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A. G. Koppad Pallavi. P Banavasi Syeda Sarfin

Abstract

The study was conducted in Joida Taluk of Uttar Kannada district, Karnataka to assess the land use land cover (LULC) and carbon sequestration of the forest during the year 2019-20. The ground truth data for different LULC was collected using GPS, and data was used for classification of IRS LISS 4 data using maximum likelihood classifier in ERDAS imagine software. The sample plots of 23.2 m X 23.2 m were laid out randomly in forests and growth parameters (tree height and diameter) were recorded, and biomass was estimated using the standard formula. There are eight LULC classes’ viz., dense forest, moderately dense forest, open/sparse forest, scrub forest, agriculture, settlement, horticulture plantation and waterbody. The overall accuracy of the classification was 97.09%. The total biomass in Joida Taluk from four forest classes (dense forest, moderately dense forest, open/sparse forest and scrub forest) was 44.16 million m3 and carbon sequestered was 15.57 million tonnes. The NDVI values ranging from -0.23 to 0.74, indicating a higher value for dense forest. Based on this study, it is concluded that forests have potential in carbon sequestration, which in turn helps in mitigating the climate change.

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Keywords

Carbon sequestration, Forest biomass, LULC, NDVI, Remote sensing

References
Cannell, M. G. R. and Dewar, R. C. (1995). The carbon sink provided by plantation forests and their products in Britain. Forestry: An International Journal of Forest Research, 68 (1): 35 - 48. https://doi.org/10.1093/forestry/6 8.1.35.
Csillik, Ovidiu, Pramukta Kumar, Joseph Mascaro, Tara O’Shea, and Gregory P. Asner (2019). Monitoring tropical forest carbon stocks and emissions using Planet satellite data. Scientific Reports 9(1):1-12. doi.org/10.1038/s41598-019-54386-6.
Congalton, Russell G. (2001). Accuracy assessment and validation of remotely sensed and other spatial information. International Journal of Wildland Fire, 10(4): 321-328. DOI: 10.1071/WF01031.
Gandhi, G., Meera, S., Parthiban, Thummalu, N. and Christy, A. (2015). NDVI: Vegetation change detection using remote sensing and GIS - A case study of Vellore District. Procedia Computer Science, 57: 1199-1210. doi.org/10.1016/j.procs.2015.07.415.
Koppad, A. G., and Tikhile, P. (2013). Influence of land use land cover classes on carbon sequestration in soils of Sirsi and Siddapur taluka of Uttara Kannada District, India. International Journal of Current Research., 5 (4): 1012-1015.
Koppad, A. G., and Tikhile, P. (2014). Role of forest on carbon sequestration in soils of Joida and Karwar taluka of Uttara Kannada district. Indian Forester, 140 (3): 260-264.
Koppad, A.G., and Janagoudar, B. S. (2018). Effect of Land Use Land Cover on Soil Carbon Sequestration in Haliyal Taluka of Uttara Kannada District. Indian Forester 144, 3: 234-237.
Koppad, A.G., and Malini P J. (2019). Assessment Of Land Use Land Cover Classification And Water Resource Impact On Forest Productivity And Carbon Sequestration In Yellapur And Haliyal Taluka Of Uttara Kannada District, Karnataka, India Through Geoinformatics Approach. International symposium on applied Geoinformatics 1(1):59-63.
Kiran, V. S. S., Y. K. Srivastava, and M. Jagannadha Rao. (2014). Utilization of Resources at LISS IV Data for Infrastructure Updation and Land Use/Land Cover Mapping-A Case Study from Simlipal Block, Bankura District, W. Bengal." International Journal of Advance Remote Sensing GIS 3 (1): 592-597.
Lizhuang, L., Chen, F., Shi, L. and Niu, S. (2018). NDVI derived forest area change and its driving factors in China. PloS one, 13: 10. doi.org/10.1371/journal.pon e.020 588
MacDicken, Kenneth G (1997). A guide to monitoring carbon storage in forestry and agroforestry projects. Forest Carbon Monitoring Program.1-87.
Madugundu, Rangaswamy, Vyjayanthi Nizalapur, and Chandra Shekhar Jha (2008). "Estimation of LAI and above-ground biomass in deciduous forests: Western Ghats of Karnataka, India." International Journal of Applied Earth Observation and Geoinformation 10(2):211-219. doi:10.1016/j.jag.2007.11.004.
Pandey, P. C., Prashant, K., Srivastava, Chetri, T., Choudhary, B. K. and Kumar, P. (2019). Forest biomass estimation using remote sensing and field inventory: A case study of Tripura, India. Canadian Journal of Remote Sens., 32(5): 355-366. doi: 10.1007/s10661-019-7730-7.
Sinha, S., Jeganathan, C., Sharma, L. K. and Nathawat, M. S. (2015). A review of radar remote sensing for biomass estimation. International Journal of Environmental Science and Technology., 15(12): 1779-1792.
Rwanga, Sophia S., and Julius M. Ndambuki (2017). "Accuracy assessment of land use/land cover classification using remote sensing and GIS." International Journal of Geoscience,s 8(04):611. doi.org/10.4236/ijg.2017.8 4033.
Zavoianu, F., Caramizoiub, A. and Badeaa, D. (2004). Study and accuracy assessment of remote sensing data for environmental change detection in Romanian coastal zone of the Black Sea. Proceeding of ISPRS, pp. 778-783.
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Koppad, A. G. ., Banavasi, P. P., & Sarfin, S. (2020). The Assessment of land use land cover and carbon sequestration in forests of Joida Taluk of Uttar Kannada district using Remote sensing technique. Journal of Applied and Natural Science, 12(3), 344-348. https://doi.org/10.31018/jans.v12i3.2317
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