Article Per Year (5 Year)
p-Index From 2019 - 2024
0.61
P-Index
This Author published in this journals
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

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
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.
Analisis Komparatif Tutupan Mangrove Menggunakan Citra Landsat 9 dan Sentinel 2A di Desa Labuan Tereng Kabupaten Lombok Barat Andrie Ridzki Prasetyo; Niechi Valentino; Moh Rodiansyah Hambali
JURNAL SAINS TEKNOLOGI & LINGKUNGAN Vol. 10 No. 2 (2024): JURNAL SAINS TEKNOLOGI & LINGKUNGAN
Publisher : LPPM Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jstl.v10i2.606

Abstract

Labuan Tereng Village is a place where mangrove vegetation grows and develops. The location close to the harbor sheet makes the mangrove ecosystem damaged by port activities. High port activity can disrupt the condition of mangrove ecosystem development in Labuan Tereng Village. This study was conducted to evaluate mangrove health by looking at canopy cover or canopy density using the Hemispherical Photography method analyzed using Landsat 9 and Sentinel 2A to assess the extent of relationship between mangrove canopy cover and images. The findings revealed that the mean mangrove cover density value of 66% which is included in the medium category. Statistical analysis of several vegetation indexes with mangrove cover obtained the highest linear regression results in the SAVI model with a value of 0,41 for Landsat 9 images and 0,65 for Sentinel 2A images. The results of image data analysis on Sentinel 2A show a smaller pixel size value and contain more pixels so as to produce better and complex data analysis when compared to Landsat 9 imagery.
Co-Authors Andi Chairil Ichsan Andrie Ridzki Prasetyo Moh Rodiansyah Hambali Moh Rodiansyah Hambali Muhammad Anwar Hadi