Share:


Modification of new built-up index to precisely extract and identify changes in the built-up area: a case study of Punjab State of India

    Suraj Shaikh Affiliation
    ; Rakesh Paliwal Affiliation
    ; Abhijit Patil   Affiliation
    ; Sachin Panhalkar Affiliation
    ; Masilamani Palanisamy Affiliation
DOI: https://doi.org/10.3846/gac.2023.13523

Abstract

Remote sensing is very useful for mapping and managing earth resources. The application of this technique has been widely used and proven useful in assessing temporal changes. The indices are used to distinguish different complex land covers, but there are still difficulties with distinguishing specific land covers. Therefore, the prime aim of this present investigation is to identify the changes in the built-up area using a modified new built-up index (MNBUI). The MNBUI is developed using the reference of four earlier developed indices. The built-up area of Punjab state is extracted from 2013 and 2017 year remote sensing satellite data using MNBUI. The result shows MNBUI is more accurate in terms of built-up area extraction as compared to the other two indices – New Built-up Index and built-up index models. The accuracy assessment is carried out to evaluate the accuracy of MNBUI with a random sampling technique. The mapping accuracy reported is 95% and 0.9333 in terms of overall accuracy (OA) and kappa coefficient (π) respectively.

Keyword : MNBUI, built-up area, remote sensing, satellite data, Punjab State

How to Cite
Shaikh, S., Paliwal, R., Patil, A., Panhalkar, S., & Palanisamy, M. (2023). Modification of new built-up index to precisely extract and identify changes in the built-up area: a case study of Punjab State of India. Geodesy and Cartography, 49(1), 19–24. https://doi.org/10.3846/gac.2023.13523
Published in Issue
Mar 6, 2023
Abstract Views
277
PDF Downloads
326
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

As-syakur, A. R., Adnyana, I. W. S., Arthana, I. W., & Nuarsa, I. W. (2012). Enhanced Built-up Land and Bareness Index (EBBI) for mapping built-up and bare land in an urban area. Remote Sensing, 4(10), 2957–2970. https://doi.org/10.3390/rs4102957

Bhuvan. (2018). Bhuvan-Indian geo-platform of ISRO. https://bhuvan.nrsc.gov.in

Census of India. (2011). https://censusindia.gov.in/2011census/dchb/DCHB.html

Chen, J., Gong, P., He, C., Pu, R., & Shi, P. (2003). Land use/cover change detection using improved change vector analysis. Photogrammetric Engineering and Remote Sensing, 4, 369–379. https://doi.org/10.14358/PERS.69.4.369

Hussain, M., Chen, D. M., Cheng, A., Wei, H., & Stanley, D. (2013). Change detection from remotely sensed images: From pixel-based to object-based approaches. ISPRS Journal of Photogrammetry and Remote Sensing, 80, 91–106. https://doi.org/10.1016/j.isprsjprs.2013.03.006

Jensen, J. R. (2005). Introductory digital image processing: A remote sensing perspective (3rd ed.). Prentice Hall.

Jiang, Z., Huete, A., Didan, K., & Miura, T. (2008). Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment, 112(10), 3833–3845. https://doi.org/10.1016/j.rse.2008.06.006

Kawamura, M., Jayamana, S., & Tsujiko, Y. (1996). Relation between social and environmental conditions in Colombo Sri Lanka and the urban index estimated by satellite remote sensing data. International Archives of the Photogrammetry and Remtesensing, 31, 321–326.

Sinha, P., Verma, N. K., & Ayele, E. (2016). Urban built-up area extraction and change detection of Adama Municipal Area using time-series Landsat images. International Journal of Advanced Remote Sensing and GIS, 5(8), 1886–1895.

Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H., & Sorooshian, S. (1994). Modified soil adjusted vegetation index (MSAVI). Remote Sensing of Environment, 48(2), 119–126. https://doi.org/10.1016/0034-4257(94)90134-1

Rajan, K., & Shibasaki, R. (2001, November). A GIS based integrated land use/cover change model to study agricultural and urban land use changes. In 22nd Asian Conference on Remote Sensing, Singapore.

Xu, H. (2005). A study on information extraction of water body with the Modified Normalized Difference Water Index (MNDWI). Journal of Remote Sensing, 9(5), 511–517.

Xu, H. (2008). A new index for delineating built-up land features in satellite imagery. International Journal of Remote Sensing, 29(14), 4269–4276. https://doi.org/10.1080/01431160802039957

Zha, Y., Gao, J., & Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24(3), 583–594. https://doi.org/10.1080/01431160304987

Zhao, H. M., & Chen, X. L. (2005, July). Use of normalized difference bareness index in quickly mapping bare areas from TM/ETM+. In Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium (Vol. 3, pp. 1666–1668), Seoul, Korea. https://doi.org/10.1109/IGARSS.2005.1526319