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Carbon Sequestration Assessment of the Orchards Using Satellite Data

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study aimed to estimate above-ground carbon sequestration of orchards using satellite data. The research methodology analyzed the relationship between the amount of above-ground carbon sequestration and vegetation indices from the data obtained from LANDSAT 8 OLI including (1) Difference Vegetation Index (DVI), (2) Green Vegetation Index (GVI), (3) Simple Ratio (SR), (4) Normalized Difference Vegetation Index (NDVI), and (5) Transformed Normalized Difference Vegetation Index (TNDVI) in order to find out the most appropriate equation to estimate above-ground carbon sequestration of the orchards in the study area at Sang Kho sub district, Phu Phan district, Sakon Nakhon province in northeast Thailand. The study results found that the relationship between the amount of above-ground carbon sequestration and the most appropriate index relating to vegetation was TNDVI. At any rate, TNDVI had the relationship equation y = 0.226e0.039x and coefficient of determination R2 = 0.877, which represented the amount of above-ground carbon sequestration in the study area in a total of 40.86 tons per hectare.
Rocznik
Strony
11--17
Opis fizyczny
Bibliogr. 26 poz., tab., rys.
Twórcy
autor
  • Faculty of Science, Mahasarakham University, Katarawichai, Mahasarakham, 44150, Thailand
autor
  • Faculty of Science, Mahasarakham University, Katarawichai, Mahasarakham, 44150, Thailand
  • Space Technology and Geoinformatics Research Unit, Faculty of Science, Mahasarakham University, Mahasarakham, 44150, Thailand
Bibliografia
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  • 2. Arbind Kumar Shah. 2013. Remote sensing – A part of an Applied Physics. The Himalayan Physics, 4
  • 3. Campbell J.B. 1996. Introduction to Remote Sensing. Taylor & Francis, London.
  • 4. Desert. Journal of Geography and Regional Planning, 5(6), 165-172.
  • 5. Farooq Ahmad, 2011. Spectral vegetation indices performance evaluated for Cholistan
  • 6. Gandia S., Fernández G., García J.C., Moreno J. 2004. Retrieval of Vegetation Biophysical Variables from CHRIS/PROBA Data in the SPARC Campaing. In Proceedings of the 4th ESA CHRIS PROBA Workshop, Frascati, Italy, 28–30 April 2004, 40−48.
  • 7. Gomasathit T., Laosuwan T., Chunpang P., Uraichun Y. 2011. The Real Experience in GIS Teaching Aid by Using GIS Open-Source Software, International Journal of Geoinformatics, 7 (4), 63–67.
  • 8. Jordan C.F. 1969. Derivation of leaf area index from quality of light on the forest floor. Ecology, 50, 663–666.
  • 9. Lal R. 2007. Researchable Priorities in Terrestri al Carbon Sequestration in Central Asia. In: Climate Change and Terrestrial Carbon Sequestration in Central Asia, Lal, R., B.A. Stewart, D.O. Hansen and P. Doraiswamy (Eds.). Routledge, London.
  • 10. Laosuwan T., Uttarak P., Klinhom U., Butthep C., Samek J.H. and Skole D.L. 2011. Development of Web-GIS Application for Carbon Sequestration in Thailand, International Journal of Geoinformatics, 7 (2), 41-47.
  • 11. Laosuwan T., Chunpang P., Sukkasena S. 2011. Development of Robotic Aerial Remote Sensing System for Field Educational Purpose, International Journal of Geoinformatics, 7 (4), 21-27.
  • 12. Laosuwan T., Sangpradid S., Gomasathit T. and Rotjanakusol T. 2016. Application of Remote Sensing Technology for Drought Monitoring in Mahasarakham Province, Thailand. International Journal of Geoinformatics, 12 (3), 17-25.
  • 13. Liaghat S. and Balasundram S.K. 2010. A review: The role of remote sensing in precision agriculture. Am. J. Agric. Biol. Sci., 5, 50-55.
  • 14. Lu D., Mausel P., Brondizio E., Moran E. 2002. Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research. Int. J. Remote Sens., 23, 2651–2671.
  • 15. Litynski J.T., Klara S.M., McIlvried H.G. and Srivastava R.D. 2006. The United States Department of Energy’s regional carbon sequestration partnerships program: A collaborative approach to carbon management. Environ. Int., 32, 128-144.
  • 16. Ogawa H., Yoda K., Ogini K. and Kira T. 1965. Comparative Ecological Study on Three Main Type of Forest Vegetation in Thailand. Nature and Life in Southeast Asia, 4, 49-80.
  • 17. Patel N.K., Saxena R.K., Shiwalkar A. 2007. Study of fractional vegetation cover using high spectral resolution data. J. Indian Soc. Remote Sens., 35, 73–79.
  • 18. Rees W.G. 2013. Physical Principles of Remote Sensing. Cambridge University Press;
  • 19. Rouse J.W., Haas R.H., Schell J.A., Deering D.W., Harlan J.C. 1974. Monitoring the Vernal Advancements and Retrogradation (Greenwave Effect) of Nature Vegetation; NASA/GSFC Final Report; NASA: Greenbelt, MD, USA.
  • 20. Samaniego L., Schulz K. 2009. Supervised classification of agricultural land cover using a modified k-NN technique (MNN) and Landsat remote sensing imagery. Remote Sens., 1, 875–895.
  • 21. Schlerf M., Alzberger C., Hill J. 2005. Remote sensing of forest biophysical variables using HyMap imaging spectrometer data, Remote Sens. Environ, 95, 177–194.
  • 22. Senpaseuth P., Navanugraha C., and Pattanakiat S. 2009. The Estimation of Carbon Storage in Dry Evergreen and Dry Dipterocarp Forests in Sang Khom District, Nong Khai Province, Thailand Environment and Natural Resources Journal, 7(2), 1-11.
  • 23. Teerawong Laosuwan & Pornchai Uttaruk, 2014. Estimating Tree Biomass via Remote Sensing, MSAVI 2, and Fractional Cover Model. IETE Technical Review, 31(5), 362-368.
  • 24. Teerawong Laosuwan and Yannawut Uttaruk, 2016. Estimating Above Ground Carbon Capture Using Remote Sensing Technology in Small Scale Agro Forestry Areas. Agriculture & Forestry, 62 (2), 253-262.
  • 25. Tucker C.J. 1979. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ., 8, 127–150.
  • 26. Wasun Jundang, Ladawan Puangchit and Sapit Diloksumpun, 2010. Carbon Storage of Dry Dipterocarp Forest and Eucalypt Plantation at Mancha Khiri Plantation, Khon Kaen Province. Thai Journal of Forestry, 29 (3), 36-44.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ad6b19b4-3b1b-42d2-b4e9-4ac67082fed7
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