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New Approach in Integrated Basin Modelling: Melen Airborne LIDAR

Year 2019, Volume: 6 Issue: 1, 22 - 32, 12.04.2019
https://doi.org/10.30897/ijegeo.530272

Abstract

References

  • Baş, N., Çoşku, HG., Kaya, Ş., Bayram, B. & Çelik, H. (2018). Effective LIDAR Data Classification by Row Data and Parameter Analysis Framework. Fresenius Environmental Bulletin, 27(6), 4068-4075.
  • Bayram, B., Demir, N., Oğurlu, M., Çatal reis, H. & Şeker, DZ. (2016, October). 3D Shoreline Extraction Using Orthopoto-Maps and LIDAR. 37th Asian Conference on Remote Sensing (p. 1-5) in. Sri Lanka: Colombo.
  • Brenner, C. (1999). Interactive modelling tools for 3D building construction. In: D. Fritsch and R. Spiller (Eds.), Photogrammetric Week ‘99, (p. 23-34). Heidelberg: Herbert Wichmann Verlag.
  • Büyüksalih, İ. (2012). Building Zone Regulation Compliance Using LIDAR Data: Real-Life Tests in İstanbul. International Journal of Environment and Geoinformatics (IJEGEO), 3(1), 48-55.
  • Chen, Q., P. Gong, D.D. Baldocchi, and Y. Tian, (2007). Estimating basal area and stem volume for individual trees from LIDAR data. Photogrammetric Engineering & Remote Sensing. 1355-1365.
  • Ekercin, S. & Üstün, B. (2004). Uzaktan Algılamada Yeni bir Teknoloji: LIDAR, HKMO Jeodezi, Jeoinformasyon ve Arazi Yönetimi Dergisi., 91s.
  • Gazioğlu, C. (2018). Biodiversity, Coastal Protection, Promotion and Applicability Investigation of the Ocean Health Index for Turkish Seas. International Journal of Environment and Geoinformatics (IJEGEO), 5(3), 353-367.
  • Gazioğlu, C., Alpar, B., Yücel, ZY., Müftüoğlu, AE., Güneysu, C. & Ertek, TA. (2014). Morphologic Features of Kapıdağ Peninsula and its Coasts (NW-Turkey) using by Remote Sensing and DTM. International Journal of Environment and Geoinformatics (IJEGEO) 1(1), 48-63.
  • Hantschel, T., Kauerauf, A.I. (2009). Introduction to Basin modeling. In: Fundamentals of Basin and Petroleum Systems Modelling, (Chapter 1, p. 1-30). Berlin/Heidelberg: Springer-Verlag.
  • Jenkins, R. B. and P. S. Frazier, (2010). High-Resolution Remote Sensing of Upland Swamp Boundaries and Vegetation for Baseline Mapping and Monitoring. Wetlands, 30(3), 531–540.
  • Kaya, H. & Gazioğlu, C. (2015). Real Estate Development at Landslides. International Journal of Environment and Geoinformatics (IJEGEO) 2(1), 62-71.
  • Kirtner, J. (2000). Using LIDAR Data in Wireless Communication System Design. Washington DC: ASPRS Proceedings.
  • Nakajima, T., Hirata, Y., Hiroshima, T., Furuya, N., Tatsuhara, S., Tsuyuki, S., and N. Shiraishi, (2011). A Growth Prediction System for Local Stand Volume Deerived from LIDAR Data. GIScience & Remote Sensing, 48(3), 394–415.
  • Nelson, J. (2019). Computational Modeling of River Flow, Sediment Transport, and Bed Evolution Using Remotely Sensed Data, 7.
  • Perroy, R. L., Bookhagen, B., Asner, G. P., and O. A. Chadwick, (2010). Comparison of Gully Erosion Estimates Using Airborne and Ground-based LIDAR on Santa Cruz Island, California. Geomorphology, 118(3–4), 288–300.
  • Petroselli, A. (2012). LIDAR Data and Hydrological Applications at the Basin Scale, GIScience & Remote Sensing, 49(1), 139-162.
  • Solberg, S., Astrup, R., Gobakken, T., Næsset, E., and D. J. Weydahl, (2010). Estimating Spruce and Pine Biomass with Interferometric X-band SAR. Remote Sensing of Environment, 114(110), 2353–2360.
  • URL 1. (2019) Orman ve Su işleri Bakanlığı. Su Yönetmi Genel Müdürlüğü, 54p. www.ormansu.gov.tr.
  • Wehr, A. & U. Lohr. (1999). Airborne Laser Scanning an Introduction and Overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2–3), 68–82.
  • Xuelian; M., Le, W. & Nate, C. (2009). Morphology-based Building Detection from Airborne Lidar Data. Photogrammetric Engineering & Remote Sensing, 4(6), 437-442.
  • Yan, W Y., Shaker, Ahmed & LaRocque, P. (2018). Water mapping using multispectral airborne LiDAR data. ISPRS - International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences. 42(3), 2047-2052. 10.5194/isprs-archives-XLII-3-2047-2018.
  • Zandbergen, P., (2010) Accuracy Considerations in the Analysis of Depressions in Medium-Resolution LIDAR DEMs. GIScience & Remote Sensing, 47(2), 187–207.
  • Zhang, K., Chen, SC., Whitman, D., Shyu; ML.,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).
  • Zhang, Y., Zhang, Z., Zhang, J. & Wu, Jun. (2005). 3D Building Modelling with Digital Map, Lidar Data and Video Image Sequences. The Photogrammetric Record. 20, 285-302. 10.1111/j.1477-9730.2005.00316.x.

New Approach in Integrated Basin Modelling: Melen Airborne LIDAR

Year 2019, Volume: 6 Issue: 1, 22 - 32, 12.04.2019
https://doi.org/10.30897/ijegeo.530272

Abstract

Airborne LIDAR technology which has an increasing importance in recent years, has entered into the field of application of many disciplines by obtaining fast and highly accurate 3D data. It provides precise topography information with dense point cloud data as well as all details on the surface. Thus, it has become useful in all disciplines associated with space such as cartography, construction, city planning, forest, energy, hydrology, geology, transportation, telecommunications, security, disaster, aviation, and infrastructure. By mounting LIDAR measurement units on aircraft large areas can be measured relatively quickly and cost-effectively. In this study, Riegl Q680i scanner and CCNS5 flight management system were mounted to the aircraft. The digital elevation models; DEM (Digital Elevation Model) and DSM (Digital Surface Model) of the Melen basin, which is located within the boundaries of Düzce and Sakarya was generated using LIDAR point cloud data (.las format) with a point density of 16 points/m2 and also 1/1000 base maps of the basin were produced. In addition, many details such as road, slope, culvert, electricity poles were drawn in accordance with the principles of large-scale map construction regulations and transferred to GIS environment. The Melen basin with an important water storage area, boundaries, basin model, water collection lines, determination of flow directions and connections, the topographic surface of the basin sub-areas, morphology were created using 3D laser point cloud data. So, the digital terrain model of the basin in GIS environment is visualized with linear maps. LIDAR data provides 3D geometric and morphological information that cannot be obtained according to classical methods in this kind of engineering studies. Results suggest that the higher spatial resolution LIDAR-derived data are preferable and can introduce more detailed information about basin hydro geomorphic behaviours.  

References

  • Baş, N., Çoşku, HG., Kaya, Ş., Bayram, B. & Çelik, H. (2018). Effective LIDAR Data Classification by Row Data and Parameter Analysis Framework. Fresenius Environmental Bulletin, 27(6), 4068-4075.
  • Bayram, B., Demir, N., Oğurlu, M., Çatal reis, H. & Şeker, DZ. (2016, October). 3D Shoreline Extraction Using Orthopoto-Maps and LIDAR. 37th Asian Conference on Remote Sensing (p. 1-5) in. Sri Lanka: Colombo.
  • Brenner, C. (1999). Interactive modelling tools for 3D building construction. In: D. Fritsch and R. Spiller (Eds.), Photogrammetric Week ‘99, (p. 23-34). Heidelberg: Herbert Wichmann Verlag.
  • Büyüksalih, İ. (2012). Building Zone Regulation Compliance Using LIDAR Data: Real-Life Tests in İstanbul. International Journal of Environment and Geoinformatics (IJEGEO), 3(1), 48-55.
  • Chen, Q., P. Gong, D.D. Baldocchi, and Y. Tian, (2007). Estimating basal area and stem volume for individual trees from LIDAR data. Photogrammetric Engineering & Remote Sensing. 1355-1365.
  • Ekercin, S. & Üstün, B. (2004). Uzaktan Algılamada Yeni bir Teknoloji: LIDAR, HKMO Jeodezi, Jeoinformasyon ve Arazi Yönetimi Dergisi., 91s.
  • Gazioğlu, C. (2018). Biodiversity, Coastal Protection, Promotion and Applicability Investigation of the Ocean Health Index for Turkish Seas. International Journal of Environment and Geoinformatics (IJEGEO), 5(3), 353-367.
  • Gazioğlu, C., Alpar, B., Yücel, ZY., Müftüoğlu, AE., Güneysu, C. & Ertek, TA. (2014). Morphologic Features of Kapıdağ Peninsula and its Coasts (NW-Turkey) using by Remote Sensing and DTM. International Journal of Environment and Geoinformatics (IJEGEO) 1(1), 48-63.
  • Hantschel, T., Kauerauf, A.I. (2009). Introduction to Basin modeling. In: Fundamentals of Basin and Petroleum Systems Modelling, (Chapter 1, p. 1-30). Berlin/Heidelberg: Springer-Verlag.
  • Jenkins, R. B. and P. S. Frazier, (2010). High-Resolution Remote Sensing of Upland Swamp Boundaries and Vegetation for Baseline Mapping and Monitoring. Wetlands, 30(3), 531–540.
  • Kaya, H. & Gazioğlu, C. (2015). Real Estate Development at Landslides. International Journal of Environment and Geoinformatics (IJEGEO) 2(1), 62-71.
  • Kirtner, J. (2000). Using LIDAR Data in Wireless Communication System Design. Washington DC: ASPRS Proceedings.
  • Nakajima, T., Hirata, Y., Hiroshima, T., Furuya, N., Tatsuhara, S., Tsuyuki, S., and N. Shiraishi, (2011). A Growth Prediction System for Local Stand Volume Deerived from LIDAR Data. GIScience & Remote Sensing, 48(3), 394–415.
  • Nelson, J. (2019). Computational Modeling of River Flow, Sediment Transport, and Bed Evolution Using Remotely Sensed Data, 7.
  • Perroy, R. L., Bookhagen, B., Asner, G. P., and O. A. Chadwick, (2010). Comparison of Gully Erosion Estimates Using Airborne and Ground-based LIDAR on Santa Cruz Island, California. Geomorphology, 118(3–4), 288–300.
  • Petroselli, A. (2012). LIDAR Data and Hydrological Applications at the Basin Scale, GIScience & Remote Sensing, 49(1), 139-162.
  • Solberg, S., Astrup, R., Gobakken, T., Næsset, E., and D. J. Weydahl, (2010). Estimating Spruce and Pine Biomass with Interferometric X-band SAR. Remote Sensing of Environment, 114(110), 2353–2360.
  • URL 1. (2019) Orman ve Su işleri Bakanlığı. Su Yönetmi Genel Müdürlüğü, 54p. www.ormansu.gov.tr.
  • Wehr, A. & U. Lohr. (1999). Airborne Laser Scanning an Introduction and Overview. ISPRS Journal of Photogrammetry and Remote Sensing, 54(2–3), 68–82.
  • Xuelian; M., Le, W. & Nate, C. (2009). Morphology-based Building Detection from Airborne Lidar Data. Photogrammetric Engineering & Remote Sensing, 4(6), 437-442.
  • Yan, W Y., Shaker, Ahmed & LaRocque, P. (2018). Water mapping using multispectral airborne LiDAR data. ISPRS - International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences. 42(3), 2047-2052. 10.5194/isprs-archives-XLII-3-2047-2018.
  • Zandbergen, P., (2010) Accuracy Considerations in the Analysis of Depressions in Medium-Resolution LIDAR DEMs. GIScience & Remote Sensing, 47(2), 187–207.
  • Zhang, K., Chen, SC., Whitman, D., Shyu; ML.,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).
  • Zhang, Y., Zhang, Z., Zhang, J. & Wu, Jun. (2005). 3D Building Modelling with Digital Map, Lidar Data and Video Image Sequences. The Photogrammetric Record. 20, 285-302. 10.1111/j.1477-9730.2005.00316.x.
There are 24 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

İsmail Büyüksalih 0000-0001-6301-8900

Cem Gazioğlu 0000-0002-2083-4008

Publication Date April 12, 2019
Published in Issue Year 2019 Volume: 6 Issue: 1

Cite

APA Büyüksalih, İ., & Gazioğlu, C. (2019). New Approach in Integrated Basin Modelling: Melen Airborne LIDAR. International Journal of Environment and Geoinformatics, 6(1), 22-32. https://doi.org/10.30897/ijegeo.530272