Vegetation and Built-Up Area Monitoring in Bandung City Using Multitemporal Imagery
DOI:
https://doi.org/10.24114/jg.v15i1.42656Abstract
Bandung is West Java's largest metropolitan city and Indonesia's third largest. The city of Bandung is very strategic in various aspects, such as accessibility, communication, public facilities, and the economy. The Increased population in Bandung indicates more complex ongoing human activities, which can then affect changes in land use. The land covers in urban areas tends to change more drastically over a short period e than in rural areas because of rapid urbanization. Therefore, urban phenomenon changes are ideally monitored and detected from satellite images with a multitemporal resolution. Vegetation greenness and built-up areas can identify through multitemporal remote sensing imagery. Changes in vegetation and built-up area can monitor using remote sensing with multitemporal imagery. The analysis of changes in vegetation and built-up area studied in Bandung City represents an area with rapid population growth. This study aims to: 1) Identify changes in vegetation greenness in Bandung City between 2014 and 2021, 2) Identify built-up area changes in Bandung City between 2014 and 2021, 3) Analyze the relevance between vegetation greenness and the built-up area in Bandung City”the correlation between NDBI and NDVI through selected samples is representative of all data in Landsat 8 imagery. The proportion between the values of NDBI and NDVI samples is 0.9034. So, it is concluded that the two variables are positively correlated. Therefore, the study™s results recommend preserving vegetated land cover to conserve natural resources and prevent increased land surface temperature.Keywords: Remote Sensing Imagery, Built-Up Area, Vegetation Greenness, Bandung CityReferences
Akinrinola, A. J. 2019. Spatial pattern of urban growth using remote sensing and landscape metrics. Journal of Geomatics Vol. 13, No. 1, April 2019.
BPS-Statistics of Bandung City. (2014). Bandung Municipality in Figures 2014. Bandung City: BPS; 2014.
BPS-Statistics of Bandung City. (2021). Bandung Municipality in Figures 2021. Bandung City: BPS; 2021.
BPS-Statistics of Bandung City. (2022). Bandung Municipality in Figures 2022. Bandung City: BPS; 2022.
Chen, L., Li, M., Huang, F. (2013). Relationships of LST to NDBI and NDVI in Wuhan City Based on Landsat ETM+ Image. 6th International Congress on Image and Signal Processing (CISP 2013).
Chuvieco, E., and Huete, A. (2010). Fundamentals of Satellite Remote Sensing. CRC Press. United States of America.
Campbell, J. B., and Wynne, R. H. (2011). Introduction to Remote Sensing (5th Edition). The Guilford Press. New York.
Danoedoro, P. (2012), Pengantar Penginderaan Jauh Digital. Penerbit ANDI. Yogyakarta
Darmaputra, P. A., Darwin, I. S. 2022. Prediksi Lahan Terbangun di Wilayah Peri-Urban Kota Bandung. Bandung Conference Series: Urban & Regional Planning Vol. 2 No. 2 (2022), Hal: 493-499.
Essien, E. & Cyrus, S. 2019. Detection of Urban Development in Uyo (Nigeria) Using Remote Sensing. Land 2019, 8, 102.
Fawzi, N.I. & Husna, V.N., 2021. Landsat 8 - Sebuah Teori dan Teknik Pemrosesan Tingkat Dasar. Elmarkazi Publisher: Bengkulu.
Hidayati, I. N., Suharyadi, Danoedoro, P. (2017). Pemetaan Lahan Terbangun Perkotaan Menggunakan Pendekatan NDBI dan Segmentasi Semi-automatik. Prosiding Seminar Nasional Geografi UMS 2017.
Hosea, H., Pravitasari, A. M., Setiawande, Y., Rustiadi, E. 2019. Landscape metric in the analysis of urban form in Cekungan Bandung Urban Region. SPIE, Vol. 11372
Indradjati, P. N., & Aisha, I. N. 2019. Adapting Urban Heat Island Mitigation Strategy on Bandung Downtown Area. Journal of Architecture and Built Environment, Vol. 46, No. 2, December 2019, 129-140.
Karanam, H. K. (2018). Study of Normalized Difference Built-up Index (NDBI) in Automatically Mapping Urban Areas from Landsat TM Imagery. International Journal of Scientific Research and Review. Volume 7, Issue 1, 2018.
Lynch, P., Blesius, L., & Hines, E. 2020. Classification of Urban Area Using Multispectral Indices for Urban Planning. Remote Sensing. 2020, 12, 2503.
Malik, M. S., Shukia, J. P., and Mishra, S. (2019). Relationship of LST, NDBI and NDVI using Landsat-8 data in Kandaihimmat Watershed, Hoshangabad, India. Indian Journal of Geo Marine Sciences Vol. 48 (01), January 2019, pp. 25-31
Morley, R. J. (2005) Tropical Rain Forests. Earth System: History and Natural Variability III.
Mróz, M., and Sobieraj, A. (2004). Comparison of Several Vegetation Indices Calculated on The Basis of a Seasonal Spot XS Time Series, and Their Suitability for Land Cover and Agricultural Crop. Identification Technical Sciences Abbrev.: Techn. Sc., No 7.
Nastiti Puspitasari, W. P. (2013). Faktor yang Mempengaruhi Perubahan Guna Lahan dan Pola Perkembangan Permukiman Kawasan Pinggiran (Studi Kasus: Daerah Gedawang, Kota Semarang). JurnalTeknikPWK, 638-648.
Neyns, R., & Canters, F. 2022. Mapping of Urban Vegetation with High-Resolution Remote Sensing: A Review. Remote Sensing. 2022, 14, 1031.
Nurhuda, A., Huda, D. N., and Adhisurya, S. (2019). Penginderaan Jauh untuk Analisis Spasial Temporal Suhu Permukaan Daratan di Kota Manado Tahun 2015 dan 2019. Seminar Nasional Penginderaan Jauh ke-6 tahun 2019.
Ozyavuz, M. (2010). Analysis of Changes in Vegetation Using Multitemporal Satellite Imagery, the Case of Tekirdag˘ Coastal Town. Journal of Coastal Research 26 (6) :1038-1046
Prasetyo, N. N., Sasmito, B., and Prasetyo, Y. 2017. Analisis Perubahan Kerapatan Hutan menggunakan Metode NDVI dan EVI pada Citra Satelit Landsat 8 Tahun 2013 dan 2016. Jurnal Geodesi Undip 6 (3): 21 “ 27
Rasul, A., Balzter, H., Smith, C., Remedios, J., Adamu, B., Sobrino, J.A., Srivanit, M., and Weng, Q. 2017. A Review on Remote Sensing of Urban Heat and Cool Islands. Land 2017, 6, 38.
Ridwan, M. A., Radzi, N. A. M., Ahmad, W. S. H. M. W., Mustafa, I.S., Din, N. M., Jalil, Y. E., Isa, A. M., Othman, N. S., Zaki, W. M. D. W. 2018. Applications of Landsat-8 Data: a Survey. International Journal of Engineering & Technology, 7 (4.35) (2018) 436-441.
Rusnandar. (2010). Sejarah Kota Bandung dari œBergdessa (Desa Udik) Menjadi Bandung œHeurin ku Tangtung (Metropolitan). Balai Pelestarian Sejarah dan Nilai Tradisional Bandung
Sajjad Hussain, S. Q. (2022). Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020. MDPI, 2-18.
Safariah, R., Majid, M. R., Rusli, N. 2022. The Contribution of Housing Area to Land Surface. Journal of Sustainability Science and Management Volume 17 Number 7, July 2022: 62-72.
Swain, P. H., and Davis, S. M. (1978). Remote Sensing the Quantitative Approach. McGraw-Hill Inc. United States of America.
Zha, Y., Gao., J., and Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal Remote Sensing Vol. 24, No. 3, 583“594.
