Studi Perbandingan Estimasi Tahun Konstruksi Jembatan di Indonesia Dengan Metode Remote Sensing
Abstract
Abstrak
Jembatan adalah infrastruktur penghubung dua bagian daerah terputus karena adanya rintangan. Berdasarkan bentangnya, jembatan diklasifikasikan menjadi jembatan pendek dengan panjang L≤ 30 m, jembatan sedang dengan panjang 30 < L < 100 m, dan jembatan panjang dengan panjang L ≥ 100 m. Tahun 2019 Bina Teknik Jalan dan Jembatan telah mendata 18.648 jembatan di Indonesia yang sebagian besar belum diketahui tahun konstruksinya. Tahun konstruksi jembatan dibutuhkan sebagai proses identifikasi usia jembatan berkaitan dengan usia pakai, rencana sistem operasi dan manajemen pemeliharaan jembatan. Penelitian ini melakukan studi perbandingan tahun konstruksi data Bintek JalJem dengan estimasi tahun konstruksi jembatan menggunakan metodologi data satelit remote sensing NDVI dan NDWI. Hasil pembahasan mendapatkan estimasi tahun konstruksi jembatan dengan remote sensing kasus jembatan panjang, persentase sebaran NDWI mencapai 63,7%, NDVI mencapai 63,05%. Untuk kasus jembatan sedang, persentase sebaran NDWI mencapai 58,61%, NDVI mencapai 52,96%. Untuk kasus jembatan pendek, persentase sebaran NDWI mencapai 55,78%, NDVI mencapai 43,7%. Simpulan penelitian mengianjurkan menggunakan metode NDWI untuk mendapatkan hasil perkiraan tahun konstruksi lebih tepat tanpa kunjungan fisik ke lokasi. Untuk mendapatkan ketepatan estimasi tahun konstruksi disarankan menggunakan index lain yang memiliki keakuratan dengan lingkup tinjauan, dengan harapan dapat mengidentifikasi jenis material obyek tinjauan. Hal ini bertujuan membuat prediksi (forecasting) sistem operasi dan manajemen pemeliharaan konstruksi tinjauan.
Kata kunci: estimasi tahun konstruksi, jembatan, remote sensing, NDWI, NDVI
Abstract
A bridge is infrastructure that connect two parts of an area that separated by an obstacle. Based on its span, a bridge is classified into short bridges with a length of L≤ 30 m, medium bridges with a length of 30 < L < 100 m, and long bridges with a length of L ≥ 100 m. In 2019, Road and Bridge Engineering Development recorded 18,648 bridges in Indonesia, most of which the year of construction is unknown. The year of bridge construction is needed for identifying the age of the bridge in relation to its service life, operation system plan, and bridge maintenance management. This study conducts a comparison of the construction year data from Road and Bridge Engineering Development with estimated construction years using satellite remote sensing methodologies, specifically NDVI and NDWI. The results show that the estimated construction year for long-bridge cases using remote sensing, with an NDWI distribution percentage of 63.7% and an NDVI of 63.05%. For medium-bridge cases, the NDWI distribution percentage reaches 58.61%, while NDVI reaches 52.96%. For short-bridge cases, the NDWI distribution percentage is 55.78%, and the NDVI is 43.7%. The study concludes by recommending the use of the NDWI method to obtain more accurate estimates of the construction year without the need for physical visits to the to obtain accurate construction year estimates, it is also recommended to use other indices that are accurate with the scope of the review. It is hoped that this index can identify the type of material of the object being reviewed. This aims to make forecasting of the operation system and maintenance management for the surveyed construction.
Keywords: estimated year of construction, bridge, remote sensing, NDWI, NDVI
Keywords
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Alamsyjah, J., 2020. Estimasi Tahun Konstruksi Jembatan di Indonesia Menggunakan Analisis Data Satelit Landsat. Skripsi ed. Bandung: Universitas Katolik Parahyangan.
Bhandari, A. K., Kumar, A. & Singh, G. K., 2012. Feature Extraction using Normalized Difference Vegetation Index (NDVI): A case study of Jabalpur city.. Procedia technology, pp. 612-621.
Brown, G. W., 1982. Standard Deviation, Standard Error. Am J Dis Child, Volume 136, pp. 937-941.
Buiten, H. J. & Clevers, J. G. P. W., 1993. Land Observation by Remote Sensing: Theory and Applications. s.l.:Gorden & Breach.
Campbell, J. B. & Wynne, R. H., 2011. Introduction to Remote Sensing. 5th ed. New York: Guilford Press.
Chander, G., Markham, B. L. & Helder, D. L., 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+,and EO-1 ALI sensors. Remote Sensing of Environment, Volume 113, pp. 893-903.
Ernst, C. et al., 2013. National forest cover change in Congo Basin: deforestation, reforestation, degradation and regeneration for the years 1990, 2000 and 2005. Global Change Biology, April, 19(4), pp. 1173-1187.
Fadli, A. H., Kosugo, A. & Ramli, R., 2018. Satellite-based monitoring of forest cover change in Indonesia using google earth engine from 2000 to 2016.. Journal of Physics: Conference Series..
Gao, B., 1996. NDWI - A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water From Space. Remote Sensing of Environment, 58(3), pp. 257-266.
Hashim, H., Latif, Z. A. & Adnan, N. A., 2019. Urban Vegetation Classification With NDVI Threshold Value. Kuala Lumpur, 6th International Conference on Geomatics and Geospatial Technology (GGT 2019).
Janssen, L. L. F. et al., 2001. Principles of Remote Sensing. 2nd ed. Netherlands: ITC.
Jiang, Y. & Sinha, K. C., 1989. Bridge Service Life Prediction Model using the Markov Chain.. Transportation research record, Issue 1223, pp. 24-30.
Kumar, N., S.S., Y. & A., V., 2015. Applications of Remote Sensing and GIS in Natural Resource Management. Journal of the Andaman Science Association, 20(1), pp. 1-6.
Landsat Science, n.d.. Landsat Science. [Online]
Available at: https://landsat.gsfc.nasa.gov/about
[Accessed 5 September 2020].
PUPR., 2018. Materi Suplemen Pengetahuan Pembekalan Keprofesian: Pemeliharaan Jembatan.. Jakarta Indonesia: Kementrian Pekerjaan Umum dan Perumahan Rakyat Indonesia.
Pusat Komunikasi Publik, 2007. Jumlah Jembatan di Indonesia Relatif Sedikit [online] 13 September.. [Online]
Available at: https://www.pu.go.id/berita/view/1037/jumlahjembatan-di-indonesia-relatif-sedikit
[Accessed 3 Maret 2024].
Sovisoth, E. et al., 2019. Estimation of the Bridge Construction Year in Cambodia by Analysis of Landsat Satellite Data. Sapporo, Japan Concrete Institute.
Struyk, H., 1984. Jembatan. Jakarta: P.T. Pradnya Paramita.
Supriyadi, 2007. Jembatan. Yogyakarta: Betta Offset.
U.S Geological Survey, n.d. U.S Geological Survey official. [Online]
Available at: https://www.usgs.gov/land-resources/nli/landsat/landsat-normalized-difference-vegetation-index?qt- science_support_page_ related_con=0#qt- science_support_page_related_ con
[Accessed Desember 2019].
U.S.G.S., 2016. Landsat-Earth Observation Satellites. [Online]
Available at: https://pubs.usgs.gov/fs/2015/3081/fs20153081.pdf
[Accessed 8 June 2020].
Vaza, H., 2016. Research on the Improvement of Bridge Management System 1992. Case of Bridge Condition Assessment in the Decentralized Indonesia, pp. 24-25.
Vaza, H., Sastrawiria, R. P., Halim, H. A. & Septinurriandiani, 2017. Identifikasi Kerusakan & Penentuan Nilai Kondisi Jembatan. 1st penyunt. s.l.:s.n.
Xian, G. & Crane, M., 2005. Assessments of Urban Growth in the Tampa Bay Watershed using Remote Sensing data.. Remote Sensing of Environment, 97(2), pp. 203-215.
Yugiantoro, H., t.thn. NSPK Jembatan. [Online]
Available at: http://nspkjembatan.pu.go.id/public/uploads/elearning/ 1556255146lecture_6.1_-_dasar_perencanaan_bangunan_atas.pdf
[Diakses 26 Maret 2020].
DOI: https://doi.org/10.29103/tj.v15i1.1234
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