Investigating the LIDAR and radar data accuracy in the Sub-watersheds and their characteristics extraction in comparison with common methods by digital elevation model | ||
| مهندسی و مدیریت آبخیز | ||
| Article 20, Volume 11, Issue 4, January 2020, Pages 1075-1085 PDF (637.19 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.22092/ijwmse.2019.123784.1561 | ||
| Authors | ||
| Behrooz Mohseni* 1; Benyamin Matinnia2; Hadi Razzaghian3 | ||
| 1Scientific Board, Payam Noor University, Tehran, Iran | ||
| 2MSc | ||
| 3Assistant Professor, Payam Noor University, Tehran, Iran | ||
| Abstract | ||
| Determining the precise location of sub-watersheds in flood production is very important. In some cases, it is time consuming and costly to do this by conducting field studies and mapping topographic maps. Today, the new and growing technology of LIDAR active sensor data is used to collect data from the ground surface, which operate based on measuring the distance of the laser. In this research, Gorgan Shast-Kalateh forest basin was selected due to various data. In order to prepare sub-watersheds and their characteristics, it is necessary to have a digital elevation model. In the above model, LIDAR and radar data and other sensors were used with spatial resolutions of 1, 12.5 and 30 m, respectively to control the ground data. The streams were extracted using the appropriate model in each method and all types of watershed characteristics were obtained through Arc-Hydro and IDRISI software. The distance index of each stream from others and ground reality were investigated. Comparison of analyses was done in SPSS software. The sig-value for comparing altitudes along the streams for LIDAR with a pairwise t test was 0.13, which shows no significant difference. Comparison of the streams of different digital models between the land 12.5th m and 30th m and LIDAR, the sig-value of 0.002 in Wilcoxon test, shows significant difference. Also, based on the overall conclusion, it was observed that there is a significant difference at 95% probability level, between the methods used. Eventually, LIDAR data had the highest accuracy with ground reality. | ||
| Keywords | ||
| Arc- hydro; IDRISI; Laser; Shast-Kalateh; Wilcoxon test | ||
| References | ||
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