-21T17:25:02ZengMDPI AGRemote Sensing2072-42922010-12-012122748277210.3390/rs2122748Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem AnalysisJane SouthworthYouliang QiuLuke RostantSanchayeeta AdhikariCerian GibbesSavanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC) for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.http://www.mdpi.com/2072-4292/2/12/2748/savannasvegetation structuretree canopiesobject basedIKONOS |
| spellingShingle | Jane Southworth Youliang Qiu Luke Rostant Sanchayeeta Adhikari Cerian Gibbes Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis Remote Sensing savannas vegetation structure tree canopies object based IKONOS |
| title | Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis |
| title_full | Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis |
| title_fullStr | Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis |
| title_full_unstemmed | Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis |
| title_short | Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis |
| title_sort | application of object based classification and high resolution satellite imagery for savanna ecosystem analysis |
| topic | savannas vegetation structure tree canopies object based IKONOS |
| url | http://www.mdpi.com/2072-4292/2/12/2748/ |
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