Dam sediment tracking using spectrometry and Landsat 8 satellite image, Taleghan Basin, Iran

被引:0
作者
Sirous Afshar
Abolfazl Shamsai
Bahram Saghafian
机构
[1] Islamic Azad University,Department of Civil Engineering, Science and Research Branch
来源
Environmental Monitoring and Assessment | 2016年 / 188卷
关键词
Sedimentation; Remote sensing; Landsat 8; X-ray diffraction; MTMF;
D O I
暂无
中图分类号
学科分类号
摘要
Sedimentation in reservoirs, in addition to reducing water storage capacity, causes serious environmental impacts including intensification of river erosion. Detection of sediment origins plays a determining role in control and prevention of sedimentation. Nowadays, with the help of studies on sedimentation and erosion, sediment origins can be detected with high accuracy. This research integrated geographic information system (GIS) and remote sensing (RS) techniques to detect the primary source of sediment to Taleghan Dam in northern Iran. After collecting samples of sediment from the basin outlet, they were divided into two parts. One part was sent to the Mineralogy Laboratory in order to determine the percentage of each mineral in the samples using X-ray. A few were sent to the Spectroscopy Laboratory to determine their spectral signature using the spectrometer. The laboratory test results determined the wavelength of the minerals. In the next step, those spots on the satellite image whose spectral reflectance fell within the spectral signature of the minerals were detected and enhanced by mixture-tuned matched filtering (MTMF) method. These spots were overlapped with the map of geological formations. Accordingly, the origin of the minerals was detected. The greatest proportion of trace minerals was found in sample 4 including 6 % of Illite trace mineral, while sample 2 contains only 2 % of trace minerals. Accordingly, the origin of the minerals was detected. The obtained results revealed that mudstone, red siltstone, and conglomerate formations, Karaj formation in section Poldokhtar, acidic tuffs, alcanic lavas of Karaj Formation, mudstone and gypsum of upper red formation, and Cambrian dolomites were recognized as the most possible origins of the dam sediments. These formations are vulnerable to erosion and should be conserved so as to substantially prevent the volume of sedimentation in the reservoir.
引用
收藏
相关论文
共 50 条
  • [21] Satellite-based streamflow simulation using CHIRPS satellite precipitation product in Shah Bahram Basin, Iran
    Mokhtari, Shirin
    Sharafati, Ahmad
    Raziei, Tayeb
    ACTA GEOPHYSICA, 2022, 70 (01) : 385 - 398
  • [22] Satellite-based streamflow simulation using CHIRPS satellite precipitation product in Shah Bahram Basin, Iran
    Shirin Mokhtari
    Ahmad Sharafati
    Tayeb Raziei
    Acta Geophysica, 2022, 70 : 385 - 398
  • [23] Extracting clay minerals with emphasis on Bentonite in Eastern Iran, using Landsat 8 and ASTER images
    Saadat, Saeed
    Ghoorchi, Maliheh
    Dabiri, Rahim
    IRANIAN JOURNAL OF EARTH SCIENCES, 2023, 15 (03): : 188 - 194
  • [24] Land cover mapping using Landsat satellite image classification in the Classical Karst - Kras region
    Kokalj, Ziga
    Ostir, Kristof
    ACTA CARSOLOGICA, 2007, 36 (03) : 433 - 440
  • [25] Inversion of corn leaf area index using terrestrial laser scanning data and Landsat8 image
    Zhang, Mingzheng
    Su, Wei
    Wang, Ruiyan
    Zhongguo Jiguang/Chinese Journal of Lasers, 2015, 42 (11):
  • [26] Forest Fire Characterization Using Landsat-8 Satellite Data in Dalma Wildlife Sanctuary
    Chaudhary S.K.
    Pandey A.C.
    Parida B.R.
    Remote Sensing in Earth Systems Sciences, 2022, 5 (4) : 230 - 245
  • [27] Evaluating the potential of sentinel-2, landsat-8, and irs satellite images in tree species classification of hyrcanian forest of iran using random forest
    Soleimannejad, Leila
    Ullah, Sami
    Abedi, Roya
    Dees, Matthias
    Koch, Barbara
    JOURNAL OF SUSTAINABLE FORESTRY, 2019, 38 (07) : 615 - 628
  • [28] Machine Learning Algorithms for Satellite Image Classification Using Google Earth Engine and Landsat Satellite Data: Morocco Case Study
    Ouchra, Hafsa
    Belangour, Abdessamad
    Erraissi, Allae
    IEEE ACCESS, 2023, 11 : 71127 - 71142
  • [29] Using Landsat-8 Images for Quantifying Suspended Sediment Concentration in Red River (Northern Vietnam)
    Quang Vinh Pham
    Nguyen Thi Thu Ha
    Pahlevan, Nima
    La Thi Oanh
    Thanh Binh Nguyen
    Ngoc Thang Nguyen
    REMOTE SENSING, 2018, 10 (11)
  • [30] Fuel type mapping using object-based image analysis of DMC and Landsat-8 OLI imagery
    Stefanidou, A.
    Dragozi, E.
    Stavrakoudis, D.
    Gitas, I. Z.
    GEOCARTO INTERNATIONAL, 2018, 33 (10) : 1064 - 1083