Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India

Anshu Jain; Shailendra Jain

doi:doi:10.11648/j.ajoe.20260101.14

Research Article |

| Peer-Reviewed

Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India

Anshu Jain

, Shailendra Jain^*

Published in American Journal of Ecology (Volume 1, Issue 1)

Received: 9 February 2026 Accepted: 9 October 2026 Published: 28 October 2026

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

Rapid urbanization is reshaping land use and land cover (LULC) across many Indian cities and complicates sustainable urban planning. Jaipur, one of the fastest-growing cities of Rajasthan, has expanded considerably over recent decades, altering both its natural and built environments. This study examines the spatio-temporal pattern of LULC change in the Jaipur urbanizable area using multi-temporal Landsat imagery. Images from 2000, 2009 and 2017 were classified with a supervised Maximum Likelihood algorithm into six classes: built-up area, bare soil/fallow land, agricultural cropped land, natural vegetation, water body, and bare rock/hill surface. Change was then quantified through post-classification comparison, change matrices and dynamic degree. Between 2000 and 2017, built-up area more than doubled (+111.86%) and bare soil/fallow land rose by 45.48%, while agricultural cropped land and natural vegetation fell by 57.65% and 32.41%, respectively, pointing to rapid urban sprawl and land transformation. Classification accuracy was assessed using confusion matrices, overall accuracy and the Kappa statistic based on GPS field data. The results underline the need for sustainable urban development strategies and effective land management policies to curb the environmental impacts of unregulated growth in Jaipur. The study shows that remote sensing combined with GIS is a dependable means of monitoring urban LULC change and offers useful guidance for planners and policymakers.

Published in	American Journal of Ecology (Volume 1, Issue 1)
DOI	10.11648/j.ajoe.20260101.14
Page(s)	30-39
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

Land Use/Land Cover, Urbanization, Jaipur, Remote Sensing, GIS, Change Detection, Maximum Likelihood Classification, Urban Sprawl, Sustainable Development

References

[1]	Das, S., & Sarkar, R. (2023). Spatiotemporal change detection analysis of land cover and land use using multi-temporal remote sensed imagery and landscape metrics: A sub-catchment level case study of the Bhagirathi-Hugli River, West Bengal, India. IOP Conference Series: Earth and Environmental Science, 1164(1), 012003. https://doi.org/10.1088/1755-1315/1164/1/012003
[2]	Abdeljawad, N., Adedokun, V., & Nagy, I. (2023). Environmental impacts of urban sprawl using remote sensing indices: A case study of Amman City—the capital of Jordan. GeoJournal of Tourism and Geosites, 46(1), 304–314. https://doi.org/10.30892/gtg.46134-1028
[3]	Parvathi, S. L., Asok, S. V., Rajani, K., & Reshma, R. S. (2017). Urban landscape analysis using remote sensing and GIS in Kollam district. International Journal for Research in Applied Science and Engineering Technology, 5(10), 879-886.
[4]	Li, X., Wang, Y., Li, J., & Lei, B. (2016). Physical and socioeconomic driving forces of land-use and land-cover changes: A Case Study of Wuhan City, China. Discrete Dynamics in Nature and Society, 2016. https://doi.org/10.1155/2016/8061069
[5]	Phyu, A. P., Htun, H. H., Eain, T. O., & Oo, H. N. (2018). Analysis of urban changes using geographic information system (GIS): Case Area of Pyin Oo Lwin Township (Myanmar). Journal of Pharmacognosy and Phytochemistry, 7(1S), 676-680.
[6]	Rahimi, A. (2016). A methodological approach to urban land-use change modeling using infill development pattern—a case study in Tabriz, Iran. Ecological Processes, 5, 1-15. https://doi.org/10.1186/s13717-016-0044-6
[7]	Rawat, J. S., & Kumar, M. (2015). Monitoring land use/cover change using remote sensing and GIS techniques: A case study of Hawalbagh block, district Almora, Uttarakhand, India. Egyptian Journal of Remote Sensing and Space Science, 18(1), 77–84. https://doi.org/10.1016/j.ejrs.2015.02.002
[8]	Prasad, S., Singh, R. B., & Pandey, B. W. (2021). Spatio-temporal analysis of land use and land cover in Delhi-NCR using satellite data. Journal of Global Resources, 7(2), 23–31. https://doi.org/10.46587/JGR.2021.v07i02.003
[9]	Singh, R. P., Ajay, K., & Kumar, P. G. (2014). Assessment of Urban Sprawl and its Impact on Natural Environment in and around Jaipur city, Rajsthan, India. Int Res J Earth Sci, 2, 1-6.
[10]	Yirsaw, E., Wu, W., Temesgen, H., & Bekele, B. (2017). Socioeconomic drivers of spatio-temporal land use/land cover changes in a rapidly urbanizing area of China, the Su-Xi-Chang region. Applied Ecology & Environmental Research, 15(4).
[11]	Rukshar, R., Vyas, A. D., & Bhatnagar, N. (2023). Assessing the deteriorating water quality in wards of Jaipur city through GIS interpolation. AQUA-Water Infrastructure, Ecosystems and Society, 72(4), 425-437. https://doi.org/10.2166/aqua.2023.090
[12]	Ning, X., Zhang, H., Shao, Z., Huang, X., Wang, H., Zhang, R., & Hao, M. (2023). Sustainability Evaluation of Chinese Capital Cities Based on Urban Geographic Environment Index. Remote Sensing, 15(8), 1966. https://doi.org/10.3390/rs15081966
[13]	Alemu, B., Garedew, E., Eshetu, Z., & Kassa, H. (2015). Land use and land cover changes and associated driving forces in north western lowlands of Ethiopia. International Research Journal of Agricultural Science and Soil Science, 5(1), 28–44. https://doi.org/10.14303/irjas.2014.063
[14]	Chong, C. H. S. (2017). Comparison of Spatial Data Types for Urban Sprawl Analysis Using Shannon's Entropy (Doctoral dissertation, University of Southern California).
[15]	Cheruto et al. (2016). Assessment of Land Use and Land Cover Change Using GIS and Remote Sensing Techniques: A Case Study of Makueni County, Kenya. J Remote Sensing & GIS, 5(4). https://doi.org/10.4172/2469-4134.1000175
[16]	Das, T., Chakraborty, S., & Samanta, K. (2016). Urban sprawl and urban growth detection analysis: A comparative study of Kolkata municipal corporation and Haora municipal corporation. International journal of Geomatics and Geosciences, 7(1), 82-92.
[17]	El Garouani, A., Mulla, D. J., El Garouani, S., & Knight, J. (2017). Analysis of urban growth and sprawl from remote sensing data: Case of Fez, Morocco. International Journal of Sustainable Built Environment, 6(1), 160-169. https://doi.org/10.1016/j.ijsbe.2017.02.003
[18]	Islam, K., Jashimuddin, M., Nath, B., & Nath, T. K. (2018). Land use classification and change detection by using multi-temporal remotely sensed imagery: The case of Chunati wildlife sanctuary, Bangladesh. The Egyptian Journal of Remote Sensing and Space Science, 21(1), 37-47. https://doi.org/10.1016/j.ejrs.2016.12.005
[19]	Jain, M., Dimri, A. P., & Niyogi, D. (2016). Urban sprawl patterns and processes in Delhi from 1977 to 2014 based on remote sensing and spatial metrics approaches. Earth Interactions, 20(14), 1-29. https://doi.org/10.1175/EI-D-15-0040.1
[20]	Mishra, A., & Arya, D. S. (2023). Assessment of land-use land-cover dynamics and urban heat island effect of Dehradun city, North India: a remote sensing approach. Environment, Development and Sustainability, 1-27. https://doi.org/10.1007/s10668-023-03558-6
[21]	Khadke, P. A., Kharat, R. U., & Kamble, K. R. (2019). Changing Occupational Structure in Aurangabad City. International Journal of Research in Engineering, IT and Social Sciences, 2250-0588.
[22]	Kumar, S., Ghosh, S., Hooda, R. S., & Singh, S. (2019). Monitoring and prediction of land use land cover changes and its impact on land surface temperature in the central part of hisar district, Haryana under semi-arid zone of India. Journal of Landscape Ecology, 12(3), 117-140.
[23]	Khan, R., & Jhariya, D. C. (2016). Land use land cover change detection using remote sensing and geographic information system in Raipur Municipal Corporation Area, Chhattisgarh. Jour. Geo Science and Geo Informatics, 3(1), 1-4.
[24]	Singh, P., Gupta, A., & Singh, M. (2014). Hydrological inferences from watershed analysis for water resource management using remote sensing and GIS techniques. The Egyptian Journal of Remote Sensing and Space Science, 17(2), 111-121. https://doi.org/10.1016/j.ejrs.2014.09.003
[25]	Ghazal, N. K., & Hussein, A. K. (2017). Accuracy Assessment of Land Use and Land Cover Classification of AL-Najaf Province, Iraq. Journal of Kufa-physics, 9(1), 72-79.
[26]	Oakleaf, J. R., Kennedy, C. M., Baruch-Mordo, S., Gerber, J. S., West, P. C., Johnson, J. A., & Kiesecker, J. (2019). Mapping global development potential for renewable energy, fossil fuels, mining and agriculture sectors. Scientific data, 6(1), 101. https://doi.org/10.1038/s41597-019-0084-8
[27]	Chavan, S. B., Newaj, R., Rizvi, R. H., Ajit, Prasad, R., Alam, B., & Tripathi, D. (2021). Reduction of global warming potential vis-à-vis greenhouse gases through traditional agroforestry systems in Rajasthan, India. Environment, Development and Sustainability, 23, 4573-4593. https://doi.org/10.1007/s10668-020-00788-w

Cite This Article

Plain Text BibTeX RIS

APA Style

Jain, A., Jain, S. (2026). Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India. American Journal of Ecology, 1(1), 30-39. https://doi.org/10.11648/j.ajoe.20260101.14

Copy | Download

ACS Style

Jain, A.; Jain, S. Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India. Am. J. Ecol. 2026, 1(1), 30-39. doi: 10.11648/j.ajoe.20260101.14

Copy | Download

AMA Style

Jain A, Jain S. Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India. Am J Ecol. 2026;1(1):30-39. doi: 10.11648/j.ajoe.20260101.14

Copy | Download

@article{10.11648/j.ajoe.20260101.14,
  author = {Anshu Jain and Shailendra Jain},
  title = {Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India},
  journal = {American Journal of Ecology},
  volume = {1},
  number = {1},
  pages = {30-39},
  doi = {10.11648/j.ajoe.20260101.14},
  url = {https://doi.org/10.11648/j.ajoe.20260101.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajoe.20260101.14},
  abstract = {Rapid urbanization is reshaping land use and land cover (LULC) across many Indian cities and complicates sustainable urban planning. Jaipur, one of the fastest-growing cities of Rajasthan, has expanded considerably over recent decades, altering both its natural and built environments. This study examines the spatio-temporal pattern of LULC change in the Jaipur urbanizable area using multi-temporal Landsat imagery. Images from 2000, 2009 and 2017 were classified with a supervised Maximum Likelihood algorithm into six classes: built-up area, bare soil/fallow land, agricultural cropped land, natural vegetation, water body, and bare rock/hill surface. Change was then quantified through post-classification comparison, change matrices and dynamic degree. Between 2000 and 2017, built-up area more than doubled (+111.86%) and bare soil/fallow land rose by 45.48%, while agricultural cropped land and natural vegetation fell by 57.65% and 32.41%, respectively, pointing to rapid urban sprawl and land transformation. Classification accuracy was assessed using confusion matrices, overall accuracy and the Kappa statistic based on GPS field data. The results underline the need for sustainable urban development strategies and effective land management policies to curb the environmental impacts of unregulated growth in Jaipur. The study shows that remote sensing combined with GIS is a dependable means of monitoring urban LULC change and offers useful guidance for planners and policymakers.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India
AU  - Anshu Jain
AU  - Shailendra Jain
Y1  - 2026/10/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ajoe.20260101.14
DO  - 10.11648/j.ajoe.20260101.14
T2  - American Journal of Ecology
JF  - American Journal of Ecology
JO  - American Journal of Ecology
SP  - 30
EP  - 39
PB  - Science Publishing Group
UR  - https://doi.org/10.11648/j.ajoe.20260101.14
AB  - Rapid urbanization is reshaping land use and land cover (LULC) across many Indian cities and complicates sustainable urban planning. Jaipur, one of the fastest-growing cities of Rajasthan, has expanded considerably over recent decades, altering both its natural and built environments. This study examines the spatio-temporal pattern of LULC change in the Jaipur urbanizable area using multi-temporal Landsat imagery. Images from 2000, 2009 and 2017 were classified with a supervised Maximum Likelihood algorithm into six classes: built-up area, bare soil/fallow land, agricultural cropped land, natural vegetation, water body, and bare rock/hill surface. Change was then quantified through post-classification comparison, change matrices and dynamic degree. Between 2000 and 2017, built-up area more than doubled (+111.86%) and bare soil/fallow land rose by 45.48%, while agricultural cropped land and natural vegetation fell by 57.65% and 32.41%, respectively, pointing to rapid urban sprawl and land transformation. Classification accuracy was assessed using confusion matrices, overall accuracy and the Kappa statistic based on GPS field data. The results underline the need for sustainable urban development strategies and effective land management policies to curb the environmental impacts of unregulated growth in Jaipur. The study shows that remote sensing combined with GIS is a dependable means of monitoring urban LULC change and offers useful guidance for planners and policymakers.
VL  - 1
IS  - 1
ER  -

Copy | Download

Author Information

Anshu Jain

Department of Physics, Eklavya University, Damoh, India

Contact Email

http://orcid.org/0009-0008-4557-1233
Shailendra Jain

Department of Physics, Eklavya University, Damoh, India

Contact Email

http://orcid.org/0009-0002-9415-5144

Download PDF

Submit an Article

Sections

Plain Text BibTeX RIS

APA Style

Jain, A., Jain, S. (2026). Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India. American Journal of Ecology, 1(1), 30-39. https://doi.org/10.11648/j.ajoe.20260101.14

Copy | Download

ACS Style

Jain, A.; Jain, S. Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India. Am. J. Ecol. 2026, 1(1), 30-39. doi: 10.11648/j.ajoe.20260101.14

Copy | Download

AMA Style

Jain A, Jain S. Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India. Am J Ecol. 2026;1(1):30-39. doi: 10.11648/j.ajoe.20260101.14

Copy | Download

@article{10.11648/j.ajoe.20260101.14,
  author = {Anshu Jain and Shailendra Jain},
  title = {Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India},
  journal = {American Journal of Ecology},
  volume = {1},
  number = {1},
  pages = {30-39},
  doi = {10.11648/j.ajoe.20260101.14},
  url = {https://doi.org/10.11648/j.ajoe.20260101.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajoe.20260101.14},
  abstract = {Rapid urbanization is reshaping land use and land cover (LULC) across many Indian cities and complicates sustainable urban planning. Jaipur, one of the fastest-growing cities of Rajasthan, has expanded considerably over recent decades, altering both its natural and built environments. This study examines the spatio-temporal pattern of LULC change in the Jaipur urbanizable area using multi-temporal Landsat imagery. Images from 2000, 2009 and 2017 were classified with a supervised Maximum Likelihood algorithm into six classes: built-up area, bare soil/fallow land, agricultural cropped land, natural vegetation, water body, and bare rock/hill surface. Change was then quantified through post-classification comparison, change matrices and dynamic degree. Between 2000 and 2017, built-up area more than doubled (+111.86%) and bare soil/fallow land rose by 45.48%, while agricultural cropped land and natural vegetation fell by 57.65% and 32.41%, respectively, pointing to rapid urban sprawl and land transformation. Classification accuracy was assessed using confusion matrices, overall accuracy and the Kappa statistic based on GPS field data. The results underline the need for sustainable urban development strategies and effective land management policies to curb the environmental impacts of unregulated growth in Jaipur. The study shows that remote sensing combined with GIS is a dependable means of monitoring urban LULC change and offers useful guidance for planners and policymakers.},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - Land Use/Land Cover Change Detection Analysis Using Remote Sensing and GIS of Jaipur District, India
AU  - Anshu Jain
AU  - Shailendra Jain
Y1  - 2026/10/28
PY  - 2026
N1  - https://doi.org/10.11648/j.ajoe.20260101.14
DO  - 10.11648/j.ajoe.20260101.14
T2  - American Journal of Ecology
JF  - American Journal of Ecology
JO  - American Journal of Ecology
SP  - 30
EP  - 39
PB  - Science Publishing Group
UR  - https://doi.org/10.11648/j.ajoe.20260101.14
AB  - Rapid urbanization is reshaping land use and land cover (LULC) across many Indian cities and complicates sustainable urban planning. Jaipur, one of the fastest-growing cities of Rajasthan, has expanded considerably over recent decades, altering both its natural and built environments. This study examines the spatio-temporal pattern of LULC change in the Jaipur urbanizable area using multi-temporal Landsat imagery. Images from 2000, 2009 and 2017 were classified with a supervised Maximum Likelihood algorithm into six classes: built-up area, bare soil/fallow land, agricultural cropped land, natural vegetation, water body, and bare rock/hill surface. Change was then quantified through post-classification comparison, change matrices and dynamic degree. Between 2000 and 2017, built-up area more than doubled (+111.86%) and bare soil/fallow land rose by 45.48%, while agricultural cropped land and natural vegetation fell by 57.65% and 32.41%, respectively, pointing to rapid urban sprawl and land transformation. Classification accuracy was assessed using confusion matrices, overall accuracy and the Kappa statistic based on GPS field data. The results underline the need for sustainable urban development strategies and effective land management policies to curb the environmental impacts of unregulated growth in Jaipur. The study shows that remote sensing combined with GIS is a dependable means of monitoring urban LULC change and offers useful guidance for planners and policymakers.
VL  - 1
IS  - 1
ER  -

Copy | Download