Analysing the Potential of OpenStreetMap Data to Improve the Accuracy of SRTM 30 DEM on Derived Basin Delineation, Slope, and Drainage Networks
Abstract
:1. Introduction
2. Study Area and Data
2.1. Data
2.1.1. Digital Elevation Models
2.1.2. Watercourses
3. Methodology
3.1. OSM Data Preparation
3.2. Creation of the Rebuilts DEMs
3.3. Drainage Networks Extraction from the DEMs
3.4. Slope Computations and Basin Generation
3.5. DEMs and Slope Accuracy Assessment
3.6. Drainage Network Accuracy Assessment
3.6.1. Horizontal Accuracy
3.6.2. Vertical Accuracy
3.7. Basins Accuracy Assessment
4. Results
4.1. DEMs Accuracy
4.2. Slope Accuracy
4.3. Drainage Networks Accuracy
4.3.1. Horizontal Accuracy
4.3.2. Vertical Accuracy
4.3.3. River Analysis
4.4. Basin Accuracy
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Moore, I.D.; Grayson, R.B.; Ladson, A.D. Digital terrain modelling: A review of hydrological, geomorphological and biological applications. Hydrol. Process. 1991, 5, 3–30. [Google Scholar] [CrossRef]
- Lin, J.Y.; Cheng, C.T.; Chau, K.W. Using support vector machines for long-term discharge prediction. Hydrol. Sci. J. 2006, 51, 599–612. [Google Scholar] [CrossRef] [Green Version]
- Kumar, R.; Samaniego, L.; Attinger, S. Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations. Water Resour. Res. 2013, 49, 360–379. [Google Scholar] [CrossRef]
- Wu, Y.; Li, T.; Sun, L.; Chen, J. Parallelization of a Hydrological Model using the massage passing Interface. Environ. Model. Softw. 2013, 43, 124–132. [Google Scholar] [CrossRef]
- Sanders, B.F. Evaluation of on-line DEMs for flood inundation modelling. Adv. Water Resour. 2007, 30, 1831–1843. [Google Scholar] [CrossRef]
- Kenward, T.; Lettenmaier, D.P.; Wood, E.F.; Fielding, E. Effects of Digital Elevation Model Accuracy on Hydrologic Predictions. Remote Sens. Environ. 2000, 3, 432–444. [Google Scholar] [CrossRef]
- Adlerab, K.K.; Tianbc, R.F.; Hongd, Y.; Piercebe, H.F. Evaluation of a Satellite-Based Global Flood Monitoring System. Int. J. Remote Sens. 2010, 31, 3763–3782. [Google Scholar]
- Manfreda, S.; McCabe, M.F.; Miller, P.E.; Lucas, R.; Pajuelo Madrigal, V.; Mallinis, G.; Ben Dor, E.; Helman, D.; Estes, L.; Ciraolo, G.; et al. On the Use of Unmanned Aerial Systems for Environmental Monitoring. Remote Sens. 2018, 10, 641. [Google Scholar] [CrossRef]
- Anornu, G.; Kabo-Bah, A.; Kortatsi, B. Comparability studies of high and low resolution Digital Elevation Models for watershed delineation in the tropics: Case of Densu river Basin of Ghana. Int. J. Coop. Stud. 2012, 1, 9–14. [Google Scholar]
- USGS. Elevation Dataset in Grid Format. Available online: https://earthexplorer.usgs.gov/ (accessed on 10 September 2015).
- USGS. Elevation Dataset in Grid Format. Available online: https://dds.cr.usgs.gov/srtm/ (accessed on 10 September 2015).
- Farr, T.G.; Kobrick, M. Shuttle Radar Topography Mission produces a wealth of data. EOS 2000, 81, 583–585. [Google Scholar] [CrossRef]
- American Society for Photogrammetry and Remote Sensing. Digital Photogrammetry—An Addendum to the Manual of Photogrammetry; Greve, C., Ed.; Publication of the American Society for Photogrammetry and Remote Sensing: Bethesda, MD, USA, 1996. [Google Scholar]
- Hanssen, R.F. Radar Interferometry: Data Interpretation and Error Analysis; Kluwer Academic Publishers: Dordrecht, The Netherlands, 2001. [Google Scholar]
- Sefercik, U.G. Performance estimation of ASTER Global DEM depending upon the terrain inclination. J. Indian Soc. Remote Sens. 2012, 40, 565–576. [Google Scholar] [CrossRef]
- Monteiro, E.V.; Fonte, C.C.; de Lima, J.L.M.P. Assessing positional accuracy of drainage networks extracted from ASTER, SRTM and OpenStreetMap. In Proceedings of the AGILE, Lisbon, Portugal, 9–12 June 2015. [Google Scholar]
- OpenStreetMap. Feature “Waterway” for a Delimited Region of United Kingdom. Available online: http://wiki.openstreetmap.org/wiki/Map_Features (accessed on 8 September 2015).
- Haklay, M.; Weber, P. OpenStreetMap: User-generated street maps. IEEE Pervasive Comput. 2008, 7, 12–18. [Google Scholar] [CrossRef]
- Mooney, P. Quality assessment of the contributed land use in information from OpenStreetMap versus authoritative datasets. In OpenStreetMap in GIScience; Jokar Arsanjani, J., Zip, A., Mooney, P., Helbich, M., Eds.; Springer International Publishing: Cham, Switzerland, 2015; pp. 319–324. [Google Scholar]
- Goodchild, M.F.; Li, L. Assuring the quality of volunteered geographic information. Spat. Stat. 2012, 1, 110–120. [Google Scholar] [CrossRef]
- Ali, A.L.; Sirilertworakul, N.; Zipf, A.; Mobasheri, A. Guided classification system for conceptual overlapping classes in OpenStreetMap. ISPRS Int. J. Geogr. Inf. 2016, 5, 87. [Google Scholar] [CrossRef]
- Mooney, P.; Minghini, M. A Review of OpenStreetMap Data. In Mapping and the Citizen Sensor; Foody, G., See, L., Fritz, S., Mooney, P., Olteanu-Raimond, A.-M., Fonte, C.C., Antoniou, V., Eds.; Ubiquity Press: London, UK, 2017; pp. 37–59. [Google Scholar] [Green Version]
- Antoniou, V.; Skopeliti, A. The Impact of the Contribution Microenvironment on Data Quality: The Case of OSM. In Mapping and the Citizen Sensor; Foody, G., See, L., Fritz, S., Mooney, P., Olteanu-Raimond, A.-M., Fonte, C.C., Antoniou, V., Eds.; Ubiquity Press: London, UK, 2017; pp. 165–196. [Google Scholar]
- Haklay, M. How good is the Volunteered Geographic Information? A Comparative Study of OpenStreetMap and Ordnance Survey datasets. Environ. Plan. B 2010, 37, 682–703. [Google Scholar] [CrossRef]
- Zielstra, D.; Zipf, A. A comparative study of proprietary geodata and volunteered Geographic Information for Germany. In Proceedings of the 13th AGILE International Conference on Geographic Information Science, Guimarães, Portugal, 11–14 May 2010. [Google Scholar]
- Ribeiro, A.; Fonte, C.C. A methodology for assessing OpenStreetMap degree of coverage for purposes of land cover mapping. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci. 2015, II-3/W5, 297–303. [Google Scholar]
- Monteiro, E.S.V.; Fonte, C.C.; de Lima, J.L.M.P. Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenStreetMap data. J. Hydrol. Hydromech. 2017, 66. [Google Scholar] [CrossRef]
- Ordnance Survey. Reference DEM of a delimited region of Great Britain. Available online: http://www.ordnancesurvey.co.uk/ (accessed on 11 May 2017).
- Mukul, M.; Srivastava, V.; Mukul, M. Analysis of the accuracy of Shuttle Radar Topography Mission (SRTM) height models using International Global Navigation Satellite System Service (IGS) Network. J. Earth Syst. Sci. 2015, 124, 1343–1357. [Google Scholar] [CrossRef]
- Santillan, J.R.; Makinano-Santillan, M. Vertical accuracy assessment of 30-m resolution ALOS, ASTER, and SRTM Global DEMs over North-eastern Mindanao, Philippines. In Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXIII ISPRS Congress, Prague, Czech Republic, 12–19 July 2016; Volume XL1-B4. [Google Scholar]
- Elkhrachy, I. Vertical accuracy assessment for SRTM and ASTER Digital Elevation Models: A case study of Najran city, Saudi Arabia. Ain Shams Eng. J. 2017. [Google Scholar] [CrossRef]
- Ordnance Survey. Rivers of a Delimited Region of Great Britain. Available online: https://www.ordnancesurvey.co.uk/business-and-government/products/os-open-rivers.html (accessed on 15 September 2015).
- Hutchinson, M.F.; Xu, T.; Stein, J.A. Recent progress in the ANUDEM Elevation Gridding Procedure. In Proceedings of the Geomorphometry, Redlands, CA, USA, 30 May 2011; pp. 19–22. [Google Scholar]
- O’Callaghan, J.F.; Mark, D.M. The extraction of drainage networks from Digital Elevation Data. Comput. Vis. Graph. Image Process. 1984, 28, 323–344. [Google Scholar] [CrossRef]
- Tarboton, D.G. A new method for the determination of flow directions and upslope areas in grid digital elevation models. Water Resour. Res. 1997, 33, 309–319. [Google Scholar] [CrossRef] [Green Version]
- Martz, L.W.; Garbrech, J. The Treatment of Flat Areas and Depressions in Automated Drainage Analysis of Raster Digital Elevation Models. Hydrol. Process. 1998, 12, 843–855. [Google Scholar] [CrossRef]
- Lin, W.T.; Chou, W.C.; Lin, C.Y.; Huang, P.H.; Tsai, J.S. WinBasin: Using Improved Algorithms and the GIS Technic for Automated Watershed Modelling Analysis from Digital Elevation Models. Int. J. Geogr. Inf. Sci. 2008, 22, 47–69. [Google Scholar] [CrossRef]
- Azeredo Freitas, H.R.; Freitas, C.C.; Rosim, S. Drainage networks and watersheds delineation derived from TIN—Based digital elevation models. Comput. Geosci. 2016, 92, 21–37. [Google Scholar] [CrossRef]
- Pelletier, J.D. A robust two-parameter method for the extraction of drainage networks from high-resolution digital elevation models (DEMs): Evaluation using synthetic and real world DEMs. Water Res. 2013, 49, 75–89. [Google Scholar] [CrossRef]
DEM i | |||||
---|---|---|---|---|---|
SRTM 30 | −6.0 | 27.5 | 28.14 | 43 | −53 |
Rebuilt DEM (rivers and streams) | −4.5 | 27.7 | 28.06 | 43 | −52 |
Rebuilt DEM (rivers) | −6.0 | 26.8 | 27.46 | 40 | −52 |
Slope Map Extracted from DEM i | (degrees) | (degrees) | (degrees) | (degrees) | (degrees) |
---|---|---|---|---|---|
SRTM 30 | 2.4 | 10.0 | 10.28 | 19 | −15 |
Rebuilt DEM (rivers and streams) | −0.4 | 10.5 | 10.51 | 18 | −18 |
Drainage Network Extracted from DEM i | RMSE (m) | ||
---|---|---|---|
SRTM 30 | 87.0 | 113.5 | 143.01 |
Rebuilt DEM (rivers and streams) | 52.9 | 98.1 | 111.5 |
Rebuilt DEM (rivers) | 76.0 | 108.9 | 132.8 |
Drainage Network Extracted from DEM i | (m) | (m) | (m) |
---|---|---|---|
SRTM 30 | 2.5 | 3.9 | 4.6 |
Rebuilt DEM (rivers and streams) | −0.03 | 4.8 | 4.8 |
Rebuilt DEM (rivers) | −0.7 | 4.7 | 4.8 |
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Monteiro, E.S.V.; Fonte, C.C.; Lima, J.L.M.P.d. Analysing the Potential of OpenStreetMap Data to Improve the Accuracy of SRTM 30 DEM on Derived Basin Delineation, Slope, and Drainage Networks. Hydrology 2018, 5, 34. https://doi.org/10.3390/hydrology5030034
Monteiro ESV, Fonte CC, Lima JLMPd. Analysing the Potential of OpenStreetMap Data to Improve the Accuracy of SRTM 30 DEM on Derived Basin Delineation, Slope, and Drainage Networks. Hydrology. 2018; 5(3):34. https://doi.org/10.3390/hydrology5030034
Chicago/Turabian StyleMonteiro, Elisabete S.V., Cidália C. Fonte, and João L.M.P. de Lima. 2018. "Analysing the Potential of OpenStreetMap Data to Improve the Accuracy of SRTM 30 DEM on Derived Basin Delineation, Slope, and Drainage Networks" Hydrology 5, no. 3: 34. https://doi.org/10.3390/hydrology5030034