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Dian Adhetya Arief
Lecturer Study Program D3 Remote Sensing Technology, Universitas Negeri Padang
Astronomy Computer Science & IT Earth & Planetary Sciences Education

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UTILIZATION OF REMOTE SENSING IMAGES IN MAPPING SUSPENDED SOLID IN LAKE MANINJAU WEST SUMATRA PROVINCE Ilham Ridho; Dian Adhetya Arief; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 2 No 1 (2021): international remote sensing application journal (June Edition 2021)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.271 KB) | DOI: 10.24036/irsaj.v2i1.20

Abstract

Remote sensing is generally defined as the technical art of obtaining information or data regarding the physical condition of an object or object, target, target or area and phenomenon without touching or direct contact with the object or target (Soenarmo, 2009). With remote sensing data, this research can easily see how the condition of the lake water. Based on these factors, efforts are needed to monitor the distribution of TSS in Lake Maninjau considering the importance of water potential to support various needs. In this study the classification was divided into 5 for the first class with concentration values of tss- 0 – 15 mg/L, 15 – 25 mg/L, 25 – 35 mg/L, TSS 35 – 80 mg/L, TSS > 80 mg/L. The result of in situ data processing is the lowest value is 8.2 mg/L and the highest is 72.2 mg/L. The Syarif Budhiman algorithm has the lowest at 8.14 mg/L and the highest at 40.04 mg/L. The lowest Parwati algorithm is 3.32 mg/L and the highest is 32.86 mg/L. The Guzman - Santaella algorithm has the lowest at 3.15 mg/L and the highest at 164.38 mg/L. The TSS concentrations in the alleged party and budhiman algorithms tend to have the same pattern as the TSS concentrations in the field, but there are several points with significant differences. The validation test shows that the Budhiman Algorithm (2004) has the smallest NMAE value between in situ data and image processing with a value of 14.4%.
DYNAMIC OF CHANGING AREA OF SUSPENDED SOLID BY UTILIZING LANDSAT 8 OIL IMAGES IN LAKE SINGKARAK, WEST SUMATRA PROVINCE, 2017 and 2022 Indra Kurniawan; Dian Adhetya Arief
International Remote Sensing Applied Journal Vol 2 No 2 (2021): international remote sensing application journal (Dec Edition 2021)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (479.152 KB) | DOI: 10.24036/irsaj.v2i2.26

Abstract

TSS is suspended materials (diameter > 1 µm) retained on a millipore filter with a pore diameter of 0.45 µm. TSS consists of silt and fine sand and micro-organisms. The main cause of TSS in waterways is soil erosion or soil erosion that is carried into water bodies. If the TSS concentration is too high, it will inhibit the penetration of light into the water and result in disruption of the photosynthesis process (Effendi in Lestari, 2009:4). Many activities cause turbidity that affects the penetration of sunlight into water bodies, so it can hinder the process of photosynthesis and primary production of waters. Turbidity usually consists of an organic particle originating from watershed erosion and resuspension from the lake bottom. Keywords : Normalized Difference Vegetation Index, Normalized Burn Ratio, Landsat 8, Severity Level of Forest and Land Fires. Based on the results of the study, researchers have obtained TSS values ​​in 2017 and 2022 at Lake Singkarak with the Landsat 8 image data processing method using the Syarif Budiman algorithm with several stages, namely first combining image data bands from band 1 to band 7 then cropping which serves to determine the area to examine then performs masking which functions to separate land from water and then enter the Syarif Budiman algorithm formula then classify the TSS values ​​in Lake Singkarak. It can be seen that the predicted TSS concentration has not been too much different from the TSS concentration in the field. researchers have obtained TSS values ​​in 2017 and 2022 at Lake Singkarak with the Landsat 8 image data processing method using the Syarif Budiman algorithm with several stages, namely first combining image data bands from band 1 to band 7 then cropping which functions to determine the area which will be examined then do masking which functions to separate land from water and then enter the Syarif Budiman algorithm formula then classify the TSS values ​​in Lake Singkarak. It can be seen that the predicted TSS concentration has not had too much difference in the concentration in the field. researchers have obtained TSS values ​​in 2017 and 2022 at Lake Singkarak with the Landsat 8 image data processing method using the Syarif Budiman algorithm with several stages, namely first combining image data bands from band 1 to band 7 then cropping which functions to determine the area which will be examined then do masking which functions to separate land from water and then enter the Syarif Budiman algorithm formula then classify the TSS values ​​in Lake Singkarak. It can be seen that the predicted TSS concentration has not to have o much difference with wififrameS concentration in the field.
Co-Authors Ilham Ridho Indra Kurniawan Sri Kandi Putri