جستجوی مقالات مرتبط با کلیدواژه « لندست 8 » در نشریات گروه « جنگلداری »

The goal of this study is to see how well the forest canopy density (FCD) model and the GLAMA mobile ‎app estimate the canopy cover density of Zagros forests in Sardasht province. Landsat 9 Operational Land ‎Imager-2 (OLI-2) in 2022 was employed for this purpose. Four indices were created to run the model: 1- Advanced ‎Vegetation Index, 2- Bare Soil Index, 3- Shadow Index, and 4- Thermal Index. The Scaled Shadow Index and Vegetation Density index were then computed by integrating and synthesizing indices one and two, as well as indices three and four, and the FCD model map was created by combining these two indices. The created model was validated using GLAMA mobile app and ‎hemispherical photographs. For this purpose, 100 square sample plots in Sardasht city with varying canopy ‎cover were chosen, and photographs of the canopy cover were taken at five positions on each sample ‎plot. The overall accuracy of the FCD model generated for Sardasht Province was 76%, with a Kappa ‎coefficient of 0.697. Furthermore, the correlation results demonstrate a strong (R2‎ = 0.985) and significant ‎‎(p-value = <0.0001) correlation between the average canopy cover index values estimated by ‎hemispherical photography using GLAMA software and the values acquired by the FCD model. According ‎to the findings of this study, the FCD model developed using Landsat 9 satellite data and the GLAMA ‎mobile app performs very well in estimating forest land canopy density in Zagros forests.

Hyrcanian forests play an important role in absorbing carbon dioxide and reducing the severity of climate change and global warming. The accurate estimation of actual evapotranspiration can help to plan for conservation and management of these forests and their water resources. Direct measurement methods for evapotranspiration have limitations, one of the most important of them is the pointed measurements. Methods for distance measuring have been developed to address these constraints. The purpose of this study was to prepare and estimate actual instantaneous () and daily () evapotranspiration maps from Landsat 8 satellite imagery and SEBAL model in Hyrcanian forests. For this purpose, Landsat 8 satellite images were prepared in two different dates, i.e. 2014/7/26 and 2016/5/28 in 200 thousand hectares of Hyrcanian forests in the cities of Pol-Sefid and Kiasar, and after processing and calculations, latent heat flux was estimated from images and from that basis,  and  maps were prepared. To evaluate these maps,  and land values were calculated using weather data of Pol-Sefid and Kiasar stations and the FAO Penman Monteith method. The estimated  and  means at the Pol-Sefid station were 0.53 and 5.39 and at Kiasar station, 0.48 and 4.98 respectively. The calculated mean of these two parameters, respectively, were 0.60 and 6.16, at the Pol-sefid station and 0.55 and 5.82, at the Kiasar station. The results showed that the percentage of estimated relative differences for  and is 0.068 and 0.809 respectively, and mean percentage of estimated relative differences for  and is 11.99% and 13.56%, respectively, which in total shows the high ability of the used approach for evapotranspiration maps.

Classifying age classes in a large area using remotely sensed data has considerable significance for forest sustainable management. In this research, Landsat ETM+ data from Loveh forest, dating July 2002, were analyzed to investigate the potential of this sensor for age class mapping. We applied a systematic cluster sampling method to collect field data. We used 99 plots so that contained 32 plot. In stands with 25-45 years, 33 plots in stand with 5-25 years and 34 plots in stands with >45 years. The quality of the image was first evaluated for radiometric noises. Separability of three age classes 5-25, 25-45 and >45 years, using a supervised classification and four algorithm of maximum likelihood, minimum distance, parallel piped and linear discriminate analysis (Fisher). The results showed that maximum likelihood in three and two age classes with overall accuracy and kappa coefficient were (79% and 94%) and (0.68 and 0.86), respectively. Signature separability, producer and user accuracies showed the highest spectral similarity between 5-25 and >45 age classes. By merging the two classes, the overall accuracy and kappa coefficient became equal to 94% and 0.86, respectively. These results demonstrate that the reflectance values recorded by ETM+ sensor are related to forest stands. This information could also be used to estimate forest biomass and carbon content, identify locations within the stands that might require treatment and plan other management activities.