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An Example of Kriging Method based on Environmental Temperature for Altitude Mapping Using ArcGIS Software

Year 2023, , 392 - 401, 31.12.2023
https://doi.org/10.54287/gujsa.1339151

Abstract

The purpose of this study is to demonstrate how Geographic Information System (GIS) software can be used for geographical interpolation, geostatistical analysis, and the creation of maps using relatively sparse data and highlighting the significance of this software in engineering and decision making. The method used in this study is applying ordinary kriging analysis on a gathered database to develop a variation map with interpolation analysis. The selected Z-values are the altitude and Environmental temperature of the selected zone which can contain a vast range. GIS can recognize and analyze the spatial relationships that exist within digitally stored spatial data. This method can bring ease for collecting data from a location that may have difficulties in visiting and gathering data by hand. By the use of semivariogram which is a graphical representation, and the covariance between every pair of points are used to calculate the spatial relationships between interpolating points. As a result, the final output of ArcGIS is a developed map showing altitude variation in the central area of Istanbul. This option can be used in making complex maps in every desired area by predicting Z-values for all the wanted zone based on the given database. Hence, the utility of GIS can bring a great improvement and ease in decision making and planning in civil engineering branches such as transportation, infrastructure, soil mechanics, and construction.

References

  • Ali, S. H., & Mustafa, F. A. (2020). Evaluation of the population distribution using GIS-based geostatistical analysis in Mosul City. Korean Journal of Remote Sensing, 36(1), 83-92. https://www.doi.org/10.7780/kjrs.2020.36.1.7
  • Bhattacharjee, S., Mitra, P., & Ghosh, S. K. (2013). Spatial interpolation to predict missing attributes in GIS using semantic kriging. IEEE Transactions on Geoscience and Remote Sensing, 52(8), 4771-4780. https://www.doi.org/10.1109/TGRS.2013.2284489
  • Bostan, P. (2017). Basic Kriging Methods in Geostatistics. Yuzuncu Yıl University Journal of Agricultural Sciences, 27(1), 10-20. https://www.doi.org/10.29133/yyutbd.305093
  • Dewata, I., & Putra, A. (2021). Kriging-GIS model for the spatial distribution of seawater heavy metals. Periodicals of Engineering and Natural Sciences, 9(2), 629-637. https://www.doi.org/10.21533/pen.v9i2.1851
  • ESRI (2023). ESRI Community, ArcGIS. (Accessed:13/02/2023) URL:https://www.esri.com/en-us/arcgis/products/arcgis-desktop/overview
  • Google Earth (2023). (Accessed:21/02/2023) URL:https://earth.google.com/
  • Johnston, K., Ver Hoef, J. M., Krivoruchko, K., & Lucas, N. (2001). Using ArcGIS Geostatistical Analyst. Redlands. (Accessed:21/02/2023) PDF:https://downloads2.esri.com/support/documentation/ao_/Using_ArcGIS_Geostatistical_Analyst.pdf
  • Liao, G. H. (2022). Configuring Waypoints and Patterns for Autonomous Arduino Robot with GPS and Bluetooth Using an Android App. In: K. Arai (Eds.), Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 3 (pp. 304-312). Springer International Publishing. https://www.doi.org/10.1007/978-3-030-82199-9_18
  • Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Science and Systems (4th ed). John Wiley & Sons.
  • Luna, R., Hall, R., Hilgers, M., Bham, G., Elgin, R., Morris, C., & Morrison, G. (2008, June 22-25). Introduction of GIS into civil engineering curricula. In: 2008 Annual Conference & Exposition (pp. 13-808), Pittsburgh, Pennsylvania. https://www.doi.org/10.18260/1-2--4433
  • Meng, Q., Liu, Z., & Borders, B. E. (2013). Assessment of regression kriging for spatial interpolation–comparisons of seven GIS interpolation methods. Cartography and Geographic Information Science, 40(1), 28-39. https://www.doi.org/10.1080/15230406.2013.762138
  • Paramasivam, C. R., & Venkatramanan, S. (2019). An introduction to various spatial analysis techniques. In: GIS and Geostatistical Techniques for Groundwater Science, (pp. 23-30). Elsevier. https://www.doi.org/10.1016/B978-0-12-815413-7.00003-1
  • Parker, D. (1996). An introduction to GIS and the impact on civil engineering. Proceedings of the Institution of Civil Engineers-Civil Engineering, 114(6), 3-11. https://www.doi.org/10.1680/icien.1996.28911
  • Shad, R., Mesgari, M. S., abkar, A., & Shad, A. (2009). Predicting air pollution using fuzzy genetic linear membership kriging in GIS. Computers, Environment and Urban Systems, 33(6), 472-481. https://www.doi.org/10.1016/j.compenvurbsys.2009.10.004
  • Simmons, G. (1996). Practical applications of GPS for GIS and civil engineering. Proceedings of the Institution of Civil Engineers-Civil Engineering, 114(6), 30-34. https://www.doi.org/10.1680/icien.1996.28913
  • Uyan, M., & Dursun, A. E. (2021). Determination and modeling of lignite reserve using geostatistical analysis and GIS. Arabian Journal of Geosciences, 14(4), 312. https://www.doi.org/10.1007/s12517-021-06633-2
  • Xu, H., & Zhang, C. (2022). Development and applications of GIS-based spatial analysis in environmental geochemistry in the big data era. Environmental Geochemistry and Health, 45(4), 1079-10901. https://www.doi.org/10.1007/s10653-021-01183-8
Year 2023, , 392 - 401, 31.12.2023
https://doi.org/10.54287/gujsa.1339151

Abstract

References

  • Ali, S. H., & Mustafa, F. A. (2020). Evaluation of the population distribution using GIS-based geostatistical analysis in Mosul City. Korean Journal of Remote Sensing, 36(1), 83-92. https://www.doi.org/10.7780/kjrs.2020.36.1.7
  • Bhattacharjee, S., Mitra, P., & Ghosh, S. K. (2013). Spatial interpolation to predict missing attributes in GIS using semantic kriging. IEEE Transactions on Geoscience and Remote Sensing, 52(8), 4771-4780. https://www.doi.org/10.1109/TGRS.2013.2284489
  • Bostan, P. (2017). Basic Kriging Methods in Geostatistics. Yuzuncu Yıl University Journal of Agricultural Sciences, 27(1), 10-20. https://www.doi.org/10.29133/yyutbd.305093
  • Dewata, I., & Putra, A. (2021). Kriging-GIS model for the spatial distribution of seawater heavy metals. Periodicals of Engineering and Natural Sciences, 9(2), 629-637. https://www.doi.org/10.21533/pen.v9i2.1851
  • ESRI (2023). ESRI Community, ArcGIS. (Accessed:13/02/2023) URL:https://www.esri.com/en-us/arcgis/products/arcgis-desktop/overview
  • Google Earth (2023). (Accessed:21/02/2023) URL:https://earth.google.com/
  • Johnston, K., Ver Hoef, J. M., Krivoruchko, K., & Lucas, N. (2001). Using ArcGIS Geostatistical Analyst. Redlands. (Accessed:21/02/2023) PDF:https://downloads2.esri.com/support/documentation/ao_/Using_ArcGIS_Geostatistical_Analyst.pdf
  • Liao, G. H. (2022). Configuring Waypoints and Patterns for Autonomous Arduino Robot with GPS and Bluetooth Using an Android App. In: K. Arai (Eds.), Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 3 (pp. 304-312). Springer International Publishing. https://www.doi.org/10.1007/978-3-030-82199-9_18
  • Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Science and Systems (4th ed). John Wiley & Sons.
  • Luna, R., Hall, R., Hilgers, M., Bham, G., Elgin, R., Morris, C., & Morrison, G. (2008, June 22-25). Introduction of GIS into civil engineering curricula. In: 2008 Annual Conference & Exposition (pp. 13-808), Pittsburgh, Pennsylvania. https://www.doi.org/10.18260/1-2--4433
  • Meng, Q., Liu, Z., & Borders, B. E. (2013). Assessment of regression kriging for spatial interpolation–comparisons of seven GIS interpolation methods. Cartography and Geographic Information Science, 40(1), 28-39. https://www.doi.org/10.1080/15230406.2013.762138
  • Paramasivam, C. R., & Venkatramanan, S. (2019). An introduction to various spatial analysis techniques. In: GIS and Geostatistical Techniques for Groundwater Science, (pp. 23-30). Elsevier. https://www.doi.org/10.1016/B978-0-12-815413-7.00003-1
  • Parker, D. (1996). An introduction to GIS and the impact on civil engineering. Proceedings of the Institution of Civil Engineers-Civil Engineering, 114(6), 3-11. https://www.doi.org/10.1680/icien.1996.28911
  • Shad, R., Mesgari, M. S., abkar, A., & Shad, A. (2009). Predicting air pollution using fuzzy genetic linear membership kriging in GIS. Computers, Environment and Urban Systems, 33(6), 472-481. https://www.doi.org/10.1016/j.compenvurbsys.2009.10.004
  • Simmons, G. (1996). Practical applications of GPS for GIS and civil engineering. Proceedings of the Institution of Civil Engineers-Civil Engineering, 114(6), 30-34. https://www.doi.org/10.1680/icien.1996.28913
  • Uyan, M., & Dursun, A. E. (2021). Determination and modeling of lignite reserve using geostatistical analysis and GIS. Arabian Journal of Geosciences, 14(4), 312. https://www.doi.org/10.1007/s12517-021-06633-2
  • Xu, H., & Zhang, C. (2022). Development and applications of GIS-based spatial analysis in environmental geochemistry in the big data era. Environmental Geochemistry and Health, 45(4), 1079-10901. https://www.doi.org/10.1007/s10653-021-01183-8
There are 17 citations in total.

Details

Primary Language English
Subjects Civil Engineering (Other)
Journal Section Civil Engineering
Authors

Mitra Salehı 0000-0001-5578-4699

Hasan Volkan Oral 0000-0002-5743-1931

Early Pub Date October 30, 2023
Publication Date December 31, 2023
Submission Date August 7, 2023
Published in Issue Year 2023

Cite

APA Salehı, M., & Oral, H. V. (2023). An Example of Kriging Method based on Environmental Temperature for Altitude Mapping Using ArcGIS Software. Gazi University Journal of Science Part A: Engineering and Innovation, 10(4), 392-401. https://doi.org/10.54287/gujsa.1339151