INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN)
In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI a...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2012-07-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/409/2012/isprsarchives-XXXIX-B8-409-2012.pdf |
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| author | F. Hoseini A. A. Darvishsefat N. Zargham |
| author_facet | F. Hoseini A. A. Darvishsefat N. Zargham |
| author_sort | F. Hoseini |
| collection | DOAJ |
| description | In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in
an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral
transformations like NDVI, PVI and PCA were performed. A ground truth map included of 34 plots (each plot 1 ha) were prepared.
Hard and soft supervised classifications were performed with 5 density classes (0–5%, 5–10%, 10–15%, 15–20% and > 20%).
Because of low separability of classes, some classes were merged and classifications were repeated with 3 classes. Finally, the
highest overall accuracy and kappa coefficient of 70% and 0.44, respectively, were obtained with three classes (0–5%, 5–20%, and >
20%) by fuzzy classifier. Considering the low kappa value obtained, it could be concluded that the result of the classification was
not desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests. |
| first_indexed | 2024-12-12T10:59:36Z |
| format | Article |
| id | doaj.art-79c5d0f78b69469da9c2ebd411d77e98 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-12T10:59:36Z |
| publishDate | 2012-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-79c5d0f78b69469da9c2ebd411d77e982022-12-22T00:26:35ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342012-07-01XXXIX-B840941110.5194/isprsarchives-XXXIX-B8-409-2012INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN)F. Hoseini0A. A. Darvishsefat1N. Zargham2MSc Graduated, Faculty of Natural Resources, University of Tehran, IranProf., Faculty of Natural Resources, University of Tehran, IranAssociate Prof., Faculty of Natural Resources, University of Tehran, IranIn order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed in an area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectral transformations like NDVI, PVI and PCA were performed. A ground truth map included of 34 plots (each plot 1 ha) were prepared. Hard and soft supervised classifications were performed with 5 density classes (0–5%, 5–10%, 10–15%, 15–20% and > 20%). Because of low separability of classes, some classes were merged and classifications were repeated with 3 classes. Finally, the highest overall accuracy and kappa coefficient of 70% and 0.44, respectively, were obtained with three classes (0–5%, 5–20%, and > 20%) by fuzzy classifier. Considering the low kappa value obtained, it could be concluded that the result of the classification was not desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/409/2012/isprsarchives-XXXIX-B8-409-2012.pdf |
| spellingShingle | F. Hoseini A. A. Darvishsefat N. Zargham INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) |
| title_full | INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) |
| title_fullStr | INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) |
| title_full_unstemmed | INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) |
| title_short | INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN) |
| title_sort | investigating the capability of irs p6 liss iv satellite image for pistachio forests density mapping case study northeast of iran |
| url | http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXIX-B8/409/2012/isprsarchives-XXXIX-B8-409-2012.pdf |
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