DOI: https://doi.org/10.14710/teknik.v40i1.23004

Digital Terrain Model (DTM) Generation From Light Detection and Ranging (LiDAR) Data By Using Simple Morphological

Pembuatan Digital Terrain Model (DTM) dari Light Detection and Ranging (LiDAR) menggunakan Metode Morfologi Sederhana

*Ayu Nur Safi'i  -  Pusat Penelitian, Promosi dan Kerjasama, Badan Informasi Geospasial, Indonesia
Prayudha Hartanto  -  , Indonesia
Open Access Copyright (c) 2019 TEKNIK

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Abstract

The production of Indonesian Topographic Map (RBI) in the scale of 1:5000 takes a long time, especially in the making of contour layer. Contour layer can be extracted from both Aerial Photogrammetry and LiDAR data. Nowadays, LiDAR technology is getting more reliable for DSM. From DSM can be exctracted to get DTM/DEM. DTM/ DEM generation because of its shorter processing  time  and  relatively  low  cost.  The  filtering  method  used  in  this  research  is  Simple Morphological Filtering (SMRF) which input parameters are: cell size, slope, windows, elevation threshold and scaling factor. Average value of Cohen’s kappa is in the range of 0.4-07 which means that the generated DTM is good. Because of the existence of null values in the generated DTM, the smoothing filters have been applied. The extracted DTM then be compared to in situ data. The RMSE ranged from 0,621 to 0,930 m and LE90 about 1,025-1,605. Those RMSE and LE90 values satisfied the vertical accuracy of the 1: 5000 topographic map and graded as the second and third class in accordance to BIG Regulation No.6 of 2018 as revision of Perka BIG No.15 of 2014 focusing on Technical guidelines for Basic Map Accuracy.

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Keywords: LiDAR; DTM; SMRF

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  1. Amin, M. B. Al. (2015). Pemanfaatan Teknologi LiDAR Dalam Analisis Genangan Banjir Akibat Luapan Sungai Berdasarkan Simulasi Model Hidrodinamik. Info Teknik, 16(1), 21–32
  2. Duantari, N., & Cahyono, A. B. (2017). Analisis Perbandingan DTM ( Digital Terrain Ranging ) dan Foto Udara dalam Pembuatan Kontur Peta Rupa Bumi Indonesia. Teknik ITS, 6(2), 793–797
  3. Fleiss, J. L. (1975). Measuring Agreement between Two Judges on the Presence or Absence of a Trait. Biometrics, 31(3), 651 ‐ 659
  4. Geospasial, I. Pedoman Teknis Ketelitian Peta Dasar. , (2018)
  5. Julzarika, A., & Sudarsono, B. (2009). Penurunan Model Permukaan Dijital (DSM) Menjadi Model Elevasi Dijital (DEM) Dari Citra Satelit Alos Palsar (Studi kasus: NAD Bagian Tenggara, Indonesia). Teknik, 30(1), 57–63
  6. Kobler, A., Pfeifer, N., Ogrinc, P., Todorovski, L., Oštir, K., & Džeroski, S. (2007). Repetitive interpolation: A robust algorithm for DTM generation from Aerial Laser Scanner Data in forested terrain. Remote Sens. Environ, 108, 9–23
  7. Maune, D. F., Huff, L. C., & Guenther, G. C. (2001). DEM user applications. Digital Elevation Model Technologies and Applications: The DEM Users Manual, 391–423
  8. Pingel, T. J., Clarke, K., & Mcbride, W. A. (2013). An Improved Simple Morphological Filter for the Terrain Classification of Airborne LIDAR Data. ISPRS Journal of Photogrammetry and Remote Sensing, 77(April 2017), 21–30. https://doi.org/10.1016/j.isprsjprs.2012.12.002
  9. Sari, D. R. (2016). Analisa Geometrik True Orthophoto Data LIDAR. Institut Teknologi Sepuluh Nopember
  10. Shamsi, U. M. (2005). GIS Aplications for water, wastewater, and Stormwater Systems. United States of America
  11. Sudarsono, B., & Julzarika, A. (2010). Uji Ketelitian Hasil Koreksi Geometrik Citra Satelit Alos Prism Dengan Hitung Perataan Kuadrat Terkecil Metode Parameter. Teknik, 31(1), 8521697
  12. Susetyo, D. B., & Perdana, P. (2015). Uji Ketelitian Digital Surface Model ( DSM ) sebagai Data Dasar dalam Pembentukan Kontur Peta Rupabumi Indonesia ( RBI ). Sinas Inderaja, 1
  13. Vosselman, G. (2000). Slope based filtering of laser altimetry data. Int. Arch. Photogramm. Remote Sens, 33, 935–942
  14. Whitman, D., Zhang, K., Leatherman, S., & Robertson, W. (2003). Airborne laser topographic mapping: Applications to hurricane storm surge hazards. https://doi.org/10.1029/SP056p0363
  15. Zhang, K., Chen, S.-C., Whitman, D., Shyu, M.-L., Yan, J., & Zhang, C. (2003). A progressive morphological filter for removing nonground measurements from airborne LIDAR data. IEEE Transactions on Geoscience and Remote Sensing, 41(4), 872–882. https://doi.org/10.1109/TGRS.2003.810682

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