Evaluation of indicators of remote sensing measurement in quantitative and qualitative studies of surface water with Landsat-8 satellite images (Case study: South of Khuzestan province)

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MIR ALIZADEHFARD S.R.; MANSOURI S.

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Journal: Journal of RS and GIS for Natural Resources Year:2019 | Volume:10 | Issue:2 (35) Page(s): 63-84

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Title

Evaluation of indicators of remote sensing measurement in quantitative and qualitative studies of surface water with Landsat-8 satellite images (Case study: South of Khuzestan province)

Author(s)

MIR ALIZADEHFARD S.R. | MANSOURI S. | Issue Writer Certificate

Keywords

Surface waterQ1

Jarahi-Zohreh riverQ1

Karun riverQ1

LandsatQ1

KhuzestanQ2

Abstract

Water as one of the most basic needs of our present life and the extent of our use in drinking, agriculture, industry, economic, social, and political-security politics make us to identify with minimal cost savings and time characteristics of the watersheds, rivers and water levels by various methods, including the use of satellite imagery. The purpose of this research was to evaluate the methods of detecting zones, water levels and rivers with indicators; Normalized difference vegetation index, Enhanced vegetation index, Soli adjusted vegetation index, Normalized difference water index, Modified normalized difference water index, Automated water extraction index, Automated water extraction index and Unsupervised IsoClusterc and supervised Maximum likelihood classification methods to identification waters basin and the Optimum factor index for identifying the quality of water in terms of salinity, as well as determination infiltrate tabs water entering the larger zones in the part of the basins of the Karun river, Jarahi-Zohreh in the southern province of Khuzestan, with Landsat-8 satellite Land Earth Observations sensor. The results of the study showed that the automatic indicators of the extraction of water in shadow and urban areas are more effective than other indicators because of the consideration of short-range infrared wavelengths in water identification. With the results of the Supervised classification method, they were Maximum likelihood to the Kappa coefficient of the same 94% and the same performance. The results of the Optimum factor Index indicator for the detection of salinity water and the determination infiltrate tabs water Show the most useful information and remove duplicate image banding data the Landsat-8 satellite Earth Observation Sensor was 79. 10% for the color combination RGB of 651.

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APA: Copy

MIR ALIZADEHFARD, S.R., & MANSOURI, S.. (2019). Evaluation of indicators of remote sensing measurement in quantitative and qualitative studies of surface water with Landsat-8 satellite images (Case study: South of Khuzestan province). JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE), 10(2 (35) ), 63-84. SID. https://sid.ir/paper/189460/en

Vancouver: Copy

MIR ALIZADEHFARD S.R., MANSOURI S.. Evaluation of indicators of remote sensing measurement in quantitative and qualitative studies of surface water with Landsat-8 satellite images (Case study: South of Khuzestan province). JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE)[Internet]. 2019;10(2 (35) ):63-84. Available from: https://sid.ir/paper/189460/en

IEEE: Copy

S.R. MIR ALIZADEHFARD, and S. MANSOURI, “Evaluation of indicators of remote sensing measurement in quantitative and qualitative studies of surface water with Landsat-8 satellite images (Case study: South of Khuzestan province),” JOURNAL OF RS AND GIS FOR NATURAL RESOURCES (JOURNAL OF APPLIED RS AND GIS TECHNIQUES IN NATURAL RESOURCE SCIENCE), vol. 10, no. 2 (35) , pp. 63–84, 2019, [Online]. Available: https://sid.ir/paper/189460/en

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