Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
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All Journal Geoid - Journal of Geodesy and Geomatics
Murdawati
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Engineering Environmental Science

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Spatio-Temporal Analysis of Carbon Monoxide (CO) Distribution According to Deforestation in West Kalimantan, Indonesia Ramadhania, Nurya; Murdawati; Devika Rahma Damayanti Yusuf; Widodo Eko Prasetyo
Geoid Vol. 21 No. 1 (2026)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/geoid.v21i1.7840

Abstract

Carbon monoxide (CO) is a harmful air pollutant primarily produced through biomass burning, including forest fires and deforestation activities. West Kalimantan Province, which has undergone massive land cover change, is a crucial area for examining the link between deforestation and the increase in atmospheric CO concentrations. This study aims to analyze the spatial and temporal relationship between CO distribution and deforestation throughout 2024. CO data were obtained from Sentinel-5P satellite imagery, while deforestation detection was carried out using the Normalized Burn Ratio (NBR) and the Normalized Difference Vegetation Index (NDVI), derived from Sentinel-2A imagery. The NBR index was used to detect areas affected by fire or land conversion, while the NDVI reflects vegetation health conditions. The analysis results show that regions with increased NBR and decreased NDVI tend to have high CO concentrations. The Pearson correlation between NBR and CO indicates a very strong positive relationship, while the correlation between NDVI and CO shows a weak to moderate negative relationship. However, the dominance of cloud cover in most Sentinel-2A imagery in West Kalimantan potentially affects the quality and representativeness of the resulting vegetation data. This study highlights that deforestation significantly contributes to the decline in air quality, demonstrating that satellite-based remote sensing is an effective tool for air pollution monitoring and supporting environmental mitigation policies.
Prediction of Erosion Hazard Level in Tripe Jaya District Using the Universal Soil Loss Equation (USLE) Method Murdawati; Yusuf, Devika Rahma Damayanti; Nurya Ramadhania; Nadya Novi Rahmadana
Geoid Vol. 21 No. 1 (2026)
Publisher : Departemen Teknik Geomatika ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/geoid.v21i1.7919

Abstract

The Tripe Jaya Subdistrict in Gayo Lues Regency features a highly vulnerable landscape where steep slopes, intense rainfall, and limited vegetation cover collectively contribute to severe erosion risk. Erosion in this region threatens soil fertility, agricultural productivity, slope stability, transportation infrastructure, and riverbank integrity. This study aims to predict and map erosion hazard levels using the Universal Soil Loss Equation (USLE) integrated with Geographic Information System (GIS) analysis, based on rainfall, soil type, slope, and land cover data. The results classify the study area into five erosion hazard categories: very light (2,909.09 ha), light (20,669.38 ha), moderate (10,880.66 ha), heavy (432.99 ha), and very heavy (6,922.76 ha), with the most critical zones concentrated in steep and intensively utilized areas. These findings emphasize the substantial erosion risk in Tripe Jaya and provide an essential reference for mitigation planning, land-use regulation, and infrastructure protection, particularly for road segments adjacent to riverbanks.
Co-Authors Devika Rahma Damayanti Yusuf Nadya Novi Rahmadana Nurya Ramadhania Ramadhania, Nurya Widodo Eko Prasetyo Yusuf, Devika Rahma Damayanti