Preliminary Study of Total Suspended Solid Distribution in Coastal Ujung Pangkah Gresik Based Reflectance Value of Landsat Satellite Imagery
Hendrata Wibisana(1*), Bangun Muljo Soekotjo(2), Umboro Lasminto(3)
(1) Universitas Pembangunan Nasional "Veteran" Jawa Timur
(2) Geomatics Engineering ITS Surabaya
(3) Civil Engineering ITS Surabaya
(*) Corresponding Author
Abstract
Total suspended solid (TSS) is one of the parameters that uses for detecting health in aquatic environments. The distribution of the TSS value in the water body will affect the aquatic ecosystem. In this research will be analyzed the distribution value of TSS during 5 year period by utilizing Landsat 8 satellite image data, where the developed method is extraction of reflectance value from Landsat 8 satellite image for 5 years using SEADASS and then compiled the TSS algorithm with reflectance value that already obtained on the existing conditions, the algorithm obtained is estimated over 5 years back to get a picture of change and distribution of TSS value. As a case study , the coast of Ujung Pangkah Gresik was taken which has the mouth of the river Bengawan Solo. The results obtained from this study illustrate the decrease of TSS value during that time period, so that with this decrease can be concluded that at the point of field coordinate, TSS value was decreasing and causing the erosion in the environment.
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Baxter, T. E. (2017). Standard Operating Procedure Total Dissolved Solids by Gravimetric Determination. Retrieved from https://www.cefns.nau.edu/~teb/ambl/sop/SOP_AMBL_105B_TotalDissolvedSolids.pdf
Cavalli, R. M. (2017). Retrieval of Sea Surface Temperature from MODIS Data in Coastal Waters. https://doi.org/10.3390/su9112032
Chen, S., Han, L., Chen, X., Li, D., Sun, L., & Li, Y. (2015). Estimating wide range Total Suspended Solids concentrations from MODIS 250-m imageries: An improved method. ISPRS Journal of Photogrammetry and Remote Sensing, 99, 58–69. https://doi.org/10.1016/j.isprsjprs.2014.10.006
Claverie, M., Vermote, E. F., Franch, B., & Masek, J. G. (2015). Evaluation of the Landsat-5 TM and Landsat-7 ETM+ surface reflectance products. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2015.08.030
DAAC, N. L. (2017). Landsat 8 OLI Level 1 Precision Terrain Corrected Registered At-Sensor Radiance. Retrieved from https://lpdaac.usgs.gov/citing_our_data
Dorji, P., & Fearns, P. (2016). A quantitative comparison of total suspended sediment algorithms: A case study of the last decade for MODIS and landsat-based sensors. Remote Sensing, 8(10). https://doi.org/10.3390/rs8100810
Dunn, R., Zigic, S., Burling, M., & Lin, H.-H. (2015). Hydrodynamic and Sediment Modelling within a Macro Tidal Estuary: Port Curtis Estuary, Australia. Journal of Marine Science and Engineering, 3(3), 720–744. https://doi.org/10.3390/jmse3030720
Erener, A., & Yakar, M. (2012). Monitoring Coastline Change Using Remote Sensing and GIS Technologies. International Conference on Earth Science and Remote Sensing, 30, 310–315.
Guillou, N., Rivier, A., Gohin, F., & Chapalain, G. (2015). Modeling Near-Surface Suspended Sediment Concentration in the English Channel. Journal of Marine Science and Engineering, 3(2), 193–215. https://doi.org/10.3390/jmse3020193
Hou, X., Feng, L., Duan, H., Chen, X., Sun, D., & Shi, K. (2017). Fifteen-year monitoring of the turbidity dynamics in large lakes and reservoirs in the middle and lower basin of the Yangtze River, China. Remote Sensing of Environment, 190, 107–121. https://doi.org/10.1016/J.RSE.2016.12.006
Hwang, D.-J., Choi, J.-K., Ryu, J.-H., & Frouin, R. (2018). Estimating GOCI daily PAR and validation. In R. J. Frouin & H. Murakami (Eds.), Remote Sensing of the Open and Coastal Ocean and Inland Waters (p. 4). SPIE. https://doi.org/10.1117/12.2500061
Kari, E., Kratzer, S., Beltrán-Abaunza, J. M., Harvey, E. T., & Vaičiūtė, D. (2017). Retrieval of suspended particulate matter from turbidity – model development, validation, and application to MERIS data over the Baltic Sea. International Journal of Remote Sensing, 38(7), 1983–2003. https://doi.org/10.1080/01431161.2016.1230289
Ozesmi, S. L., & Bauer, M. E. (2002). Satellite remote sensing of wetlands. Wetlands Ecology and Management, 10(5), 381–402. https://doi.org/10.1023/A:1020908432489
Shuchman, R. A., Leshkevich, G., Sayers, M. J., Johengen, T. H., Brooks, C. N., & Pozdnyakov, D. (2013). An algorithm to retrieve chlorophyll, dissolved organic carbon, and suspended minerals from Great Lakes satellite data. Journal of Great Lakes Research, 39(S1), 14–33. https://doi.org/10.1016/j.jglr.2013.06.017
Siripong, A. (n.d.). DETECT THE COASTLINE CHANGES IN THAILAND BY REMOTE SENSING. Retrieved from http://www.isprs.org/proceedings/xxxviii/part8/pdf/W09O24_20100226133356.pdf
Sullivan, D. G., White, J. G., & Vepraskas, M. J. (2017). Using Land-Use Change, Soil Characteristics, and a Semi-Automated On-Line GIS Database to Inventory Carolina Bays. Wetlands, 37(1), 89–98. https://doi.org/10.1007/s13157-016-0842-8
Tan, C. W., Thishalini, A., Goh, E. G., & Edlic, S. (2017). Studies on turbidity in relation to suspended solid, velocity, temperature, pH, conductivity, colour and time. ARPN Journal of Engineering and Applied Sciences, 12(19), 5626–5635.
Thiruvenkatasamy, K., & Baby Girija, D. K. (2014). Shoreline evolution due to construction of rubble mound jetties at Munambam inlet in Ernakulam-Trichur district of the state of Kerala in the Indian peninsula. Ocean and Coastal Management. https://doi.org/10.1016/j.ocecoaman.2014.09.026
Wang, C., Chen, S., Li, D., Wang, D., Liu, W., & Yang, J. (2017). A Landsat-based model for retrieving total suspended solids concentration of estuaries and coasts in China, 105194, 4347–4365. https://doi.org/10.5194/gmd-10-4347-2017
Wibisana, H., Sukojo, B. M., & Lasminto, U. (2018). PENENTUAN MODEL MATEMATIS YANG OPTIMAL SUHU PERMUKAAN LAUT DI PANTAI UTARA GRESIK BERBASIS NILAI REFLEKTAN CITRA SATELIT AQUA MODIS. GEOMATIKA, 24(1), 31. https://doi.org/10.24895/JIG.2018.24-1.771
Zhang, F. F., Zhang, B., Li, J. S., Shen, Q., Wu, Y., & Song, Y. (2011). Comparative analysis of automatic water identification method based on multispectral remote sensing. Procedia Environmental Sciences, 11(PART C), 1482–1487. https://doi.org/10.1016/j.proenv.2011.12.223
DOI: https://doi.org/10.22146/ijg.38967
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