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ŠUMARSKI LIST 7-8/2015 str. 73     <-- 73 -->        PDF

method trained with field data for a remote forest in China area produced satisfactory results (R = 0.69, RMSE = 20.7 tons ha−1) (Tian et al., 2012).
The resulting equation and reflection of pixels on the entire satellite image are used to calculate the values of the amount of carbon stock of each pixel and these values were collected and carbon stock capacity of the total working area of was found. Thus, RapidEye satellite image calculated that the amount of carbon stored in the 9 917 ha study area that is mostly covered in Scotch pine and located in the 61 646 ha Camyazi Forest Directorate is  285 208 tons.
CONCLUSION
RASPRAVA
Forests are the largest carbon deposits and very important in this sense to the world. There is a linear relationship between the amount of woodland areas and the amount of carbon stored. Also in the context of the Kyoto Protocol, woodlands and the amount of carbon stored here is very important for the carbon exchanges in the coming years.
In the study, forestry plan inventory data and remote sensing techniques were utilized to determine the amount of carbon deposited in the stand within the boundaries of the Camyazi Forest Directorate. As a result of the calculations made, using the RapidEye imagery and a (Band 4)2 devised equation producing R2=0.71 depending upon the data from Erzurum Camyazi Forest Directorate, the amount of carbon stored within stand was found 285 208 tons. From this value, we can conclude that average carbon stock of the study area is 28.8 tons/ha.
Remote sensing techniques used in this study showed that these techniques can save time, budget and labor when calculating carbon stock capacity data (which is rather time and resource consuming to calculate) and accurate results may be achieved. Besides, the study showed that the Red-Edge band (Band 4) of RapidEye satellite image that is sensitive to biomass and chlorophyll can be used in studies related to carbon stock. When the study conducted by Myeong et al. (2006) and our study are compared, it became clear that both manifest accuracy rates close to one another.
Equations of biomass and carbon stock for each type of tree have not yet been completed. They have to complete as soon as possible and the carbon stock capacity needs to be identified more accurately. When calculating the capacity for this type of study, the financial side of the study has to be considered and combined methods with low costs have to be preferred.
ACKNOWLEDGMENTS
This study is funded by the Scientific Research Projects Committee of Kastamonu University with the project number KUBAP-01/2012-49.
REFERENCES
BIBLIOGRAFIJA
Asan, U., 1999: Climate change, carbon sings and the forest of Turkey. Proceedings of the International Conference on Tropical Forests and Climate Change: Status, Issues and Challenges, Laguana, Philippines, ISBN 971-579-021-6, pp.157–170.
Asan, U., 2006: Final Report for the LULUCF Forestry Group Concerning the Estimation of Net Annual Amount of Carbon Uptake or Release in the Forests of Turkey.
Brown, S., 2002: Measuring carbon in forests: current status and future challenges. Environmental Pollution, 116(3), pp. 363–372.
Bulut, A., 2012: Determining the carbon storage capacity of forests by using three different satellite images with remote sensing method (a case study of Alacadag forest management chiefdom). MsD. Thesis, Karadeniz Technical University, Graduate School of Natural and Applied Sciences, Trabzon, Turkey.
Chung, S. Y., Yim, J. S., Cho, H. K., Shin, M. Y., 2009: Comparison of forest biomass estimation methods by combining satellite data and field data. IUFRO Division 4 – Extending Forest Inventory and Monitoring Proceeding, Quebec City, Canada, May 19-22 2009.
Comez, A., 2012: Determination of carbon sequestration in scots pine (Pinussylvestris L.) stands on Sundiken Mountain-Eskisehir. General Directorate of Forestry, Research Institute for Forest Soils and Ecology Technical Bulletin, 2, pp. 123.
De Gier, I. K. S. A., Hussin, Y. A., 2012: Estimation Of Tropical Forest Biomass For Assessment Of Carbon Sequestration Using Regression Models And Remote Sensing In Berau. East Kalimantan, Indonesia, Department of Natural Resources, The International Institute for Geoinformation Science and Earth Observation (ITC), Hengelosstraat, 99, 7500.
Dube, T., Mutanga, O., 2015: Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa. ISPRS Journal of Photogrammetry and Remote Sensing, 101, 36–46.
Galeana-Pizaña, J. M., López-Caloca, A., López-Quiroz, P., Silván-Cárdenas, J. L., Couturier, S.,2014: Modeling the spatial distribution of above-ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach. International Journal of Applied Earth Observation and Geoinformation, 30, 179–189.
Goetz, S., Baccini, A., Laporte, N., Johns, T., Walker, W., Kellndorfer, J., Houghton, R.,Sun, M., 2009: Mapping and monitoring carbon stocks with satellite observations: a comparison review. Carbon Balance and Management 4 (2), 1–7.
Goodale, C. L., Apps, M. J., Birdsey, R. A., Field, C. B., Heath, L. S., Houghton, R. A., Jenkins, J. C., Kohlmaier, G. H., Kurz, W., Liu, S., Nabuurs, G., Nilsson, S., Shvidenko, A. Z., 2002: Forest carbon sinks in the northern hemisphere. Ecological Applications,12 (3), pp. 891–899.
Gough, C. M., Vogel, C. S., Schmid, H, P., Curtis P. S., 2008: Controls on annual forest carbon storage: lessons from the past and predictions for the future. Bioscience, 58 (7), pp. 609–622.
Gulsunar, M., 2011: Remote sensing method for forest carbon capacity estimation (The example of Duzdag Forest Management Chiefdom). MsD. Thesis, Karadeniz Technical University, Graduate School of Natural and Applied Sciences, Trabzon, Turkey, 2011.
IPCC, Climate Change 2001: Working Group I: The Scientific Basis. Cambridge University Press, New York.
Langner, A., Samejima, H., Ong, R. C., Titin, J., Kitayama, K., 2012: Integration of carbon conservation into sustainable forest