Claim Missing Document
Check
Articles

Found 2 Documents
Search

Geospatial Analysis-Based Tidal Flood Vulnerability Mapping in the Coastal Area of Sungai Kakap District, Kubu Raya Regency Yoga Prasetya Adi Nugraha; Paiman Paiman; Rosanti Rosanti; Nadine Andara Septiani; Shelsi Nabila Putri
Jurnal Penelitian Pendidikan IPA Vol 12 No 10 (2026): In Press
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i10.15762

Abstract

Tidal flooding has become an increasingly significant environmental hazard in coastal areas. This study aims to: (1) identify the spatial characteristics of tidal flooding in the coastal area, (2) analyze the spatial factors influencing tidal flood vulnerability; (3) assess the level of tidal flood vulnerability using geospatial analysis; and (4) propose adaptation strategies based on the resulting vulnerability patterns. The analysis includes eight key variables: slope gradient, elevation, distance to the coastline, distance to the river, Topographic Moisture Index (TWI), soil type, rainfall, and land use. The spatial datasets were processed in a Geographic Information System (GIS) environment and integrated using a multi-criteria spatial analysis approach to generate a tidal flood vulnerability map. The results showed that vulnerability to tidal flooding was strongly associated with low elevation, gentle slopes, proximity to the coastline and river network, high TWI values, poorly drained alluvial soils, high rainfall intensity, and land use dominated by settlements, fish farming ponds, and agricultural land. The vulnerability assessment classified the study area into five categories: very high (5,717 ha; 12.62%), high (7,919 ha; 17.47%), moderate (5,515 ha; 12.17%), low (2,404 ha; 5.30%), and very low (23,762 ha; 52.44%). Areas with high and very high vulnerability were concentrated in lowland coastal zones and riverine environments. Adaptation strategies include strengthening coastal protection, improving drainage infrastructure, implementing ecosystem-based coastal management, regulating land use in vulnerable areas, and enhancing community-based disaster preparedness. This study demonstrates the effectiveness of geospatial analysis to support tidal flood risk reduction and sustainable coastal planning.
Surface Carbon Stock Estimation Using Geospatial-Based Stock Difference Method in Sungai Kakap District, Kubu Raya Regency Agus Sudiro; Paiman Paiman; Rosanti Rosanti; Muhammad Haikal Parabi; Muhammad Aprizal
Jurnal Penelitian Pendidikan IPA Vol 12 No 10 (2026): In Press
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v12i10.15912

Abstract

Carbon stock assessment is a critical component of climate change mitigation, particularly in coastal areas experiencing rapid land-use change. This study aims to estimate aboveground carbon stocks, potential CO₂ emissions, and the economic value of carbon across various land use and land cover (LULC) types in Sungai Kakap District, Kubu Raya Regency, West Kalimantan, Indonesia. A geospatial stock-difference approach was used by integrating land use/land cover maps with carbon emission factors for each LULC category. Carbon stocks were calculated by multiplying the area of each land use class by its respective carbon density, while potential CO₂ emissions were estimated using the IPCC conversion factor (44/12). The economic value of carbon was determined using a carbon price of USD 5 per ton of CO₂. The study results show that the total aboveground carbon stock reached 3.197.198,96 tons of carbon, with an estimated potential emission of 11.723.062,86 tons of CO₂ and a total carbon economic value of USD 15.985.994,81. Mangrove ecosystems contributed the largest carbon stock (1.141.154,51 tons of C), followed by agricultural land (828.861,07 tons of C) and forest formations (620.751,79 tons of C). Consequently, mangroves also exhibit the highest CO₂ emission potential and carbon economic value among all land use classes. These findings highlight the strategic importance of mangrove and forest conservation while promoting sustainable land management to maintain carbon storage, reduce greenhouse gas emissions, and enhance the economic benefits of ecosystem services. Integrating geospatial analysis with carbon valuation provides a practical framework to support low-carbon development and evidence-based land-use planning in coastal landscapes