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p-Index From 2021 - 2026
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All Journal International Journal of Health, Engineering and Technology
Muhammad Efendi
Lambung Mangkurat University
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Dentistry Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Mapping Of Aboveground Biomass Estimation Based On Vegetation Index In Banjarbaru City Sukmawati Sukmawati; Muhammad Efendi
International Journal of Health Engineering and Technology Vol. 5 No. 2 (2026): Vol 5. No. 2 JULY 2026
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v5i2.1016

Abstract

Climate change increases the importance of aboveground biomass information as an indicator of carbon stocks and a basis for urban vegetation management. This study aims to determine the best model for estimating aboveground biomass using Sentinel-2 imagery-based vegetation indices and to map biomass distribution in Banjarbaru City. The study uses a quantitative approach with remote sensing-based spatial analysis. The study population is all woody vegetation in Banjarbaru City, while the sample consists of 45 plots determined using stratified random sampling. The research instruments include Diameter at Breast Height (DHT), tree height, Global Positioning System (GPS), and Sentinel-2B Level-2A imagery. Data analysis was carried out through biomass calculations using allometric equations, Pearson correlation analysis, linear, exponential, polynomial, and power regressions, regression assumption testing, model validation using SA, SR, RMSE, bias, and chi-square, and spatial mapping. The results showed that the Linear SAVI model was the best model with the equation B = -287.341 + 517.644 SAVI and an R² value of 0.905. In conclusion, the Linear SAVI model is able to provide accurate and representative biomass estimates, while the application of masking improves the quality of biomass mapping, thereby supporting carbon inventory and green open space planning.
Mapping The Distribution Of Soil pH, Pyrite (FeS2) Content, Soil Texture, And Waterlogging In Rice Field Areas In Jejangkit District, Barito Kuala Regency Akhmad Maki; Muhammad Efendi
International Journal of Health Engineering and Technology Vol. 5 No. 2 (2026): Vol 5. No. 2 JULY 2026
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v5i2.1013

Abstract

This study aims to identify the characteristics of soil pH, pyrite (FeS₂) content, soil texture, and waterlogging in rice fields in Jejangkit District, Barito Kuala Regency, map their spatial distribution using the Inverse Distance Weighting (IDW) method based on Geographic Information Systems (GIS), evaluate the accuracy of the interpolation results, and develop land management guidelines based on the physical conditions of the land. The study uses a quantitative approach with field survey methods and GIS-based spatial analysis. A total of 64 sample points are used as the main data for interpolation. The results show that the soil pH value ranges from 3.5–5.5, pyrite content is 0.3–4.4%, soil texture is dominated by clay fractions, while the height of waterlogging ranges from 14–64 cm. The IDW interpolation results are able to describe the spatial distribution pattern of all research parameters continuously. Validation testing shows that the interpolation results have a good level of accuracy so that they can be used to describe the condition of the research land.
Co-Authors Akhmad Maki Sukmawati Sukmawati