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  • 标题:INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN)
  • 本地全文:下载
  • 作者:F. Hoseini ; A. A. Darvishsefat ; N. Zargham
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2012
  • 卷号:XXXIX - B8
  • 页码:409-411,
  • DOI:10.5194/isprsarchives-XXXIX-B8-409-2012
  • 出版社:Copernicus Publications
  • 摘要: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
  • 关键词:IRS-P6-LISS IV; Ground Truth; Pistachio Forests; Forest Density; Iran
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