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All Journal Jurnal Sains Teknologi dan Lingkungan (JSTL)
Niechi Valentino
Program Studi Kehutanan, Fakultas Pertanian, Universitas Mataram
Agriculture, Biological Sciences & Forestry Computer Science & IT Public Health

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Identifikasi Sebaran Spasial dan Kerapatan Mangrove Gili Lawang menggunakan Citra Landsat 9 OLI-2/TIRS-2: Identification Gili Lawang Mangrove Spatial Distribution and Density with Landsat 9 OLI-2/TIRS-2 Imagery Andrie Ridzki Prasetyo; Niechi Valentino; Muhammad Anwar Hadi
JURNAL SAINS TEKNOLOGI & LINGKUNGAN Vol. 9 No. 2 (2023): JURNAL SAINS TEKNOLOGI & LINGKUNGAN
Publisher : LPPM Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jstl.v9i2.450

Abstract

Mangrove ecosystems have a great influence on the sustainability of human life and the environment. The high level of vulnerability of mangrove ecosystems has implications for the importance of quality planning. This study aims to identify the spatial distribution and density of mangrove forests in Gili Lawang using Landsat 9 OLI-2/TIRS-2 satellite imagery. Data processing is done with the help of the QGIS 3.30 application. Data processing consists of band combinations, image classification with the SVM algorithm, classification results accuracy test, NDVI value extract, and reclass NDVI. The results showed that the use of band 564 in Landsat 9 imagery visually resulted in an increase in sharpness in identifying mangrove ecosystems. Classification of objects with the SVM algorithm has overall accuracy and kappa accuracy > 80%. The identified area of Gili Lawang is 432.72 ha, consisting of 37.89 ha of mangroves, 58.11 ha of non-mangrove and 3.75 ha of water bodies. NDVI values at the study sites ranged from 0.068 to 0.87. The maximum NDVI value is found in mangrove objects, while the minimum NDVI value is found in water body objects. Mangrove density in Gili Lawang is dominated by high and very high density. The use of Landsat 9 OLI-2/TIRS-2 imagery in the future is expected to provide positive benefits in providing data and information related to natural resources.  
Estimasi Simpanan Karbon Tegakan Menggunakan Citra Sentinel-2A Pada Kawasan Mangrove Labuan Tereng Kabupaten Lombok Barat: Estimation of Standing Carbon Stock Using Sentinel-2A Imagery in the Labuan Tereng Mangrove Area West Lombok Regency Moh Rodiansyah Hambali; Andi Chairil Ichsan; Niechi Valentino; Andrie Ridzki Prasetyo
JURNAL SAINS TEKNOLOGI & LINGKUNGAN Vol. 9 No. 4 (2023): JURNAL SAINS TEKNOLOGI & LINGKUNGAN
Publisher : LPPM Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jstl.v9i4.522

Abstract

The primary worry in addressing climate change problems is the elevation in global temperatures resulting from the growing levels of CO2 emissions in the atmosphere. Mangrove ecosystems contribute to the "blue carbon" plan which is capable of storing carbon well, this research was conducted to assess carbon storage within the mangrove forest ecosystem by combining Sentinel-2A satellite imagery with on-site field measurements. The data analysis findings indicate the presence of six distinct mangrove varieties, namely R. mucronata, A. marina, R. apiculata, S. alba, E. agallocha, and C. decandra. The R. mucronata type is the type that dominates the mangrove area with an average carbon amount of 122.1 tonnes/ha. Correlation analysis shows a strong relationship between IKVm and mangrove forest carbon stocks, with a correlation coefficient value of 80%. In the regression model, the power model provides the best equation for estimating carbon stocks with a coefficient of determination value of 64.4% giving a model equation of y = 109.51x1.2381. Analysis of image carbon reserves obtained the lowest value, namely 0.02-10.46 tonnes/ha which was in the very rare vegetation density type and the highest carbon reserve value was 58.30-59.02 tonnes/ha in the very high density class.
Co-Authors Andi Chairil Ichsan Andrie Ridzki Prasetyo Moh Rodiansyah Hambali Muhammad Anwar Hadi