An Analysis of Land Use and Land Cover Change Detection Using Geospatial Technology-A Case Study of Phalsoond Tehsil in Jaisalmer District, Rajasthan, India
Analysis of Land Use and Land Cover (LULC) change is significant indicators of environmental changes, resource utilization and sustainable development, especially in arid regions where land and water resources are very fragile. The present study has investigated the spatio-temporal analysis of LULC changes in Phascoond Tehsil of Jaisalmer District of Rajasthan, India from the year 2017 to 2024 using Remote sensing and Geographic Information System (GIS) techniques. To classify the study area, multi-temporal Sentinel-2 data with 10 m spatial resolution were provided by the Esri Sentinel-2 Land Cover Explorer, which was used to separate the area into five categories i.e. water bodies, agriculture land, built-up areas, bare ground and wasteland. LULC changes were quantified in terms of magnitude and direction using post-classification comparison and GIS-based change detection techniques. The findings show significant change in landscape over the year 2017 to 2024. Wasteland remained the dominant land-cover category but declined from 779.07 km² (78.28%) in 2017 to 726.86 km² (71.41%) in 2024. Agricultural area grew by 86.62 km² (+19.48% to 280.52 km²), adding 94.76 km² of wasteland. Gradual settlement and infrastructure development also resulted in an increase in built-up area from 3.89 km2 to 7.73 km2. The water bodies were small in spatial extent and slight shifts happened between bare ground and other land-cover classes. The results clearly show that the Sentinel-2 data and GIS-based analysis is useful in monitoring LULC dynamics in data-sparse arid regions. The present extent of agriculture and development has occurred at a time when there is a need to manage the land and groundwater resources sustainably, monitor environment, and plan land use with climate change in Phalsoond tehsil of Jaisalmer District in western Rajasthan.
Introduction
(LULC) Change in Phalsoond Tehsil
The text presents a study of Land Use and Land Cover (LULC) changes in Phalsoond Tehsil, Jaisalmer District, Rajasthan, using Remote Sensing and Geographic Information System (GIS) techniques for the period 2017–2024.
1. Background
Land is a fundamental natural resource supporting agriculture, settlements, infrastructure, economic activities, and ecosystems. Increasing population, urbanization, agricultural expansion, infrastructure development, and climate variability are putting increasing pressure on land resources. These pressures cause changes in land use and land cover, which can affect biodiversity, soil health, water resources, ecosystem services, and climate.
These issues are particularly important in arid regions such as western Rajasthan, where low and irregular rainfall, sandy soils, sparse vegetation, and human activities make the land highly vulnerable to degradation, erosion, and desertification.
2. Study Area
The study focuses on Phalsoond Tehsil in Jaisalmer District, Rajasthan, an arid region characterized by:
Sand dunes and sandy plains.
Sparse natural vegetation.
Limited agricultural land.
Small and isolated settlements.
Low and irregular rainfall.
Extreme summer and winter temperatures.
Limited irrigation facilities.
The tehsil covers approximately 1,015.26 km² and is experiencing changes associated with agriculture, irrigation, settlements, solar and wind energy infrastructure, and other development activities.
3. Problem Statement
Phalsoond Tehsil has experienced changes in LULC because of agricultural development, renewable-energy infrastructure, settlement growth, and other land-development activities. Combined with climate variability and the fragile desert ecosystem, these changes may affect environmental sustainability.
The study therefore aims to provide updated spatial information about these changes and answer three main questions:
What were the major LULC categories in 2017 and 2024?
What was the area and percentage of each LULC category?
How did LULC change spatially and temporally between 2017 and 2024?
4. Objectives
The main objectives are to:
Identify and classify LULC categories in Phalsoond Tehsil for 2017 and 2024.
Analyze the spatial and temporal changes in LULC.
Determine the direction and extent of land-use changes.
Use Remote Sensing and GIS for LULC change detection.
5. Methodology
The study uses geospatial techniques, particularly Remote Sensing and GIS.
The main data source is the Esri Sentinel-2 Land Cover Explorer, based on Sentinel-2 satellite imagery from the European Space Agency's Copernicus programme.
Important characteristics of the dataset include:
10-meter spatial resolution.
Free satellite data.
Preprocessed atmospheric and radiometric corrections.
Consistent annual land-cover classifications.
Data available from 2017 onward.
The study uses post-classification comparison to identify changes between 2017 and 2024. GIS tools are used to calculate land-cover areas, percentages, and transitions between different LULC classes.
6. LULC Classification in 2017
The 2017 analysis shows that wasteland dominated Phalsoond Tehsil.
LULC Class
Area (km²)
Percentage
Wasteland
779.07
78.28%
Agricultural Land
193.86
19.48%
Bare Ground
18.34
1.84%
Built-up Area
3.89
0.39%
Water Bodies
0.10
0.01%
Total
1,015.26
100%
The results indicate that:
Wasteland was the largest category, covering 78.28% of the tehsil.
Agricultural land was the second-largest category, covering 19.48%.
Bare ground represented 1.84%.
Built-up land accounted for only 0.39%.
Water bodies occupied just 0.01%.
The dominance of wasteland reflects the arid and desert characteristics of the region, while agricultural land is concentrated in areas with relatively better soil conditions and irrigation.
Conclusion
The spatio-temporal analysis of Land Use and Land Cover (LULC) was carried out in Phalsoond Tehsil, Jaisalmer District, Rajasthan over the period 2017-2024 upon the image of Sentinel-2 (10 m spatial resolution) with the help of Geographic Information System (GIS) analysis technique. The analysis reveals significant land changes that took place in the study area, both due to anthropogenic activities and to environmental conditions. The change that was most notable was the growth of agriculture area, slowly rising built up area and a decreasing wasteland. Minor changes in water bodies and transitions between bare ground also reflect dynamic land resources along this arid landscape. These changes are all indicative of an increasing intensity of intervention by humans, as well as changing patterns of land use in Phalsoond Tehsil.
The results highlight the need for geospatial technologies to offer an efficient and reliable method to monitor land use dynamics through space and time, in a scientifically robust way. Multi-temporal Sentinel-2 imagery combined with spatial GIS-based analyses allowed for accurate identification of land cover change, quantification of the extent of change, and visualization of land cover change, helping to evidence-based assess environmental change. From a planning point of view, this process of ‘wasteland’ changing to agriculture and built-up areas of land are representative of socio-economic developments and not just the landscapes of the past; however, these changes also raise planning concerns regarding development in a land that is environmentally sustainable. Conserving fragile ecosystems, efficiently managing water resources, soil protection action and applying climate proof methods for agriculture is sustainable land-use planning.
This synthesized LULC database has potential applications as a useful decision support tool for planners, policy makers, and resource managers to create strategies for sustainable land management and region development in western Rajasthan.
Nonetheless, the study may be limited in regard to several aspects. Remotely sensed images classification uncertainty and relatively limited temporal coverage (2017-2024) can affect the long-term land use trends. The application of higher-resolution satellite data, advanced machine learning classification algorithms, climate and hydrological data, and socio-economic indicators should include additional factors for better understanding the complexity of the drivers of land transformation, which will be beneficial for future research. The role of continuous monitoring of land resources is even more critical in an arid terrain like western Rajasthan where owing to the variability in climate and the rising human pressure, the landscape can change quickly. These comprehensive evaluations will enhance the management of the environment, fine-tune policies, and help to utilize land resources sustainably in the face of climate and development pressures.
References
[1] Anderson, J. R., Hardy, E. E., Roach, J. T., & Witmer, R. E. (1976). A land use and land cover classification system for use with remote sensor data. U.S. Geological Survey Professional Paper 964. https://doi.org/https://doi.org/10.3133/pp964
[2] Burley, T. M. (1961). Land use or land utilization. The Professional Geographer, 13(6), 18-20.
[3] Campell, J. B. (1983). Mapping the Land: Aerial Imagery for Land Use Information. Association of American Geographers, Washington, D. C.
[4] Clawson, M., & Stewart, C. L. (1965). Land use information. A critical survey of U.S. statistics including. Baltimore: The Johns Hopkins Press for Resources for the Future.
[5] Duraisamy, V., Bendapudi, R., & Jadhav, A. (2018). Identifying hotspots in land use land cover change and the drivers in a semi-arid region of India. Environ Monit Assess, 190(535). https://doi.org/https://doi.org/10.1007/s10661-018-6919-5
[6] Fajardo, S. T., Magsanoc, M. K., Gloria, J. R., Cruz, S. S., Gonzales, J. K., Policarpio, J. F., & Babalcon, R. V. (2026). Assessment of Land Use and Land Cover Change in Talavera, Nueva Ecija from 2020 to 2025 Using GIS Mapping. Engineering and Technology Journal, 11(5), 10095-10102. https://doi.org/10.47191/etj/v11i05.45
[7] Foley, J. A., Defries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter, S. R., . . . Monfred, C. (2005). Global consequences of land use. Science, 309,(5734), 570-574. https://doi.org/DOI: 10.1126/science.1111772
[8] Green, K., Kempka, D., & Lackey, L. (1994). Using remote sensing to detect and monitoring land-cover and land-use change. Photogrammetric Engineering and Remote Sensing, 60, 331–337.
[9] Hussain, M., Chen, D., Cheng, A., Wei, H., & Stanley, D. (2013). Change detectionfromremotelysensedimages:Frompixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, 91-106. https://doi.org/https://doi.org/10.1016/j.isprsjprs.2013.03.006
[10] Lambin, E. F., & Meyfroidt, P. (2010). Land use transitions: Socio-ecological feedback versus socio-economic change. Land Use Policy 27, 27, 108-118.
[11] Land Cover Explorer. (n.d.). Retrieved from Esri | Sentinel-2 Land Cover Explorer: https://livingatlas.arcgis.com/landcoverexplorer
[12] Phiri, D., Simwanda, M., Salekin, S., R., N. V., Murayama, Y., & Ranagalage, M. (2020). Sentinel-2 Data for Land Cover/Use Mapping: A Review. Remote Sensing, 12(2291), 1-35. https://doi.org/https://doi.org/10.3390/rs12142291
[13] Roy, P. S., Roy, A., Joshi, P. K., Kale, M. P., Srivastava, V. K., Srivastava, S. K., . . . Palchowdhuri, Y. (2015). Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India. Remote Sensing, 7(3), 2401-2430. https://doi.org/10.3390/rs70302401
[14] Singh, A. (1989). Review Article Digital change detection techniques using remotely-sensed data. International Journal of Remote Sensing, 10(06), 989-1003. https://doi.org/https://doi.org/10.1080/01431168908903939
[15] Turner Ii, B. L., Skole, D., Sanderson, S., Fischer, G., Fresco, L., & Leemans, R. (Eds.). (1995). Land-use and land-cover change. Science/Research plan. Stockholm: Royal Swedish Academy of Science, IGBN.
[16] Wang, Y., Sun, Y., Cao, X., Wang, Y., Zhang, W., & Cheng, X. (2023). A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 206, 311-334. https://doi.org/https://doi.org/10.1016/j.isprsjprs.2023.11.014
[17] Yadav, S. C. (2022). (2022). A spatio-temporal analysis of land use pattern and land use changes in Rajasthan. Sustainability, Agri, Food and Environmental Research, 11(X). https://doi.org/https://doi.org/10.7770/safer-V11N1-art2350
[18] Yadav, S. K., & Nath, S. (2018). Probability estimation and rainfall variability analysis for Barmer and Jaisalmer districts of Rajasthan, India. Journal of Pharmacognosy and Phytochemistry, 7(4), 1273–1277.
[19] Zhang, X., Liu, L., Zhao, T., Zhang, W., Guan, L., Bai, M., & Chen, X. (2025). GLC_FCS10: a global 10m land-cover dataset with a fine classification system from Sentinel-1 and Sentinel-2 time-series data in Google Earth Engine. Earth System Science Data, 17, 4039–4062. https://doi.org/https://doi.org/10.5194/essd-17-4039-2025