Open Access
| Issue |
BIO Web Conf.
Volume 216, 2026
The 6th Sustainability and Resilience of Coastal Management (SRCM 2025)
|
|
|---|---|---|
| Article Number | 03001 | |
| Number of page(s) | 14 | |
| Section | Environmental and Hazard Mitigation | |
| DOI | https://doi.org/10.1051/bioconf/202621603001 | |
| Published online | 05 February 2026 | |
- Madani Berkelanjutan, “40 Ribu Hektare Karhutla Diindikasi Terjadi di Indonesia Selama Januari-April 2024, Terbesar di Kalimantan Timur,” madani berkelanjutan.id. Available: https://madaniberkelanjutan.id/40-ribu-hektare-karhutla-diindikasiterjadi-di-indonesia-selama-januari-april-2024-terbesar-dikalimantan-timur/. [Accessed: Feb. 10, 2025]. [Google Scholar]
- L. Syaufina and I.S. Sitanggang, “Peatland fire detection using spatio-temporal data mining analysis in Kalimantan, Indonesia,” J. Trop. For. Sci., vol. 30, no. 2, pp. 154-162, 2018. doi: 10.26525/jtfs2018.30.2.154162. [Google Scholar]
- A.J. Horton et al., “Identifying key drivers of peatland fires across Kalimantan's Ex-Mega Rice Project using machine learning,” Earth and Space Sci., vol. 8, no. 9, Art. no. e2021EA001873, 2021. doi: 10.1029/2021EA001873. [Google Scholar]
- A. Schmidt et al., “Fire frequency, intensity, and burn severity in Kalimantan’s threatened peatland areas over two decades,” Front. Forests Global Change, vol. 7, Art. no. 1221797, 2024. doi: 10.3389/ffgc.2024.1221797. [Google Scholar]
- A. Choiruddin, Aisah, F. Trisnisa, and N. Iriawan, “Quantifying the effect of geological factors on distribution of earthquake occurrences by inhomogeneous Cox processes,” Pure Appl. Geophys., vol. 178, pp. 1579-1592, 2021. [Google Scholar]
- R. Kumalawati et al., “Hotspot spatial patterns using SNNP-VIIRS for fire potential monitoring,” Int. J. Forestry Res., vol. 2023, Art. no. 3121862, 2023. [Google Scholar]
- S. Nurdiati, A. Sopaheluwakan, P. Septiawan, and M.R. Ardhana, “Joint spatio-temporal analysis of various wildfire and drought indicators in Indonesia,” Atmosphere, vol. 13, no. 10, Art. no. 1591, 2022. [Google Scholar]
- F. Bioresita, D.E. Pongdatu, N. Hayati, U.W. Deviantari, and C.B. Pribadi, “Estimation of forest fire areas in Palangka Raya, Central Kalimantan, Indonesia using NBR2 and its impact on environment,” Indonesian J. Forestry Res., vol. 12, no. 1, pp. 1-12, 2025. doi: 10.59465/ijfr.2025.12.1.1-12. [Google Scholar]
- Y. Wang, A. Degleris, A. Williams, and S.W. Linderman, “Spatiotemporal clustering with Neyman-Scott processes via connections to Bayesian nonparametric mixture models,” J. Amer. Statist. Assoc., vol. 119, no. 547, pp. 2382-2395, 2024. doi: 10.1080/01621459.2023.2257896. [Google Scholar]
- HA Sidharta, B Al Kindhi, E Mulyanto, MH Purnomo, “Semantic Segmentation of Pedestrian Groups Based on Directional-oriented Density Features with Shallow U-net Architecture”, International Journal of Intelligent Engineering & Systems, 18, 1, 2025 [Google Scholar]
- A.J. Baddeley, J. Møller, and R. Waagepetersen, “Non- and semiparametric estimation of interaction in inhomogeneous point patterns,” Stat. Neerl., vol. 54, no. 3, pp. 329-350, 2000. [CrossRef] [Google Scholar]
- J. Illian, A. Penttinen, H. Stoyan, and D. Stoyan, Statistical Analysis and Modelling of Spatial Point Patterns. Chichester, U.K.: Wiley, 2008. [Google Scholar]
- A. Baddeley, E. Rubak, and R. Turner, Spatial Point Patterns: Methodology and Applications with R. New York, NY, USA: Chapman and Hall/CRC, 2015. [Google Scholar]
- S. Portet, “A primer on model selection using the Akaike Information Criterion,” Infect. Disease Modelling, vol. 5, pp. 111-128, 2020. doi: 10.1016/j.idm.2019.12.010. [Google Scholar]
- J. Zhang, Y. Yang, and J. Ding, “Information criteria for model selection,” WIREs Comput. Stat., vol. 15, no. 5, Art. no. e1607, 2023. doi: 10.1002/wics.1607. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.