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:: Volume 13, Issue 2 (12-2023) ::
JGST 2023, 13(2): 95-106 Back to browse issues page
The Economic Valuation of Oak Trees Decline Regions (Quercus brantii .Lindl) in Semi-Mediterranean Zagros Forests Using Sentinel-2 Satellite Imagery
Zohreh Bazvand , Kamran Adeli * , Javavd Soosani , Ali Asghar Torahi
Abstract:   (782 Views)
This study used satellite imagery to evaluate the effect of oak trees’ decline on carbon storage and its economic value in Zagros forests of Kuhdasht, Lorestan Province, Iran. To this goal, the study used the Sentinel-2 Satellite MSI sensor data recorded on June 15, 2021. In order to measure the ground biomass, we randomly selected 250 square samples with dimensions of 30 × 30. The Diameter at Breast Height [DBH] of each tree was measured and the amount of ground biomass for each sample plot was also obtained. General multivariate regression, Artificial Neural Networks, and K-nearest neighbors were used for modeling the ground biomass of the selected regions. In order to value the amount of stored carbon, the average rate was used for each ton of absorbed carbon dioxide gas (54 euros). The plot for the monetary valuation of carbon (in terms of carbon dioxide absorption) was determined by using the relationship between the amount of ground biomass and stored carbon, as well as absorbed carbon dioxide gas. The results showed that linear regression obtained by the vegetation index of NDVI with R2=0.73 and RMSE (%) = 21.88 was the best model for the studied area. The findings confirm that Sentinel-2 imagery data were considerably efficient for estimating the ground biomass of the Zagros declined forests.  Moreover, the results of the economic valuation of the carbon inventory in terms of carbon dioxide absorption service showed that each hectare of forests in the region has a value equivalent to 2547.12 Million Rial in carbon dioxide absorption function. The economic valuation of declined areas indicated that the more the degradation [decline] of these areas escalates, the more their economic value decreases. Accordingly, the highest value was obtained in the healthy areas and the lowest amount was calculated in the most declined regions. The findings suggest that Sentinel satellite images could be used to determine the accurate biomass map for the degraded areas. This map can be employed as a base map for decision-making, forestation/protection operations, and the economic valuation of these invaluable resources. 

 
Article number: 8
Keywords: Decline of oak trees, Economic value, Carbon storage, Biomass, Kouhdasht, Lorestan.
Full-Text [PDF 1307 kb]   (503 Downloads)    
Type of Study: Research | Subject: Photo&RS
Received: 2023/11/19
References
1. Molaei, M. & Kavoosi Kalashami, M. (2011). Estimating the preservation value of Lilium Ledebourii using single bounded dichotomous choice contingent valuation method. Journal of Economy and Agricultural Development (Agricultural Sciences and Industries), 25(3), 322-329, (in Persian).
2. Mafi-Gholami D., Pirasteh S., Ellison J.C., Jaafarid A. (2021). Fuzzy-based vulnerability assessment of coupled social-ecological systems to multiple environmental hazards, Journal of Environmental Management. 299 (2021) 113573. doi.org/10.1016/j.jenvman.2021.113573. [DOI:10.1016/j.jenvman.2021.113573]
3. Murphy, M., T. Balser, N. Buchmann, V. Hahn, and C. Potvin. 2008. Linking tree biodiversity to Agriculture Sciences and Technology, Natural Resources. Water and Soil Science. 52:14-19.
4. Badehian, Z. & Mansouri, M. (2019). Comparing the economic value of market function and un-market function of some populus species. Iranian Journal of Wood and Paper, 10(1), 217-222, (in Persian).
5. Zarafshar, M., Rousta, M., Matinizadeh, M., Bordbar, S.K., Enayati, K., Negahdarsaber, M. & Abassi, A. (2020). Comparison of the amount of Carbon and Nitrogen storage in the soil of hand-planted forest, natural forest and watershed agricultural lands of Arjan plain in Fars province. Iranian Forest Ecology Journal, 8(16), 165-172, (in Persian). [DOI:10.52547/ifej.8.16.165]
6. Li W., Zhu J., Pirasteh S., Zhu Q., Fu L., Wu J. (2022). Investigations of disaster information representation from geospatial perspective: progress, challenges, and recommendations. Transactions in GIS. DOI: 10.1111/tgis.12922, 00:1-23. [DOI:10.1111/tgis.12922]
7. Pirasteh S., Zenner E.K., Mafi-Gholami D., Jaafarid A., Nouri Kamarie A., Liu G., Zhu Q., Li J. (2021). Remote sensing of multi-decadal spatial extents and biomass changes of mangroves in response to climate change and anthropogenic impacts, International Journal of Applied Earth Observation and Geoinformation. Vol. 102, https://doi.org/10.1016/j.jag.2021.102390 [DOI:10.1016/j.jag.2021.102390.]
8. Ghanbari, M., Kafaky, S., Mataji, A. & Akhavan, R. (2020). Estimation of forest above ground biomass in Hyrcanian forests using satellite imagery. Journal of Environmental Sciences and Technology, 22 (3), 63-78.
9. Katani, J.Z. 2013. Allometric models for prediction of above-and belowground biomass of trees in the miombo woodlands of Tanzania. Forest Ecology and Management, 310: 87-101. [DOI:10.1016/j.foreco.2013.08.003]
10. Sarouie, S., Darvish-Sefat, A., & Namirian, M. (2021). Modeling the estimation of woody ground biomass of Zagros oak high forest trees using Sentinel-1 satellite radar data. Iranian Remote Sensing and GIS Journal, 12(4), 32-52, (in Persian). [DOI:10.52547/gisj.12.4.35]
11. IPCC 2007: Climate Change 2007: Mitigation of Climate Change. IPCC Fourth Assessment Report (AR4). Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, 2007: Metz, B., O. R. Davidson, P. R Bosch, R. Dave, and L.A Meyer. (eds). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
12. Gunawardena, A. R., S.P. Nissanka, and N.D.K. Dayawansa. 2006. Relationship between above ground live biomass and satellite image spectral responses (Landsat ETM+) of Pinus caribaea morelet at lower Hantana region in Sri Lanka. Tropical Agricultural Research,18.
13. Li W., Zhu J., Pirasteh S., Zhu Q., Fu L., Wu J. (2022). Investigations of disaster information representation from geospatial perspective: progress, challenges, and recommendations. Transactions in GIS. DOI: 10.1111/tgis.12922, 00:1-23. [DOI:10.1111/tgis.12922]
14. Asgari, H. (2013). Economic valuation of oak forests in Ilam province. Journal of Natural Resources Economy, 2(2), 77-88, (in Persian).
15. Zhang, W., L Zhao, Y. Li, J. Shi, M. Yan, and Y. Ji. 2022. Forest Above-Ground Biomass Inversion Using Optical and SAR Images Based on a Multi-Step Feature Optimized Inversion Model. Remote Sensing, 14(7): 1608. [DOI:10.3390/rs14071608]
16. Aynekulu, E., M. Suber, M. Van Noordwijk, J. Arango, J.M. Roshetko, and T.S. Rosenstock. 2020. Carbon storage potential of silvopastoral systems of Colombia. Land, 9(9), 309. [DOI:10.3390/land9090309]
17. Estrada, G. C. D., M. L. Soares, V. Fernadez, and P. M. de Almeida. 2015. The economic evaluation of carbon storage and sequestration as ecosystem services of mangroves: a case study from southeastern Brazil. International Journal of Biodiversity Science, Ecosystem Services & Management, 11(1): 29-35. [DOI:10.1080/21513732.2014.963676]
18. Jafarzadeh, A., Mahdavi, A., Shamsi, S.R. & Yousefpour, R. (2020). Economic evaluation of some of the most important ecosystem services in Zagros forests. Environmental Sciencies, 18(1), 137-150, (in Persian). [DOI:10.29252/envs.18.1.137]
19. Sohrabi, H., Hosseini, S.M. & Zobeiri, M. (2010). Estimation of forest stand volume using textural indices of aerial images, Iranian Journal of Forest and Poplar Research 12(4), 297-306, (in Persian).
20. Gol-Mohammadi, F,. Hassanzad Navroodi, I., Bonyad, A., & Mirzaee, J. (2017). Effects of some environmental factors on dieback severity of trees in middle Zagros forests of Iran: Case Study, strait Daalaab, Ilam Province. Journal of Plant Research (Journal of Iran Biology), 30(3), 644-655, (in Persian).
21. Yusof vand, M., Soosani, J., & Nagavi, H. (2023). Estimation of biomass and its reduction in forests affected by deterioration in Dadabad region of Lorestan province. Iranian Journal of Forest, 13(5), 17-28.
22. Balan, B., Mohaghegh, S., & Ameri, S. (1995). State-of-the-art in permeability determination from well log data: part 1-A comparative study, model development. Paper SPE, 30978, 17-21. [DOI:10.2118/30978-MS]
23. Werner D, Francisco J A, Artifitial intelligence in the life sciences, Artif Intell Rev 2003; 20: 7-11.
24. Häyhä, T., P.P Franzese, A. Paletto, and D.F. Brian. 2015. Assessing, valuing, and mapping ecosystem services in Alpine forests, Ecosystem Services, 14: 12-23. [DOI:10.1016/j.ecoser.2015.03.001]
25. Sinha S.K., H. Padalia, A. Dasgupta, J. Verrelst and J.P. Rivera. 2020. Estimation of leaf area index using PROSAIL based LUT inversion, MLRAGPR and empirical models: Case study of tropical deciduous forest plantation, North India. Int J Appl Earth Obs Geoinformation, 86. [DOI:10.1016/j.jag.2019.102027]
26. Li, X, and C. Liu. 2011. Carbon storage and sequestration by urban forests in Shenyang, China. Urban Forestry and Urban Greening, 11 (2): 121-128. [DOI:10.1016/j.ufug.2011.03.002]
27. Hall, R.J., R.S. Skakun, E.J. Arsenault, and B.S. Case. 2006. Modeling forest stand structure attributes using Landsat ETM+ data: Application to mapping of aboveground biomass and stand volume. Forest ecology and management, 225(1-3):378-390. [DOI:10.1016/j.foreco.2006.01.014]
28. Katani, J.Z. 2013. Allometric models for prediction of above-and belowground biomass of trees in the miombo woodlands of Tanzania. Forest Ecology and Management, 310: 87-101. [DOI:10.1016/j.foreco.2013.08.003]
29. Mobraghi, N., Sharzehee, Gh, Makhdoom, M., Yavari, A., & Ja'fari, H. (2009). Presenting a spatial evaluation model of carbon dioxide absorption performance in the Caspian forests of Iran. Journal of Environmental Science, 51, 68-57, (in Persian).
30. Pato, M., Salehi, A., Zahedi Amiri, G. & Banj Shafie, A. (2016). The economic values of carbon storage functions in different land uses of Northern Zagros forest. Forest Research and Development, 2(4), 367-377, (in Persian).
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bazvand Z, Adeli K, Soosani J, Torahi A A. The Economic Valuation of Oak Trees Decline Regions (Quercus brantii .Lindl) in Semi-Mediterranean Zagros Forests Using Sentinel-2 Satellite Imagery. JGST 2023; 13 (2) : 8
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Volume 13, Issue 2 (12-2023) Back to browse issues page
نشریه علمی علوم و فنون نقشه برداری Journal of Geomatics Science and Technology