Yazar "Bolat, Ferhat" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    Comparing parameter recovery methods for diameter distribution models of oriental spruce (picea orientalis (L.) link.) and scotch pine (pinus sylvestris L.) mixed stands located trabzon and giresun forest regional directorate
    (Artvin Çoruh Üniversitesi, 2013) Ercanlı, İlker; Bolat, Ferhat
    Diameter distributions are important stand characteristic for describing forest stand structure and stand dynamic. The knowledge about diameter distribution has been required to forecast the range of products, which might be expected from a stand in forest management. There are several methods for predicting the diameter distribution of a stand, varying from methods which utilize theoretical distribution functions to non-parametric methods. In these methods, the studies characterizing diameter distributions with probability density functions (pdf) have provided the most successful and predictive results to model diameter distributions. In fitting the probability density functions, percentiles and moments values of diameter distributions have been used successfully to characterize distributions. The parameter recovery methods for calculating the parameters of probability density functions include the different percentiles values for distribution, e.g. 67, 31, 25, 50 or 95% values of the diameter distribution. In this study, 161 sample plots were used to compare some parameter recovery methods using different percentiles and moment values for distribution for fitting 3-paramaters Weibull in Oriental spruce and Scotch pine mixed stands located in Trabzon and Giresun Forest Regional Directorate. The parameter recovery methods were compared by based on Rennolds et al. (1988)’s error index values calculated by difference between observed and predicted diameter distributions. The comparative results have shown that the parameter recovery method using 25%, 50% and 63% values with 2.341615 mean rank has the more successful results for describe different diameter distributions than other recovery methods.
  • Küçük Resim
    Öğe
    Modeling aboveground carbon in flooded forests using synthetic aperture radar data: a case study from a natural reserve in Turkish Thrace
    (iForest, 2024) Vatandaşlar, Can; Bolat, Ferhat; Abdikan, Saygın; Pamukçu Albers, Pınar; Satıral, Caner
    Flooded forests are rare and highly dynamic ecosystems, yet they can store a significant amount of carbon because of their ability to produce biomass rapidly. Estimation and mapping of the carbon that is stored in flooded forests are challenging tasks through the use of optical remote sensing because these ecosystems are often located in moist regions where clouds can interfere with data acquisition and image interpretation. This study models the aboveground carbon (AGC) stocks of a flooded forest in Turkish Thrace with synthetic aperture radar (SAR) data, which are less affected by weather and illumination conditions compared to optical imagery. Forest management plan data, including inventory records of 229 sample plots, a detailed forest cover map, and stand tables of the 2,119-ha Igneada Longoz Forest, were used to calculate AGC and to develop spatially explicit models based on ALOS/PALSAR-2 (Advanced Land Observing Satellite/Phased Array L-band Synthetic Aperture Radar) and Landsat-8 images. The results indicated that the horizontally transmitted and horizontally received (HH) and cross-polarization ratio (CPR) bands of ALOS/PALSAR were the most influential variables in the linear and nonlinear regression models. The models did not include any variables from either radaror optical-based vegetation indices. While the estimation accuracies of the two models were similar (root mean square percentage error approximate to 26%), the linear model yielded negative estimations in several land cover classes (e.g., dune, forest opening, degraded forest). AGC stock was estimated and mapped using the nonlinear model in these cases. The density map revealed that Igneada Longoz Forest stored 279,258.9 t AGC, with a mean and standard deviation of 124 +/- 115.4 t C ha-1. AGC density varied significantly depending on stand types and management units across the forest, and carbon hotspots accumulated in the northern and southern sites of the study area, primarily composed of ash and alder seed stands. The models and maps that this study developed are expected to help in the rapid and cost-effective assessment of AGC stored in flooded forest ecosystems across the temperate climate zone.