English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In order to investigate the capability of satellite images for Pistachio forests density mapping, IRS-P6-LISS IV data were analyzed inan area of 500 ha in Iran. After geometric correction, suitable training areas were determined based on fieldwork. Suitable spectraltransformations 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, thehighest 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 wasnot desirable. Therefore, this approach is not appropriate for operational mapping of these valuable Pistachio forests

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

INVESTIGATING THE CAPABILITY OF IRS-P6-LISS IV SATELLITE IMAGE FOR PISTACHIO FORESTS DENSITY MAPPING (CASE STUDY: NORTHEAST OF IRAN)