Predicting Some Stand Attributes of Scots Pine Stands Using Landsat 8 OLI Satellite Image
Yazarlar (3)
Arş. Gör. Döndü BULUR Kastamonu Üniversitesi, Türkiye
Doç. Dr. Oytun Emre Sakıcı Kastamonu Üniversitesi, Türkiye
Prof. Dr. Alkan Günlü Çankırı Karatekin Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (Diğer hakemli uluslarası dergilerde yayınlanan tam makale) | ||
| Dergi Adı | Mindanao Jornal Section 1: AJOST | ||
| Dergi ISSN | 2651-7884 | ||
| Dergi Tarandığı Indeksler | Academia | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2022 |
| Cilt / Sayı / Sayfa | 3 / 1 / 93–116 | DOI | – |
| UAK Araştırma Alanları |
Orman Hasılatı ve Amenajmanı
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| Özet |
| Monitoring forest resources using satellite images has been employed for different forest inventory purposes. This study used remote sensing data to derive regression models for estimating some stand attributes, including mean diameter, stand basal area, stand volume, number of trees, and stand density of pure Scots pine (Pinus sylvestris L.) stands. Field measurements were conducted within the 135 sample plots to obtain the above-mentioned stand attributes data. Reflectance values, vegetation indices, and texture values of each sample plot were generated from Landsat 8 OLI satellite images. The data obtained from sample plots were randomly selected and divided into two groups, consisting of 101 sample plots (75% of total data) for derivation of models, and 34 sample plots (25% of total data) for validation of the derived models. The prediction strengths of seven independent variable groups (i.e … |
| Anahtar Kelimeler |
