Assessment of Land Use and Land Cover Change: A Comparative Study of Tribal and non-Tribal District in Gujarat
Keywords:
Land use land cover, supervised classification technique, Remote sensing, Geographical information System, Dahod district, Gandhinagar districtAbstract
To support development activities in a given area, it is necessary to have a thorough grasp of the land use and land cover because these elements offer important information about the topography of that area. By analyzing satellite imagery using remote sensing and Geographic Information System (GIS) techniques, this study explores the land use, land cover, and changes in the districts of Dahod and Gandhinagar. The study has used a supervised classification technique to assess the changes in land use and land cover between 2016 and 2022. In the Gandhinagar district, as more people purchase property for residential building, urbanization is increasing, leading to a decrease in agricultural and wooded regions and an increase in wasteland. In contrast, the majority of the land in the Dahod district is unsuited for agriculture due to its mountainous and flat environment. There is hence an abundance of wasteland in the Dahod district. There are currently attempts to encourage farming on these hills and plateaus in Dahod district, which will reduce the amount of wasteland.
Downloads
References
Qian, J., Zhou, Q., & Hou, Q. (2007). Comparison of pixel-based and object-oriented classification methods for extracting built-up areas in arid zone. In ISPRS workshop on updating Geo-spatial databases with imagery & the 5th ISPRS workshop on DMGISs (Vol. 8, pp. 163-171). China: Urumchi, Xingjizng.
Kaul, H. A., & Sopan, I. (2012). Land use land cover classification and change detection using high resolution temporal satellite data. Journal of Environment, 1(4), 146-152.
Aydinoglu, A. C., & Gungor, O. (2010). A novel land cover/use data model for GIS and remote sensing applications in Turkey. Italian Journal of Remote Sensing, 42(2), 27-41.
Loveland, T.; Sohl, T.; Stehman, S.; Gallant, A.; Sayler, K.; Napton, D. A strategy for estimating the rates of recent United States land cover changes. Photogramm. Eng. Remote Sens. 2002, 68, 1091–1099.
Lu, D.; Mausel, P.; Brondizio, E.; Moran, E. Change detection techniques. Int. J. Remote Sens. 2003, 25, 2365–2401.
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.
Setegn, S. G., Srinivasan, R., Dargahi, B., & Melesse, A. M. (2009). Spatial delineation of soil erosion vulnerability in the Lake Tana Basin, Ethiopia. Hydrological Processes: An International Journal, 23, 3738–- 3750.
Yalew, S. G., Mul, M. L., Van Griensven, A., Teferi, E., Priess, J., Schweitzer, C., & Van Der Zaag, P. (2016). Land-use change modelling in the Upper Blue Nile Basin. Environments, 3(4), 21.
Ahmad, S. (2014). Land use change detection using remote sensing and artificial neural network: Application to Birjand, Iran. Computational Ecology and Software, 4, 276.
Chakilu, G., & Moges, M. (2017). Assessing the land use/cover dynamics and its impact on the low flow of Gumara Watershed, Upper Blue Nile Basin, Ethiopia. Hydrol Current Res, 7, 2.
Hegazy, I. R., & Kaloop, M. R. (2015). Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1), 117–124.
Sewnet, A. (2015). Land use/cover change at infraz Watershed, Northwestren Ethiopia. Journal of Landscape Ecology, 8(1), 69–83.
Antrop, M., 1998.Landscapechange: planorchaos? Landsc.UrbanPlan.41,155–161.
Bürgi, M., Russell, E.W.B., 2001. Integrative methods to study landscape changes. Land Use Policy 18, 9–16.
Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., Lambin, E., 2004. Digital change detection methods in ecosystem monitoring: a review. Int. J. Remote Sens. 25, 1565–1596.
Verboom, J., Alkemade, R., Klijn, J., Metzger, M.J., Reijnen, R., 2007. Combining biodiversity modeling with political and economic development scenarios for 25 EU countries. Ecological Economics 62, 267–276.
Rogan J., Chen D. (2004) - Remote sensing technology for mapping and monitoring land cover and land-use change. Progress in Planning, 61 (4): 301-325.
Shanwad, U.K., Patil V.C., Honne Gowda H. and Dasog G.S. (2008). Application of Remote Sensing Technology for Impact Assessment of Watershed Management Programme. J. Indian Soc. Remote Sens, 36, 375–386.
Dutta, D., Narasimhan S., Sharma J.R. and Adiga S. (2003) Remote Sensing Based Rapid Watershed Health Appraisal - A Case Study of NWDPRA Watershed of Rajasthan. Water resources: Map India Conference.
Foody, G.M. (2002). Status of Land Cover Classification Accuracy Assessment. Remote Sensing of Environment, 80, 185-201.
Chowdary V.M., Paul S., Srinivas Kumar T., Sudhakar S. and Adiga S. (2001). Remote Sensing and GIS Approach for Watershed Monitoring and Evaluation: A case Study of Orissa State, India. In: 22nd Asian Conference on Remote Sensing, Singapore, 5-9 November.
Csaplovics E. (1998). High Resolution space imagery for regional environmental monitoring -status quo and future trends. International Archives of Photogrammetry and Remote Sensing, 32(7), 211-216.
Lausch, A., Herzog, F., 2002. Applicability of landscape metrics for the monitoring of landscape change: issues of scale, resolution and interpretability. Ecol. Indic. 2, 3–15.
Vuorela, N., Alho, P., Kalliola, R., 2002. Systematic assessment of maps as source information in landscape change research. Landsc. Res. 27, 141–166.
Usman B (2013) Satellite imagery land cover classification using K means clustering algorithm: computer vision for environmental information extraction. Elixir Journal of Computer Science and Eng: 18671–18675
Yuan, F., Sawaya, K. E., Loeffelholz, B. C., & Bauer, M. E. (2005). Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing. Remote Sensing of Environment, 98(2–3), 317–328.
Chen, X., Vierling, L., & Deering, D. (2005). A simple and effective radiometric correction method to improve landscape change detection across sensors and across time. Remote Sensing of Environment, 98(1), 63–79.
Jensen, J. R. (1996). Introductory digital image processing: A remote sensing perspective. Prentice-Hall Inc.
Fonji SF, Taff GN (2014) Using satellite data to monitor land-use land cover change in North-eastern Latvia. Springerplus 3(1):61.
Li M, Zang S, Zhang B, Li S, Wu C (2014) A review of remote sensing image classification techniques: the role of spatio-contextual information. European Journal of Remote Sensing 47(1):389–411.
Yang Q, Zhang H, Peng W, Lan Y, Luo S, Shao J, Chen D, Wang G (2018) Assessing climate impact on forest cover in areas undergoing substantial land cover change using Landsat imagery. Sci Total Environ 659:732–745.
Restrepo AMC et al (2017) Land cover change during a period of extensive landscape restoration in Ningxia Hui Autonomous Region, China. Sci Total Environ 598:669–679.
El Jazouli A et al (2019) Remote sensing and GIS techniques for prediction of land use land cover change effects on soil erosion in the high basin of the Oum Er Rbia River (Morocco). Remote Sensing Applications: Society and Environment 13:361–374.
Birhane E, Ashfare H, Fenta AA, Hishe H, Gebremedhin MA, G. wahed H, Solomon N (2019) Land use land cover changes along topographic gradients in Hugumburda national forest priority area,Northern Ethiopia. Remote Sensing Applications: Society and Environment 13:61–68.
Bagan H, Li H, Yang Y, Takeuchi W, Yamagata Y (2018) Sensitivity of the subspace method for land cover classification. Egypt J Remote Sens Space Sci 21(3):383–389.
Bakr N, Afifi AA (2019) Quantifying land use/land cover change and its potential impact on rice production in the Northern Nile Delta, Egypt. Remote Sensing Applications: Society and Environment 13(2019):348–360.
Kabisch N, Selsam P, Kirsten T, Lausch A, Bumberger J (2019) A multi sensor and multi-temporal remote sensing approach to detect land cover change dynamics in heterogeneous urban landscapes. Ecol Indic 99:273–282.
Directorate of Census Operations (2011), District Census Handbook, Dahod,Gujarat.
Directorate of Census Operations (2011), Gujarat District Census Handbook, Gandhinagar,Gujarat.
Office of the Principal Chief Conservator of the Forests & Head of the Forest Force, Forest Department, Gujarat Forest Statistics-2018-19, Gujarat.
Websites: https://earthexplorer.usgs.gov/
Downloads
Published
Issue
Section
License
Copyright (c) 2025 International Journal of Scientific Research in Science and Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
https://creativecommons.org/licenses/by/4.0
