An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India
Abstract
Anthropogenic activities are leads to changing a natural land cover, and consequences are severe to human and environments etc. The present study has examined the Muthupet mangrove forest and its surrounding land-use changes from 1975 to 2015 using the geospatial technology. An assessment of land use and land cover was done at Muthupet mangrove forest which is an occupied the three coastal district of Tamilnadu i.e. Thanjavur, Thiruvarur, and Nagappattinam. The remote sensing (MSS, TM, and OLI) data was adopted to explore the land use and land cover with help of visual image interpretation. The study had justified the results based upon the ground truth verification, and 203 sites were selected for explore the 10 land use categories. An Accuracy Assessment has done based on the KAPPA index for the year 2015 classified image and appraisal of land use change detection from 1975 to 2015 for all the categories. The study revealed that the land use and land cover condition from the 1975 to 2015, for example 1975 water bodies covered an area of about 156.1 km2, and 2015 it has comprised 89.8 km2. An appraisal of land use and land cover clearly is evidence in 2005 entire land use and land cover changed, and reasons for that an influence of the Tsunami. Consequently, Muthupet mangrove forest is one of the important to human and environments, and the present study has exposed that the changes of the mangrove forest, and its impact on to the coastal community.
Keywords : Mangrove Fores; Remote sensing; LULC; Classification; Change detection
Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember
This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
References
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Rao, K. S., & Pant, R. (2001). Land use dynamics and landscape change pattern in a typical micro watershed in the mid elevation zone of central Himalaya, India. Agriculture, Ecosystems and Environment, 86(2), 113–124. https://doi.org/10.1016/S0167-8809(00)00274-7.
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Thakur, S., Maity, D., Mondal, I., Basumatary, G., Ghosh, P. B., Das, P., & De, T. K. (2021). Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environment, Development and Sustainability, 23(2), 1917–1943. https://doi.org/10.1007/s10668-020-00656-7.
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Widiawaty, M. A., Ismail, A., Dede, M., & Nurhanifah, N. (2020). Modeling land use and land cover dynamic using geographic information system and Markov-CA. Geosfera Indonesia, 5(2), 210. https://doi.org/10.19184/geosi.v5i2.17596.
Wu, Y., Li, S., & Yu, S. (2016). Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China. Environmental Monitoring and Assessment, 188(1), 1–15. https://doi.org/10.1007/s10661-015-5069-2.
Anderson, J. (1976). A Land use and land cover classification system for use with remote sensor data. US Government Printing Office.
Annaidasan, K. N. K. (2017). Multi temporal assessment of shoreline changes using geoinformatics in Muthupet Lagoon, Tamil Nadu, India. Interantiaonal Journal of Environment, Ecology, Family and Urban Studies (IJEEFUS), 7(6), 1–6.
Bogale, A. (2020). Review, impact of land use/cover change on soil erosion in the Lake Tana Basin, Upper Blue Nile, Ethiopia. Applied Water Science, 10(12), 1–6. https://doi.org/10.1007/s13201-020-01325-w.
Brown, D. G., & Duh, J. Der. (2004). Spatial simulation for translating from land use to land cover. International Journal of Geographical Information Science, 18(1), 35–60. https://doi.org/10.1080/13658810310001620906.
Cleyndert, G. D. J., Sanchez, A. C., Seki, H. A., Shirima, D. D., Munishi, P. K. T., Burgess, N., Calders, K., & Marchant, R. (2020). The effects of seaward distance on above and below ground carbon stocks in estuarine mangrove ecosystems. Carbon Balance and Management, 1–15. https://doi.org/10.1186/s13021-020-00161-4.
Cohen, J. (1960). A Coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20(1), 37–46. https://doi.org/10.1177/001316446002000104.
Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37(1), 35–46. https://doi.org/10.1016/0034-4257(91)90048-B.
Güler, M., Yomralioǧu, T., & Reis, S. (2007). Using landsat data to determine land use/land cover changes in Samsun, Turkey. Environmental Monitoring and Assessment, 127(1–3), 155–167. https://doi.org/10.1007/s10661-006-9270-1.
Hanafi, F., Rahmadewi, D., & Setiawan, F. (2021). Land cover changes based on cellular automata for land surface temperature in Semarang Regency. Geosfera Indonesia, 6(3), 301–318. https://doi.org/10.19184/geosi.v6i3.23471.
Islam, M. M., Borgqvist, H., & Kumar, L. (2019). Monitoring Mangrove forest landcover changes in the coastline of Bangladesh from 1976 to 2015. Geocarto International, 34(13), 1458–1476. https://doi.org/10.1080/10106049.2018.1489423.
Jaganathan, R., Annaidasan, K., Surendran, D., & Tamilarasan, V. (2010). Land use / land cover change detection In Kumbakonam Taluk , Tamil Nadu : A Geoinformatics Approach. The Indian Geographical Journal, 85(1), 29–36.
Lambin, E. F., Geist, H. J., & Lepers, E. (2003). Dynamics of land-use and land-cover change in tropical regions. Annual Review of Environment and Resources, 28, 205–241. https://doi.org/10.1146/annurev.energy.28.050302.105459.
Liu, X., Fatoyinbo, T. E., Thomas, N. M., Guan, W. W., Zhan, Y., Mondal, P., Lagomasino, D., Simard, M., Trettin, C. C., Deo, R., & Barenblitt, A. (2021). Large-scale high-resolution coastal mangrove forests mapping across West Africa with machine learning ensemble and satellite big data. Frontiers in Earth Science, 8(January), 1–15. https://doi.org/10.3389/feart.2020.560933.
Melet, A., Teatini, P., Le Cozannet, G., Jamet, C., Conversi, A., Benveniste, J., & Almar, R. (2020). Earth observations for monitoring marine coastal hazards and their drivers. Surveys in Geophysics 41(6). https://doi.org/10.1007/s10712-020-09594-5.
Meli Fokeng, R., Gadinga Forje, W., Meli Meli, V., & Nyuyki Bodzemo, B. (2020). Multi-temporal forest cover change detection in the Metchie-Ngoum Protection Forest Reserve, West Region of Cameroon. Egyptian Journal of Remote Sensing and Space Science, 23(1), 113–124. https://doi.org/10.1016/j.ejrs.2018.12.002.
Mishra, P. K., Rai, A., & Rai, S. C. (2020). Land use and land cover change detection using geospatial techniques in the Sikkim Himalaya, India. Egyptian Journal of Remote Sensing and Space Science, 23(2), 133–143. https://doi.org/10.1016/j.ejrs.2019.02.001.
Mohan, M. (2005). Urban land cover/land use change detection in National Capital Region (NCR) Delhi: A Study of Faridabad District. FIG Working Week.
Mundia, C. N., & Aniya, M. (2005). Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. International Journal of Remote Sensing, 26(13), 2831–2849. https://doi.org/10.1080/01431160500117865.
Muttitanon, W., & Tripathi, N. K. (2005). Land use/land cover changes in the coastal zone of Ban Don Bay, Thailand using Landsat 5 TM data. International Journal of Remote Sensing, 26(11), 2311–2323. https://doi.org/10.1080/0143116051233132666.
Narmada, K., & Annaidasan, K. (2019). Estimation of the Temporal Change in Carbon Stock of Muthupet Mangroves in Tamil Nadu Using Remote Sensing Techniques. Journal of Geography, Environment and Earth Science International, 19(4), 1–7. https://doi.org/10.9734/jgeesi/2019/v19i430096.
Nguyen, H. T. T., Hardy, G. E. S., Le, T. Van, Nguyen, H. Q., Nguyen, H. H., Nguyen, T. Van, & Dell, B. (2021). Mangrove forest landcover changes in coastal vietnam: A case study from 1973 to 2020 in thanh hoa and nghe an provinces. Forests, 12(5), 1–20. https://doi.org/10.3390/f12050637.
NRSC. (2007). Natural Resources Census National Land Use and Land Cover Mapping Using Multi-Temporal AWiFS Data. June. https://bhuvanapp1.nrsc.gov.in/
NRSC. (2014). Natural Resource Census ‐ Land Use Land Cover Database. Technical Report – Ver.1, 1–9. https://bhuvanapp1.nrsc.gov.in/2dresources/thematic/2LULC/lulc1112.pdf.
Pitkänen, T. P., Sirro, L., Häme, L., Häme, T., Törmä, M., & Kangas, A. (2020). Errors related to the automatized satellite-based change detection of boreal forests in Finland. International Journal of Applied Earth Observation and Geoinformation, 86(August 2019), 102011. https://doi.org/10.1016/j.jag.2019.102011.
Raj, A., & Sharma, L. K. (2022). Assessment of land-use dynamics of the Aravalli range (India) using integrated geospatial and CART approach. Earth Science Informatics, 15(1), 497–522. https://doi.org/10.1007/s12145-021-00753-9.
Rao, K. S., & Pant, R. (2001). Land use dynamics and landscape change pattern in a typical micro watershed in the mid elevation zone of central Himalaya, India. Agriculture, Ecosystems and Environment, 86(2), 113–124. https://doi.org/10.1016/S0167-8809(00)00274-7.
Sibanda, S., & Ahmed, F. (2021). Modelling historic and future land use/land cover changes and their impact on wetland area in Shashe sub-catchment, Zimbabwe. Modeling Earth Systems and Environment, 7(1), 57–70. https://doi.org/10.1007/s40808-020-00963-y.
Temgoua, L. F., Meyabeme Elono, A. L., Mfonkwet Njiaghait, Y., Ngouh, A., & Nzuta Kengne, C. (2021). Land use and land cover dynamics in the Melap Forest Reserve, West Cameroon: implications for sustainable management. Geology, Ecology, and Landscapes, 00(00), 1–11. https://doi.org/10.1080/24749508.2021.1923269.
Tewabe, D., & Fentahun, T. (2020). Assessing land use and land cover change detection using remote sensing in the Lake Tana Basin, Northwest Ethiopia. Cogent Environmental Science, 6(1). https://doi.org/10.1080/23311843.2020.1778998.
Thakur, S., Maity, D., Mondal, I., Basumatary, G., Ghosh, P. B., Das, P., & De, T. K. (2021). Assessment of changes in land use, land cover, and land surface temperature in the mangrove forest of Sundarbans, northeast coast of India. Environment, Development and Sustainability, 23(2), 1917–1943. https://doi.org/10.1007/s10668-020-00656-7.
Vivekananda, G. N., Swathi, R., & Sujith, A. (2021). Multi-temporal image analysis for LULC classification and change detection. European Journal of Remote Sensing, 54(2), 189–199. https://doi.org/10.1080/22797254.2020.1771215.
Weslati, O., Bouaziz, S., & Serbaji, M. M. (2020). Mapping and monitoring land use and land cover changes in Mellegue watershed using remote sensing and GIS. Arabian Journal of Geosciences, 13(14). https://doi.org/10.1007/s12517-020-05664-5.
Widiawaty, M. A., Ismail, A., Dede, M., & Nurhanifah, N. (2020). Modeling land use and land cover dynamic using geographic information system and Markov-CA. Geosfera Indonesia, 5(2), 210. https://doi.org/10.19184/geosi.v5i2.17596.
Wu, Y., Li, S., & Yu, S. (2016). Monitoring urban expansion and its effects on land use and land cover changes in Guangzhou city, China. Environmental Monitoring and Assessment, 188(1), 1–15. https://doi.org/10.1007/s10661-015-5069-2.
Published
2022-08-28
How to Cite
KRISHNAN, Annaidasan; RAMASAMY, Jaganathan.
An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India.
Geosfera Indonesia, [S.l.], v. 7, n. 2, p. 119-135, aug. 2022.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/28077>. Date accessed: 23 nov. 2024.
doi: https://doi.org/10.19184/geosi.v7i2.28077.
Section
Original Research Articles
