STUDY ON SPATIAL-TEMPORAL URBAN GROWTH AND LAND CONSUMPTION PATTERNS OF THIMPHU, BHUTAN USING MULTI-TEMPORAL SATELLITE IMAGES

Authors

  • Indra Bahadur Chhetri

DOI:

https://doi.org/10.54417/jaetm.v3i1.107

Keywords:

Land Consumption Pattern (LCP), out-migration, landsat images, Thimphu city, urban growth

Abstract

Like many other countries, Bhutan is also experiencing rapid trend of urban expansion mainly due to out-migration from rural to urban areas particularly in capital city, Thimphu. This study focuses on the dynamics of urban expansion, evaluating urban growth and land consumption pattern of Thimphu, using multi-temporal Landsat images during the year 1990-2018. The main aim of the study is to perform supervised classification to classify built-up area, green area, bare-land and others (water bodies, agricultural lands, etc…) and to perform a change analysis from the viewpoint of increasing the built-up areas (man-made structures) and decreasing in green and open spaces. Moreover, the study also highlights how has the land consumption pattern of the region changed over the years. The findings of the study confirmed that the Thimphu city has its built-up areas increased during 1990-2018 with net growth of 4.63 km2 (106.19%). The urban area was 4.36 km2 in 1990, 5.80 km2 in 2000 (33.03% growth), which increased to 7.24 km2 in 2013 (24.83% growth) and 8.99 km2 (24.17% growth) in 2018. The study also showed that there is decrease in land consumption between 1990-2018. In 1990, land consumption was 155.65 m2 per person which decreased to 78.48 m2 per person in 2018. This decrease in land consumption indicate that the city is experiencing increased densification between the years 1990-2018. The classifier performance evaluation was done using overall accuracy and kappa coefficient. The classification produced an overall accuracies ranging between 78.74% to 90.46 % and overall kappa statistics between 0.72 to 0.87 for all years indicating classification accuracy of moderate to substantial accuracy.

Author Biography

Indra Bahadur Chhetri

Lecturer

Department of Civil and Surveying Engineering

Jigme Namgyel Engineering College, Royal University of Bhutan

References

L. Sharma, P. C. Pandey, and M. S. Nathawat, “Assessment of land consumption rate with urban dynamics change using geospatial techniques,” J. Land Use Sci., vol. 7, no. 2, pp. 135–148, 2012, doi: 10.1080/1747423X.2010.537790.

M. Antrop, “Landscape change and the urbanization process in Europe,” Landsc. Urban Plan., vol. 67, no. 1–4, pp. 9–26, 2004, doi: 10.1016/S0169-2046(03)00026-4.

P. N. Dadhich and S. Hanaoka, “Spatio-temporal Urban Growth Modeling of Jaipur, India,” J. Urban Technol., vol. 18, no. 3, pp. 45–65, 2011, doi: 10.1080/10630732.2011.615567.

E. F. Lambin, H. J. Geist, and E. Lepers, “Dynamics of Land-Use and Land-Cover Change in Tropical Regions,” Annu. Rev. Environ. Resour., vol. 28, no. 1, pp. 205–241, 2003, doi: 10.1146/annurev.energy.28.050302.105459.

O. R. Abd EL-kawy, H. A. Ismail, H. M. Yehia, and M. A. Allam, “Temporal detection and prediction of agricultural land consumption by urbanization using remote sensing,” Egypt. J. Remote Sens. Sp. Sci., vol. 22, no. 3, pp. 237–246, 2019, doi: 10.1016/j.ejrs.2019.05.001.

M. Dadras, H. Z. M. Shafri, N. Ahmad, B. Pradhan, and S. Safarpour, “Spatio-temporal analysis of urban growth from remote sensing data in Bandar Abbas city, Iran,” Egypt. J. Remote Sens. Sp. Sci., vol. 18, no. 1, pp. 35–52, 2015, doi: 10.1016/j.ejrs.2015.03.005.

A. S. Aguda and S. A. Adegboyega, “Evaluation of Spatio-Temporal Dynamics of Urban Sprawl in Osogbo, Nigeria using Satellite Imagery & GIS Techniques,” Int. J. Multidiscip. Curr. Res., vol. 1, pp. 60–73, 2013.

R. Chand, “Social ecology of immigrant population and changing urban landscape of Thimphu, Bhutan,” J. Urban Reg. Stud. Contemp. India, vol. 4, no. 1, pp. 1–12, 2017, [Online]. Available: http://home.hiroshima-u.ac.jp/hindas/index.html

S. Canaz, Y. Aliefendioğlu, and H. Tanrıvermiş, “Change detection using Landsat images and an analysis of the linkages between the change and property tax values in the Istanbul Province of Turkey,” J. Environ. Manage., vol. 200, no. November, pp. 446–455, 2017, doi: 10.1016/j.jenvman.2017.06.008.

A. F. Alqurashi and L. Kumar, “Investigating the Use of Remote Sensing and GIS Techniques to Detect Land Use and Land Cover Change: A Review,” Adv. Remote Sens., vol. 02, no. 02, pp. 193–204, 2013, doi: 10.4236/ars.2013.22022.

K. Green, D. Kempka, and L. Lackey, “and Remote to Detect Using Sensing Ghange Monitor and Land-Use,” Photogramm. Eng. Remote Sens., vol. 60, no. 3, pp. 331–337, 1994.

J. Rogan and D. M. Chen, “Remote sensing technology for mapping and monitoring land-cover and land-use change,” Prog. Plann., vol. 61, no. 4, pp. 301–325, 2004, doi: 10.1016/S0305-9006(03)00066-7.

S. Reis, “Analyzing land use/land cover changes using remote sensing and GIS in Rize, North-East Turkey,” Sensors, vol. 8, no. 10, pp. 6188–6202, 2008, doi: 10.3390/s8106188.

R. K. Jaiswal, R. Saxena, and S. Mukherjee, “Application of remote sensing technology for land use/land cover change analysis,” J. Indian Soc. Remote Sens., vol. 27, no. 2, pp. 123–128, 1999, doi: 10.1007/BF02990808.

Z. Deng, X. Zhu, Q. He, and L. Tang, “Land use/land cover classification using time series Landsat 8 images in a heavily urbanized area,” Adv. Sp. Res., vol. 63, no. 7, pp. 2144–2154, 2019, doi: 10.1016/j.asr.2018.12.005.

Diksha and A. Kumar, “Analysing urban sprawl and land consumption patterns in major capital cities in the Himalayan region using geoinformatics,” Appl. Geogr., vol. 89, no. October, pp. 112–123, 2017, doi: 10.1016/j.apgeog.2017.10.010.

N. S. N. Shaharum, H. Z. M. Shafri, J. Gambo, and F. A. Z. Abidin, “Mapping of Krau Wildlife Reserve (KWR) protected area using Landsat 8 and supervised classification algorithms,” Remote Sens. Appl. Soc. Environ., vol. 10, pp. 24–35, 2018, doi: 10.1016/j.rsase.2018.01.002.

B. Calka, A. Orych, E. Bielecka, and S. Mozuriunaite, “The Ratio of the Land Consumption Rate to the Population Growth Rate: A Framework for the Achievement of the Spatiotemporal Pattern in Poland and Lithuania,” Remote Sens., vol. 14, no. 5, 2022, doi: 10.3390/rs14051074.

G. Cecili, P. De Fioravante, L. Congedo, M. Marchetti, and M. Munafò, “Land Consumption Mapping with Convolutional Neural Network: Case Study in Italy,” Land, vol. 11, no. 11, 2022, doi: 10.3390/land11111919.

N. Currit, “Development of a remotely sensed, historical land-cover change database for rural Chihuahua, Mexico,” Int. J. Appl. Earth Obs. Geoinf., vol. 7, no. 3, pp. 232–247, 2005, doi: 10.1016/j.jag.2005.05.001.

S. S. Heydari and G. Mountrakis, “Effect of classifier selection, reference sample size, reference class distribution and scene heterogeneity in per-pixel classification accuracy using 26 Landsat sites,” Remote Sens. Environ., vol. 204, no. February 2017, pp. 648–658, 2018, doi: 10.1016/j.rse.2017.09.035.

D. Lu, P. Mausel, E. Brondízio, and E. Moran, “Change detection techniques,” Int. J. Remote Sens., vol. 25, no. 12, pp. 2365–2401, 2004, doi: 10.1080/0143116031000139863.

S. S. Nath, G. Mishra, J. Kar, S. Chakraborty, and N. Dey, “A survey of image classification methods and techniques,” 2014 Int. Conf. Control. Instrumentation, Commun. Comput. Technol. ICCICCT 2014, pp. 554–557, 2014, doi: 10.1109/ICCICCT.2014.6993023.

J. . Benediktsson, P. . Swain, and O. . Ersoy, “Neural network approaches versus statistical methods in classification of multisource remote sensing data,” 1990.

JICA, “Data Collection Survey on Urban Development and Environment in the Kingdom of Bhutan Final Report,” 2014.

Downloads

Published

05/30/2023

How to Cite

Chhetri, I. B. . (2023). STUDY ON SPATIAL-TEMPORAL URBAN GROWTH AND LAND CONSUMPTION PATTERNS OF THIMPHU, BHUTAN USING MULTI-TEMPORAL SATELLITE IMAGES. Journal of Applied Engineering, Technology and Management, 3(1), 32–38. https://doi.org/10.54417/jaetm.v3i1.107