Journal of Veterinary and Animal Sciences

Volume: 55 Issue: 3

  • Open Access
  • Research Article

The application of remote sensing and geographic information system techniques for the analysis of land use and land cover changes in Wayanad district of Kerala

M. G. Bijosh1 and John Abraham1

1 Department of Livestock Production Management, College of Veterinary and Animal Sciences, Pookode, Wayanad-673 576, Kerala Veterinary and Animal Sciences University, Kerala, India

Year: 2024, Page: 516-523, Doi: https://doi.org/10.51966/jvas.2024.55.3.516-523

Received: Nov. 4, 2023 Accepted: March 12, 2024 Published: Sept. 30, 2024

Abstract

Mapping Land Use and Land cover Changes (LULC) and detecting changes using remote sensing and Geographic Information System (GIS) techniques is a cost-effective way of gaining a good understanding of the land cover alteration processes caused by land use change and their effects. This study assessed the transformation of the Wayanad district landscape over a period of 23 years. LANDSAT satellite images (of 30 m resolution) encompassing the area at three epochs were classified into nine classes (coffee dominated mixed crop, built-up, evergreen forest, deciduous forest, grassland, mixed crop with built-up, paddy, tea plantation, and waterbody) using the maximum likelihood algorithm, resulting in classes for each land use. The results showed that over the past 23 years, coffee-dominated mixed crops have increased by 0.84% in 2014 and 11.84% in 2022 compared to 1999; deciduous forest area decreased 3.6% and increased 0.6% in 2014 and 2022, respectively. Tea plantations increased by 0.9% in 2014 and by 0.49% in 2022, which decreased by 0.41% compared to 2014. Built-up has increased by 6.42% and 6.02% in 2014 and 2022 respectively, and slightly decreased by 0.4% compared to 2014. Evergreen forest areas increased in 2014 by 6.68% and 2.28% in 2022 and decreased by 4.44% compared to the previous time period. Grass land areas have decreased by 6.25% and 5.33%, respectively, and mixed crops with built-up areas has decreased by 0.74% and remained the same in the last two epochs, while paddy and waterbodies have decreased by 3.4%, 15.79%, and 0.07 and 0.19%, respectively, in 2014 and 2022 of the total geographical area

Keywords: Remote sensing, GIS techniques, LULC, forest cover

References

Ahmad, N., Khan, S., Ehsan, M., Rehman, F.U. and Al-Shuhail, A. 2022. Estimating the Total Volume of Running Water Bodies Using Geographic Information System (GIS): A Case Study of Peshawar Basin (Pakistan). Sustainability. 14: 3754-3777.

Alaguraja, P., Durairaju, S., Yuvara. D., Sekar, M., Muthuveerran, P., Manivel, M. and                    Thirunavukkaras, A. 2010. Land Use and Land Cover Mapping - Madurai District, Tamilnadu, India Using Remote Sensing and GIS Techniques. Int. J. Civ. Struct. Eng. 1(1): 91-100.

Belay, T. and Mengistu, D.A. 2019. Land use and land cover dynamics and drivers in the Muga watershed, Upper Blue Nile basin, Ethiopia. RSASE. 15: 225-249.

Bassole, A., Brunner, J. and Tunstall, D. 2001. “GIS: Supporting Environmental Planning    and Management in West Africa.” World Resources Institute, London.

      Brahmabhatt, V.S., Dalwadi, G.B., Chhabra, S.B., Ray, S.S. and Dadhwal, V.K. 2000.      Land Use/Land Cover Change Mapping in Mahi Canal Command Area, Gujarat, Using Multi-temporal Satellite Data. J. Indian Soc. Remote Sense. 28(4): 221-232.

      Culvenor, D. 2003. Extracting individual tree information: A survey of techniques for high      spatial resolution imagery. Remote Sensing of Forest Environments, pp. 255-277.

      De Sy, V.M., Herol1, F., Achard, G.P., Asner, A., Held, J. Kellndorfer.  and J. Verbesselt. 2012. Synergies of multiple remote sensing data sources for REDD+ monitoring. Curr. Opin. Environ. Sustain. 4(6): 696-706.

      Elhag, M. 2016. Evaluation of different soil salinity mapping using remote sensing techniques in arid ecosystems, Saudi Arabia. Journal of Sensors. 1: 2-16.

      Feyissa, G. and Gebremariam, E. 2018.  Mapping of landscape structure and forest cover change detection in the mountain chains around Addis Ababa: the case of Wechecha Mountain, Ethiopia. RSASE. 11: 254-264.

      Franklin, S.E. 2001. Remote sensing for sustainable forest management. Boca Raton, Florida: CRC Press. pp. 354.

     Geeraert, L., Hulsmans, E., Helsen, K., Barecha, G., Aerts, R. and Honnay, O. 2019. Rapid diversity and structure degradation over time through continued coffee cultivation in remnant Ethiopian Afromontane forests. Biol. Conserv. 236: 8-16.

     Hegazy, I.R. and Kaloop, M.R. 2015. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. Int. J. Sustain. Built Environ. 4(1): 117-124.

      Hill, D.A. and Leckie, D.G. 1999. International forum: Automated interpretation of high spatial resolution digital imagery for forestry. Proceedings of a workshop held at Victoria, British Columbia, Canada. February 10-12, 1998. Natural Resources Canada, Canadian Forest Service, Victoria, B.C. 339p.

       Houghton, R.A. 1994. The Worldwide Extent of Land Use Change. BioScience. 44: 305 -313.

       Jansen, l.J.M. and Di Gregorio. 2004. Obtaining land-use information from a remotely sensed land cover map: results from a case study in Lebanon. Int. J. of Appli. Earth Obser. Geoinf. 5(2): 141-157.

     Kanga, S., Sharma, L.K., Nathawat, M.S. and Sharma S.K. 2011. Geospatial approach for forest fire risk modelling: a case study of Taradevi Range of Shimla Forest division in Himachal Pradesh (India). Indian Forester. 137(3): 296-303.

      Kanga, S., Sharma, L.K., Pandey, P.C., Nathawat, M.S. and Sharma, S.K. 2013. Forest fire modelling to evaluate potential hazard to tourism sites using geospatial approach. Journal of Geomatics. 7: 93-96.

     Kanga, S., Sharma, L.K., Pandey, P.C. and Nathawat, M.S. 2014. GIS Modelling Approach for Forest Fire Risk Assessment. IJARSGG. 2: 30-34.

     Kanga, S., Sharma, L.K. and Nathawat, M.S. 2015.  Himalayan Forest Fires Risk Management: A geospatial Approach, LAP Lambert Academic Publishing. 188p.

     Karwariya, S. and Goyal, S. 2011. Land Use and Land cover Mapping using Digital Classification in Tikamgarh District, Madhya Pradesh, India using Remote Sensing. Int. J. Geomat. Geosci. 2(5): 1302-1307.

      Lillesand, T., Kiefer, R. and Chipman, J. 2003. Remote Sensing and Image Interpretation. 5th Edition, Wiley, New York, 784.

      Meyer, W.B. 1993. Past and Present Land-Use and Land- Cover in the U.S.A.   Consequences.  1: 24-33.

      Minta, M., Kibret, K., Thorne, P., Nigussie, T. and Nigatu, L. 2018. Land use and land cover dynamics in Dendi-Jeldu hilly-mountainous areas in the central Ethiopian highlands. Geoderma. 314: 27-36.

      Nunes, C. and Auge J.I. 1999. Land-Use and Land-Cover Implementation Strategy.  International Geosphere-Biosphere Programme, Stockholm. 125 p.

Quan, R.S., Liu, M., Lu, M., Zhang, L.J., Wang, J.J. and Xu, S.Y. 2010.Waterlogging risk assessment based on land use/cover change: A case study in Pudong New Area, Shanghai. Environ. Earth Sci. 61(6): 1113-1121.

Quan, B., Xiao, Z., Römkens, M., Bai, Y. and Lei, S. 2013. Spatiotemporal Urban Land Use Changes in the Changzhutan Region of Hunan Province in China. J. Geogr. Inf. Syst. 5: 136-147.

Roy, B. and Kasemi, N. 2021. Monitoring urban growth dynamics using remote sensing and GIS techniques of Raiganj Urban Agglomeration, India. Egypt. J. Remote Sensing Space Sci. 24: 221–230.

Ruiz-Luna, A. and Berlanga-Robles, C.A. 2003. Land use, land cover changes and coastal lagoon surface reduction associated with urban growth in northwest Mexico. Land. Ecol. 18: 159-171.

Selcuk, R., Nisanci, R., Uzun, B., Yalcin, A., Inan, H. and Yomralioglu, T. 2003. Monitoring land-use changes by GIS and remote sensing techniques: case study of Trabzon. In: Proceedings of 2nd FIG Regional Conferenc, Morocco. 1-11.

Singh, N. and Kumar, J. (2012). Urban Growth and Its Impact on Cityscape: A Geospatial Analysis of Rohtak City, India. J. Geogr. Inf. Syst. 4: 12-19.

Sinha, S., Sharma, L.K. and Nathawat, M.S. 2013. Integrated Geospatial Techniques for Land- use/Land-cover and Forest Mapping of Deciduous Munger Forests (India). UJERT. 3(2): 190-198.

Sishodia, R.P., Ray, R.L. and Singh, S.K., 2020. Applications of remote sensing in precision agriculture: A review. Remote Sens. 12(19): 1-31.

Tekle, K. and Hedlund, L. 2000. Land cover changes between 1958 and 1986 in Kalu District, southern Wello, Ethiopia. MRD. 20(1): 42-51.

Turner, M. G. and Ruscher, C.L. 2004. Change in landscape patterns in Georgia. USA. Land. Ecol. 1(4): 251-421.

Weiss, M.J. Jacob, F. and Duveiller, G.  2020. Remote sensing for agricultural applications: A meta-review. RSE. 263: 111-402.

Weng, Q. 2002. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. J. Environ. Manage. 64(3): 273-284.

Wulder, M. and Franklin, S. 2003. Remote sensing of forest environments: Concepts and     case studies. Kluwer Academic Publishers, Dordrecht, Boston, London, pp.3-12.

 

Cite this article

Bijosh, M.G. and Abraham J. 2024. The application of remote sensing and geographic information system techniques for the analysis of land use and land cover changes in Wayanad district of Kerala. J. Vet. Anim. Sci. 55 (3):516-523

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