Publisher

APTKLHIAPTKLHI

Journal Indonesian Journal of Forestry ResearchIndonesian Journal of Forestry Research Abstract

Indonesia khususnya Kota Palangka Raya yang terletak di Kalimantan Tengah memiliki kawasan hutan dengan luas sekitar 241.736,25 hektar. Kawasan hutan tersebut mempunyai peranan penting bagi kelangsungan hidup manusia. Namun setiap tahunnya, kebakaran hutan selalu terjadi dan menimbulkan kerusakan hutan, berdampak pada kondisi lingkungan seperti kesehatan vegetasi dan kualitas udara. Penelitian ini bertujuan untuk mengidentifikasi kawasan kebakaran hutan dan dampaknya berdasarkan kesehatan vegetasi dan perubahan kualitas udara dengan menggunakan teknologi penginderaan jauh. Metode penginderaan jauh yang digunakan dalam makalah ini adalah indeks spektral kebakaran Normalized Burn Ratio 2 (NBR2) untuk identifikasi area terbakar, Enhanced Vegetation Index (EVI) untuk mengidentifikasi kesehatan vegetasi, dan PM2.5 untuk analisis kualitas udara. Data citra satelit Landsat-8 digunakan sebagai data primer untuk mengekstraksi area terbakar dan dampaknya. Area terbakar yang dihasilkan NBR2 menunjukkan akurasi keseluruhan yang tinggi yaitu 82,229%. Studi tersebut menunjukkan bahwa kebakaran hutan berdampak pada polusi udara dengan peningkatan besar dalam paparan PM2.5 setelah kebakaran hutan, dan penurunan kesehatan vegetasi, yang terjadi di sekitar area yang diidentifikasi sebagai area yang terbakar. Dengan hasil tersebut, identifikasi kawasan kebakaran hutan dan dampaknya dapat dipantau secara terus menerus menggunakan data penginderaan jauh guna meminimalkan dampak kebakaran hutan.

Conclusion

Forest fires in 2019 severely degraded vegetation health and increased PM2.5 levels, classifying air quality as not healthy.These findings highlight the significant environmental and public health impacts of the 2019 fire event.

Future Research

First, perform a five‑year EVI time‑series analysis to quantify peat swamp forest recovery after fires. The analysis will reveal a clear vegetation‑health threshold that can trigger early fire‑impact alerts. Second, build a spatial model that combines fire‑occurrence data with detailed local land‑clearing practices. Include climatic variables such as pronounced dry peat layers to improve high‑risk period forecasting accuracy. Third, develop a hybrid remote‑sensing framework fusing Landsat‑8 and MODIS observations to refine NBR2 detection performance. The fusion will systematically correct water‑related misclassifications commonly seen in wet peatlands. Assessing these methods will provide policymakers with precise tools for targeting mitigation and prevention in Palangka Raya. Integrating vegetation dynamics, human activity patterns, and advanced sensor fusion directly addresses knowledge gaps highlighted by this study. The resulting strategy will support the construction of evidence‑based fire‑prevention plans specifically adapted to local environmental conditions. Overall, this comprehensive approach will enhance peat swamp forest resilience and ultimately safeguard community health and wellbeing.

References

1. Radware Bot Manager Captcha. radware manager captcha apologize ensure keep safe please confirm human... doi.org///10.1088/1742-6596/1825/1/012087Radware Bot Manager Captcha radware manager captcha apologize ensure keep safe please confirm human doi 10 1088 1742 6596 1825 1 012087
2. Using Landsat Spectral Indices in Time-Series to Assess Wildfire Disturbance and Recovery. landsat spectral... doi.org///10.3390/rs10030460Using Landsat Spectral Indices in Time Series to Assess Wildfire Disturbance and Recovery landsat spectral doi 10 3390 rs10030460
3. The Optimal Threshold and Vegetation Index Time Series for Retrieving Crop Phenology Based on a Modified... doi.org///10.3390/rs11232725The Optimal Threshold and Vegetation Index Time Series for Retrieving Crop Phenology Based on a Modified doi 10 3390 rs11232725
4. Strategy and Roadmap for Achieving Sustainable Development Goals in Serang City | Jurnal Bina Praja.... doi.org///10.21787/JBP.11.2019.219-235Strategy and Roadmap for Achieving Sustainable Development Goals in Serang City Jurnal Bina Praja doi 10 21787 JBP 11 2019 219 235
5. On a Data-Driven Approach for Detecting Disturbance in the Brazilian Savannas Using Time Series of Vegetation... doi.org///10.3390/rs13244959On a Data Driven Approach for Detecting Disturbance in the Brazilian Savannas Using Time Series of Vegetation doi 10 3390 rs13244959

Subjects

1. #bibliometric analysis#bibliometric analysis
2. #sensor ultrasonik#sensor ultrasonik

Metadata

File size	1.11 MB
Pages	12
Short Link	https://juris.id/p-32
Lookup Links	Google ScholarGoogle Scholar, Semantic ScholarSemantic Scholar, CORE.ac.ukCORE.ac.uk, WorldcatWorldcat, ZenodoZenodo, Research GateResearch Gate, Academia.eduAcademia.edu, OpenAlexOpenAlex, Hollis HarvardHollis Harvard
DMCA	Report