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Spatial Analysis of the Relationship between Vegetation Index and Land Surface Temperature in Ternate Island, Indonesia Rakuasa, Heinrich; Khromykh, Vadim V; Latue, Philia Christi
BIOPENDIX: Jurnal Biologi, Pendidikan dan Terapan Vol 12 No 1 (2025): Biopendix: Jurnal Biologi, Pendidikan & Terapan
Publisher : Program Studi Pendidikan Biologi FKIP Unpatti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/biopendixvol12issue1page48-57

Abstract

This research focuses on the spatial analysis of the relationship between vegetation index and land surface temperature in Ternate Island, Indonesia, which is becoming increasingly relevant amidst the phenomenon of rapid urbanization. The background of the research shows that land use change has the potential to reduce green open space, contributing to an increase in surface temperature that can trigger the Urban Heat Island (UHI) phenomenon. The methods used include utilizing Landsat 8 OLI/TRIS satellite image data to calculate NDVI and LST values and statistical analysis using Pearson's correlation test and Spearman's rho to identify the relationship between the two. The results showed a significant negative relationship between NDVI and LST, with a Pearson correlation coefficient of -0.613, indicating that areas with better vegetation cover tend to have lower surface temperatures, and non-vegetated areas influence the increase of land surface temperature. The discussion highlights the importance of vegetation in regulating surface temperature through evapotranspiration and shading processes and suggests the need for afforestation strategies to mitigate climate change on Ternate Island
Spatial Analysis of the Impact of Nickel Mining on Vegetation Cover Change in Obi Island, Indonesia Rakuasa, Heinrich; Khromykh, Vadim V; Rifai, Ahmad; Latue, Philia Christi
BIOPENDIX: Jurnal Biologi, Pendidikan dan Terapan Vol 12 No 2 (2025): Biopendix: Jurnal Biologi, Pendidikan & Terapan
Publisher : Program Studi Pendidikan Biologi FKIP Unpatti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/biopendixvol12issue2page77-85

Abstract

The nickel mining activities in Indonesia, particularly on Obi Island, have significantly altered land-use patterns, marked by an expansion of bare land due to topsoil and vegetation removal. This has led to a drastic decline in dense and productive vegetation cover, which previously served as a carbon sink and habitat for local biodiversity. Utilizing Landsat 8 Surface Reflectance Collection 2 Tier 1 imagery (2015, 2020, 2025), this study employed the Normalized Difference Vegetation Index (NDVI) within the Google Earth Engine and ArcGIS Pro platforms to assess spatiotemporal changes in vegetation cover. Results indicate a substantial increase in non-vegetated areas and a significant reduction in moderate-to-high-density vegetation, particularly within the mining core zone, directly attributable to nickel extraction activities, which drive habitat fragmentation and ecosystem degradation. Although rehabilitation and revegetation efforts demonstrate localized success, ongoing mining pressures pose risks of further environmental damage without sustainable management. This study underscores the critical need for stringent environmental regulations and targets ecological restoration to mitigate mining impacts and ensure the long-term sustainability of Obi Island's ecosystems
Spatial Dynamics of Vegetation Index Changes in the Weda Nickel Mining Area, Halmahera Island, Indonesia Rakuasa, Heinrich; Khromykh, Vadim V
Journal of Scientific Insights Vol. 3 No. 1 (2026): Available online
Publisher : Science Tech Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69930/jsi.v3i1.596

Abstract

Nickel mining in Weda, Halmahera Island, is one of the largest nickel mines in Indonesia, and its activities impact changes in vegetation indices and cover in the area. The research uses Landsat 8 satellite imagery from 2019, 2022, and 2025 with the NDVI algorithm to analyse changes in vegetation index values and vegetation cover. The research results show that the NDVI values for 2019 are the lowest at -0.233774 and the highest at 0.999903; for 2022, the lowest is -0.369486 and the highest is 0.799867; and for 2025, the lowest is -0.369486 and the highest is 0.530372. The NDVI values were then classified into 4 vegetation cover classes: active mining areas, sparse, moderate, and dense vegetation. The active mining area in 2019 was 1.27 km², in 2022 it was 11.91 km², and in 2025 it was 18.20 km². Sparse vegetation in 2019 covered 5.73 km², in 2022 it covered 6.03 km², and in 2025 it covered 8.07 km². Moderate vegetation in 2019 covered 5.72 km², in 2022 it covered 2.68 km², and in 2025 it covered 2.21 km². Dense vegetation in 2019 covered 522.64 km², in 2022 it covered 515.35 km², and in 2025 it covered 507.20 km². The presentation of the mining area continues to increase every year. The results of this research are expected to be used for continuous monitoring to ensure compliance with environmental standards and support rehabilitation programmes in Weda and other tropical mining areas.
Spatial Distribution and Suitability of the Endemic Babirusa Habitat (Babyrousa babyrussa) on Buru Island, Maluku using Maximum Entropy Rakuasa, Heinrich; Khromykh, Vadim V; Latue, Philia Christi; Manakane, Susan E; Somae, Glendy; Joshua, Benson
BIOPENDIX: Jurnal Biologi, Pendidikan dan Terapan Vol 13 No 1 (2026): Biopendix: Jurnal Biologi, Pendidikan & Terapan
Publisher : Program Studi Pendidikan Biologi FKIP Unpatti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/biopendixvol13issue1page41-51

Abstract

Buru Island is the endemic habitat of the Babirusa (Babyrousa babyrussa), facing pressures from human activities and habitat fragmentation. This study used the Maximum Entropy (MaxEnt) modeling method to map the spatial distribution and assess the habitat suitability of Babirusa based on environmental variables including elevation, slope, temperature, land cover, distance to water, and distance from built-up areas. The results show that the habitat is divided into four main classes: Very Low at 24.95%, Low at 31.67%, Moderate at 29.71%, and High at 13.68% of the total island area, which requires more intensive management and protection. Elevation and distance from settlements have an influence but with relatively small contributions, indicating the species’ tolerance to elevation variation. This model provides a scientific basis for integrated conservation strategies, including habitat management, reduction of anthropogenic pressures, and sustainable spatial planning based on habitat suitability to ensure the long-term survival of Babirusa on Buru Island.