Abstract
The soil has organic and inorganic matter, which helps the plants to grow. The main component of organic matter is soil organic carbon (SOC). SOC is studied in the Thuckalay block of the Kanyakumari district with Sentinel-2 data. The following indices, Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BSI), and Soil Adjusted Vegetation Index (SAVI), are analyzed using linear regression, and R2 values were compared. The linear regression values for NDVI are R2 = 0.5146; for BSI, R2 = 0.7608; and for SAVI, R2 = 0.7493. Then 15 soil samples were collected, and the Walkley-Black technique was used for the analysis of soil organic carbon for validation. The relationship between SOC and BSI is high, while the relationship between SOC and NDVI is very low, and the relationship between SOC and SAVI is medium. When BSI is high, the SOC will also be increased, and vice versa, and the SOC has a low impact due to the vegetation content. Land degradation causes nutrient depletion and soil erosion which can be reduced by analyzing the relationship between LULC and land degradation. The identification of SOC helps in precision farming and good yield for agriculture. Increasing SOC levels in degraded soils helps to restore soil health, improve soil fertility, and enhance the capacity of the soil to support healthy ecosystems.
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References
Jandl et al (2014) Current status, uncertainty and future needs in soil organic carbon monitoring. Elsevier. https://doi.org/10.1016/j.scitotenv.2013.08.026
Lal R (2010) Beyond Copenhagen: Mitigating climate change and achieving food security through soil carbon sequestration. Food Secur 2(2):169–177. https://doi.org/10.1007/S12571-010-0060-9/TABLES/3
Schlesinger WHA, Jeffrey A (2000) Soil respiration and the global carbon cycle. Biogeochemistry 48:7–20
Verchot et al (2007) Climate change: linking adaptation and mitigation through agroforestry. Mitig Adapt Strateg Glob Chang 12(5):901–918. https://doi.org/10.1007/s11027-007-9105-6
Lal R (2006) Carbon management in agricultural soils. Mitig Adapt Strateg Glob Chang. https://doi.org/10.1007/s11027-006-9036-7
Driss H, John M, Elizabeth RP, Zarco-Tejada, Strachan PJ, Ian B (2003) Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sens Environ. https://doi.org/10.1016/j.rse.2003.12.013
Post WM, Kwon KC (2000) Soil carbon sequestration and land-use change: processes and potential. Glob Chang Biol 6:317–328
Gunnar VT, Lal R, Singh BR (2005) Soil carbon sequestration in sub-Saharan Africa: a review. Land Degrad Dev 16(1):53–71, Jan 2005. https://doi.org/10.1002/LDR.644.
Lal R (2003) Offsetting global CO2 emissions by restoration of degraded soils and intensification of world agriculture and forestry. Land Degrad Dev 14(3):309–322. https://doi.org/10.1002/LDR.562
Pimentel D, Kounang N (1998) Ecology of soil erosion in ecosystems. Ecosystem
Vågen TGW, Leigh A (2013) Mapping of soil organic carbon stocks for spatially explicit assessments of climate change mitigation potential. Environ Res Lett 8(1):015011, Feb 20130. https://doi.org/10.1088/1748-9326/8/1/015011
Amundson R (2001) The carbon budget in soils. Earth Planet Sci
Jobbagy EGJ, Jobba J, Robert B (2000) April 2000 423 Belowground processes and global change 423 the vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol Appl 10(2):423–436
Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta analysis. Glob Chang Biol 8(4):345–360. https://doi.org/10.1046/J.1354-1013.2002.00486.X
Haboudane DM, Pattey JR, Zarco-Tejada E, Strachan PJ, Ian B (2004) Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sens Environ. https://doi.org/10.1016/j.rse.2003.12.013.
Berthrong ST, Jobbagy EG, Jackson RB (2009) A global meta-analysis of soil exchangeable cations, pH, carbon, and nitrogen with afforestation. Ecol Appl 19(8):2228. https://doi.org/10.1890/08-1730.1
Noreen B et al. (2002) Linkages between climate change and sustainable development. Clim Policy 2:129–144, Accessed: 02 Feb 2023. [Online]. Available: www.oecd.org
Mark J, Tim W (2007) A framework for assessing climate change vulnerability of the Canadian forest sector. Forest Chronicle 83
Lal R (2004) Soil carbon sequestration to mitigate climate change. Geoderma 123(1–2):1–22. https://doi.org/10.1016/J.GEODERMA.2004.01.032
Kirschbaum MUF (2000) Will changes in soil organic carbon act as a positive or negative feedback on global warming? Biogeochemistry 48:21–51
Scharlemann JPW, Tanner EVJ, Hiederer R, Kapos V (2014) Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Manag 5(1):81–91. https://doi.org/10.4155/CMT.13.77/SUPPL_FILE/TCMT_A_10816421_SM0001.DOC
Keshavarzi A, Sarmadian F, Shiri J, Iqbal M, Tirado-Corbalá R, Omran ESE (2017) Application of ANFIS-based subtractive clustering algorithm in soil cation exchange capacity estimation using soil and remotely sensed data. Measurement 95:173–180. https://doi.org/10.1016/J.MEASUREMENT.2016.10.010
Jandl R et al (2013) Current status, uncertainty and future needs in soil organic carbon monitoring ☆. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2013.08.026
Vaudour E, Gilliot JM, Bel L, Lefevre J, Chehdi K (2016) Regional prediction of soil organic carbon content over temperate croplands using visible near-infrared airborne hyperspectral imagery and synchronous field spectra. Int J Appl Earth Obs Geoinf 49:24–38. https://doi.org/10.1016/J.JAG.2016.01.005
Zeng Y, Huang W, Zhan F, Zhang H, Liu H (2010) Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries. Geo-Spat Inf Sci 13(1):1–7. https://doi.org/10.1007/S11806-010-0204-2
Saei Jamalabad M, Abkar AA (2004) Forest canopy density monitoring, using satellite images. Int Soc Photogrammetry Remote Sens
Huete AR (1988) A soil-adjusted vegetation index (SAVI). Remote Sens Environ 25(3):295–309. https://doi.org/10.1016/0034-4257(88)90106-X
Umrit G, Ng Cheong R, Gillabel J, Merckx R (2014) Effect of conventional versus mechanized sugarcane cropping systems on soil organic carbon stocks and labile carbon pools in Mauritius as revealed by 13C natural abundance. Plant Soil 379(1–2):177–192, Jun 2014. https://doi.org/10.1007/S11104-014-2053-5/FIGURES/4
Jandl R et al (2014) Current status, uncertainty and future needs in soil organic carbon monitoring. Sci Total Environ 468–469:376–383. https://doi.org/10.1016/j.scitotenv.2013.08.026
Wei X, Shao M, Gale W, Li L (2014) Global pattern of soil carbon losses due to the conversion of forests to agricultural land. Sci Rep. https://doi.org/10.1038/srep04062
ShunHua Y et al (2015) The spatial variability of soil organic carbon in plain-hills transition belt and its environmental impact. China Environ Sci 35(12):3728–3736
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Arthi, A.P., Kumar, J.S. (2024). Spatial Analysis of Soil Organic Carbon in the Thuckalay Block of the Kanyakumari District. In: Reddy, K.R., Ravichandran, P.T., Ayothiraman, R., Joseph, A. (eds) Recent Advances in Civil Engineering. ICC IDEA 2023. Lecture Notes in Civil Engineering, vol 398. Springer, Singapore. https://doi.org/10.1007/978-981-99-6229-7_15
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