نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مهندسی منابع آب، دانشگاه بین المللی امام خمینی (ره)، قزوین، ایران

2 استادیار، گروه مهندسی آب، دانشکده کشاورزی و منابع طبیعی، دانشگاه بین المللی امام خمینی، قزوین، ایران

چکیده

مدلهای رقومی ارتفاعی (DEMs) از روشهای متداول برای نمایش تغییرات توپوگرافی سطح زمین هستند، که با توجه به هزینه بالای تهیه نقشههای توپوگرافی زمینی، از کاربرد بسیار زیادی در زمینههای مختلف برخوردار میباشند. پژوهش حاضر با هدف بررسی کارایی منابع ارتفاعی با توان تفکیک مکانی مختلف در  کاربریهای گوناگون دو استان قزوین و مازندران به انجام رسیده است. در این تحقیق برای ارزیابی منابع ارتفاعی 30 متریASTER، SRTM و 90 متری SRTM از دادههای GPS دو فرکانسه (داده مبنا) استفاده شد و بر اساس شاخصهای آماری همچون STD،RMSE، MD و MAD دقت ارتفاعی این منابع در سطح هر دو استان و در کاربریهای مختلف بررسی گردید. نتایج بهدست آمده حاکی از آن است که DEM 30متری SRTM از قابلیت به مراتب مناسبتری در تخمین رقوم ارتفاعی برخوردار میباشد. به طوریکه شاخص RMSE این منبع در هردو بازه استان قزوین و مازندران به ترتیب برابر با 3.8 و 5.8 متر میباشد. همچنین ارزیابی دقت ارتفاعی منابع مختلف در کاربریهای گوناگون حاکی از عملکرد قابل قبول منبع 30 متری SRTM در اکثر کاربریها و پوششها به غیر از نواحی کوهستانی و جنگلی میباشد. علت اصلی این عملکردِ پائین به ویژه در اراضی با پوشش جنگلی، عدم نفوذ امواج راداری در سطوح دارای پوشش و همچنین تراکم کم دادههای برداشت شده توسط سنجنده SRTM میباشد. منبع ارتفاعی 90 متریSRTM نیز علیرغم دارا بودن توان تفکیک پائین از عملکرد به مراتب بهتری نسبت به منبع 30 متری ASTER برخوردار میباشند. در یک جمعبندی کلی میتوان چنین عنوان نمود که منبع ارتفاعیSRTM-30m میتواند در حوضههای فاقد آمار زمینیِ مناسب و یا با کمبود آمار بسیار راهگشا باشد. البته لازم بهذکر است که با توجه به تأثیر قابل توجه نوع پوشش گیاهی بر دقت ارتفاعی این منابع، توصیه میشود تا بهمنظور حصول نتایج قابلاطمینانتر، در ابتدا با توجه به نوع پوشش گیاهی موجود در محدوده مطالعاتی به انتخاب منبع ارتفاعی مناسب اقدام شده و سپس با استفاده از دادههای زمینی (نقاط کنترل زمینی)، مقادیر ارتفاعی اصلاح شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Assessing vertical accuracy of remotely sensed DEMs in different land uses

نویسندگان [English]

  • Sakine Koohi 1
  • Asghar Azizian 2

1 Ph.D. student in Water Resources Engineering, Water engineering Dept., Imam Khomeini International University, Qazvin, Iran

2 Assistant Professor, Water Engineering Department, Faculty of Agriculture and Natural Resources, Imam Khomeini International University, Qazvin, Iran

چکیده [English]

Extended Abstract
Introduction
Due to the high costs of land surveying, remotely sensed digital elevation models (DEMs) are a common method used to demonstrate topographic variations of the land surface. Generally, these DEM datasets are freely accessible to engineers and researchers covering most parts of the world in different spatial resolutions. DEMs can be classified into two categories of high (small pixel size) and low (large pixel size) resolution DEMs. Several studies have addressed the vertical accuracy of different digital elevation datasets especially in countries lacking access to high quality ground-based data. Despite the widespread application of these products, vertical accuracy of these datasets in different land uses has not been addressed in Iran and most engineering studies use 1:1000 and 1:2000 topographic maps which are very expensive and time-consuming to obtain. The present study seeks to assess vertical accuracy of different resolution DEM datasets used to estimate elevation in various land uses in two Iranian provinces of Qazvin (urban, agricultural lands, garden, and forest, mountainous areas, plains, and rivers) and Mazandaran (urban, agricultural, forest/mountain, plains, and rivers).
 
Materials & Methods
ASTER and SRTM DEMs with a resolution of 30-meter and SRTM DEM with a resolution of 90 m resolution were collected in the present study to investigate their vertical accuracy in various land uses of Qazvin and Mazandaran provinces. Several topographic maps and GPS based datasets of the study areas were also investigated for a better assessment of these DEM datasets. Finally, common statistical measures such as standard deviation (SD), mean absolute difference (MAD) and root mean square error (RMSE) were used to compare remotely sensed DEMs with ground-based observations.
 
Results & Discussion
Findings indicated that 30m SRTM DEMs showed a better agreement with ground-based observations in both study areas. RMSE of this dataset in Qazvin and Mazandaran provinces equaled 3.8m and 5.8 m, respectively. Results also indicated that in 30m SRTM DEM, 87% of points in Qazvin and 79.7% of points in Mazandaran provinces showed a lower than 5m mean absolute difference (MAD), while in the case of 30m ASTER DEM 79% of points in Qazvin and 53% of points in Mazandaran showed a lower than 5m mean absolute difference (MAD). For 90m STRM DEM, around 29% of points in Qazvin and 74% of points in Mazandaran showed a lower than 5m mean absolute difference (MAD). Although 90m SRTM DEM did not work efficiently in Qazvin province, its result in Mazandaran province was almost as efficient as 30m SRTM dataset. Assessing the vertical accuracy of different elevation datasets in different land uses indicated that 30m SRTM showed an acceptable result in most land uses except for mountainous areas and forests. This was mainly due to forest canopies blocking the radio waves penetrating such areas and low density of points generated by STRM sensors. Moreover, 30m ASTER did not show an acceptable result in most land uses except for plains in Qazvin along with urban and agricultural land uses in Mazandaran. Despite having a lower resolution, 90m SRTM worked better than 30m ASTER. However, 90m SRTM showed considerable errors in mountainous, urban and forest land uses, and therefore it shall not be used in such areas.
 
Conclusion
Results indicated that 30m STRM DEM is a valuable resource which makes elevation estimation for areas lacking ground-based information possible. Moreover, the type of land cover has a significant effect on the vertical accuracy of elevation datasets and thus, increased vegetation results in decreased accuracy of DEM datasets. Therefore depending on the land cover type in the study area, ground control points can be used along with remotely sensed DEMs to decrease errors.

کلیدواژه‌ها [English]

  • Digital Elevation Models (DEMs)
  • Remote sensing
  • Elevation
  • Land use
1- Amans, O. C., Beiping, P. W., & Ziggah, Y. Y. (2014). Assessing Vertical Accuracy of SRTM Ver 4 . 1 and ASTER GDEM Ver 2 Using Differential GPS Measurements – Case Study in Ondo State. International Journal of Scientific & Engineering Research, 4(12), 523–531.
2- Azizian, A. (2018). Investigating the Application of Remote-Sensing Based DEMs on Flood Inundation Mapping and Hydraulic Modeling (In Persian). Iran-WaterResourcesResearch.
3- Bhang, K. J., & Schwartz, F. (2008). Limitations in the Hydrologic Applications of C-Band SRTM DEMs in Low-Relief Settings. IEEE Geoscience. Remote Sensing, 5(3), 497–501.
4- del Rosario González-Moradas, M., & Viveen, W. (2020). Evaluation of ASTER GDEM2, SRTMv3.0, ALOS AW3D30 and TanDEM-X DEMs for the Peruvian Andes against highly accurate GNSS ground control points and geomorphological-hydrological metrics. Remote Sensing of Environment, 237. https://doi.org/10.1016/j.rse.2019.111509
5- Elkhrachy, I. (2016). Vertical accuracy assessment for SRTM and ASTER Digital Elevation Models: A case study of Najran city, Saudi Arabia. Ain Shams Engineering Journal, 2. https://doi.org/10.1016/j.asej.2017.01.007
6- Falorni, G., Teles, V., Vivoni, E. R., Bras, R. L., & S., A. K. (2005). Analysis and characterization of the vertical accuracy of digital elevation models from the Shuttle Radar Topography Mission. JOURNAL OF GEOPHYSICAL RESEARCH, 10.
7- Fan, X. T., Du, X. P., Tan, J., & Zhu, J. J. (2009). Three-dimensional visualization simulation assessment system based on multi-source data fusion for the Wenchuan earthquake. Journal of Applied Remote Sensing, 3(May), 1–9. https://doi.org/10.1117/1.3154425
8- Gamba, P., Acqua, F. D., & Houshmand, B. (2002). SRTM data characterization in urban areas. International Archives of Photogrammetry, 1–4.
9- Gesch, D., Oimoen, M., Zhang, Z., Meyer, D., & Danielson, J. (2012). Validation of the Aster Global Digital Elevation Model Version 2 Over the Conterminous United States. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B4(September), 281–286.https://doi.org/10.5194/isprsarchives-XXXIX-B4-281-2012
10- Gorokhovich, Y., & Voustianiouk, A. (2006). Accuracy assessment of the processed SRTM-based elevation data by CGIAR using field data from USA and Thailand and its relation to the terrain characteristics. Journal of Remote Sensing of Environment, 104(4), 409–415.
11- Hinkel, J., Lincke, D., Vafeidis, A. T., Perrette, M., Nicholls, R. J., Tol, R. S. J., … Levermann, A. (2014). Coastal flood damage and adaptation costs under 21st century sea-level rise. Proceedings of the National Academy of Sciences, 111(9), 3292–3297. https://doi.org/10.1073/pnas.1222469111
12- Kolecka, N., & Kozak, J. (2013). Assessment of the Accuracy of SRTM C- and X-Band High Mountain Elevation Data: a Case Study of the Polish Tatra Mountains. Pure and Applied Geophysics.
13- Miliaresis, G. C. (2008). The Land Cover Impact on the Aspect/Slope Accuracy Dependence of the SRTM-1 Elevation Data for the Humboldt Range. Sensors, 8, 3134–3149.
14- Montgomery, D. C., Peck, E. A., & Vining, G. G. . (1981). Introduction to linear regression analysis. 504.
Nadi, S., Ghiasi, Y., & Hadavand, S. (2016). Vertical Accuracy Assessment of SRTM and GDEM Open Source Digital Elevation Models and Error Propagation for Slope and Aspect Maps. Journal of Geomatics Science and Technology, 6(2), 99–118.
15- Pakoksung, K., & Takagi, M. (2016). Digital elevation models on accuracy validation and bias correction in vertical. Modeling Earth Systems and Environment, 2(1), 11. https://doi.org/10.1007/s40808-015-0069-3
16- Peralvo, M. (2017). Influence of DEM Interpolation Methods in Drainage Analysis.December.
17- Sanders, B. F. (2007). Evaluation of on-line DEMs for flood inundation modeling. Advances in Water Resources, 30(8), 1831–1843. https://doi.org/10.1016/j.advwatres.2007.02.005
18- Santillan, J. R., & Makinano-Santillan, M. (2016). Vertical accuracy assessment of 30-M resolution ALOS, ASTER, and SRTM global DEMS over Northeastern Mindanao, Philippines. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 41(July), 149–156. https://doi.org/10.5194/isprsarchives-XLI-B4-149-2016
19- Shokoohi, A., & Azizian, A. (2014). Evaluating the effects of topographic and radar based DEMs on the simulation results of geomorphologic model (In Persian). Journal of Watershed Engineering and Management, 6(January), 52–62.
20- Su, Y., Guo, Q., Ma, Q., & Li, W. (2015). SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery. Remote Sensing, 7(9), 11202–11225.
21- Su, Y., Ma, Q., & Q., G. (2017). Fine-Resolution Forest Tree Height Estimation across the Sierra Nevada through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery. International Journal of Digital Earth, 10(3), 307–323.
22- Thomas, J., Joseph, S., Thrivikramji, K. P., & Arunkumar, K. S. (2014). Sensitivity of digital elevation models: The scenario from two tropical mountain river basins of the Western Ghats, India. Geoscience Frontiers, 5(6), 893–909. https://doi.org/10.1016/j.gsf.2013.12.008
23- Wolock, D. M., & Price, C. V. (1994). Effects of Digital Elevation Model map scale and data resolution on a topographic based watershed. Water Resources Research, 30(11), 3041–3052. https://doi.org/10.1029/94WR01971
24- Zhao, X., Su, Y., Hu, T., Chen, L., Gao, S., Wang, R., … Guo, Q. (2018). A global corrected SRTM DEM product for vegetated areas. Remote Sensing Letters, 9(4), 393–402. https://doi.org/10.1080/2150704X.2018.1425560