Detection Of Land Drought Using Landsat Imagery On The Google Earth Engine Platform For Forest Fire Mitigation
Sari
ABSTRAK
Kekeringan yang diperparah oleh El Nino dan pemanasan global sering kali mejadi pemicu terjadinya kebakaran hutan di Sumatra dan Kalimantan, Indonesia, yang berdampak pada ekosistem dan masyarakat setempat. Studi ini menggunakan Temperature Vegetation Dryness Index (TVDI) yang menggabungkan Land Surface Temperature (LST) dan Normalized Difference Vegetation Index (NDVI) di platform Google Earth Engine (GEE) untuk mendeteksi area rawan kekeringan dengan cepat dan akurat. Analisis dilakukan dengan data satelit Landsat 8 dari musim kemarau tahun 2022 dan 2023 di Kabupaten Kubu Raya, Kalimantan Barat. Peta kekeringan yang dihasilkan mengidentifikasi hotspot di wilayah tengah, dengan validasi data kebakaran hutan BRIN mencapai akurasi 97%. Metode ini memberikan wawasan yang berharga bagi pemerintah daerah, memungkinkan pengambilan keputusan kebijakan yang lebih baik dan membantu pencegahan kebakaran lebih awal, meskipun terdapat kendala tutupan awan selama musim kemarau.
Kata kunci: TVDI, LST, NDVI, GEE, Kebakaran Hutan
ABSTRACT
Exacerbated by El Nino and global warming, drought often precedes forest fires in Sumatra and Kalimantan, Indonesia, impacting local ecosystems and communities. This study utilizes the Temperature Vegetation Dryness Index (TVDI), combining Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) data on the Google Earth Engine (GEE) platform to detect drought-prone areas quickly and accurately. Analysis was performed using Landsat 8 satellite data from the 2022 and 2023 dry seasons in Kubu Raya Regency, West Kalimantan. The generated drought map identified central region hotspots, with validation using BRIN's forest fire data, achieving 97% accuracy. This method's high reliability offers valuable insights for local governments, enabling better policy decisions and aiding early fire prevention measures despite challenges like frequent cloud cover during the dry season.
Keywords: TVDI, LST, NDVI, GEE, Forest Fire
Kata Kunci
Teks Lengkap:
PDF (English)Referensi
Alfarizi, I. A. G., Herlambang, G. A., Hartono, R., Sucahyo, H. R., Wiwoho, B. S., & Astuti, I. S. (2022). Drought Indices to Map Forest Fire Risks in Topographically Complex Mountain Landscapes. KnE Social Sciences, 2022, 197–209. https://doi.org/10.18502/kss.v7i16.12167
Amani, M., Ghorbanian, A., Ahmadi, S. A., Kakooei, M., Moghimi, A., Mirmazloumi, S. M., Moghaddam, S. H. A., Mahdavi, S., Ghahremanloo, M., Parsian, S., Wu, Q., & Brisco, B. (2020). Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, 5326–5350. https://doi.org/10.1109/JSTARS.2020.3021052
Cheng, L., Liu, S., Mo, X., Hu, S., Zhou, H., Xie, C., Nielsen, S., Grosen, H., & Bauer-Gottwein, P. (2023). Assessing the Potential of 10-m Resolution TVDI Based on Downscaled LST to Monitor Soil Moisture in Tang River Basin, China. Remote Sensing, 15(3). https://doi.org/10.3390/rs15030744
Ghorbanzadeh, O., Blaschke, T., Gholamnia, K., & Aryal, J. (2019). Forest fire susceptibility and risk mapping using social/infrastructural vulnerability and environmental variables. Fire, 2(3), 1–27. https://doi.org/10.3390/fire2030050
Guha, S., Govil, H., Gill, N., & Dey, A. (2020). Analytical study on the relationship between land surface temperature and land use/land cover indices. Annals of GIS, 26(2), 201–216. https://doi.org/10.1080/19475683.2020.1754291
Holzman, M. E., Rivas, R., & Piccolo, M. C. (2014). Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index. International Journal of Applied Earth Observation and Geoinformation, 28(1), 181–192. https://doi.org/10.1016/j.jag.2013.12.006
Hulley, G., & Lluis Perez-Planells. (2024). Terminology in thermal infrared remote sensing of natural surfaces. Land Product Validation Subgroup. Retrieved from https://lpvs.gsfc.nasa.gov/LSTE/LSTE_home.html#:~:text=Land Surface Emissivity Definition,Units%3A Dimensionless.
Li, Y., Wang, X., Wang, F., Feng, K., Li, H., Han, Y., & Chen, S. (2024). Temporal and Spatial Characteristics of Agricultural Drought Based on the TVDI in Henan Province, China. Water (Switzerland), 16(7). https://doi.org/10.3390/w16071010
Li, Z. L., Wu, H., Duan, S. B., Zhao, W., Ren, H., Liu, X., Leng, P., Tang, R., Ye, X., Zhu, J., Sun, Y., Si, M., Liu, M., Li, J., Zhang, X., Shang, G., Tang, B. H., Yan, G., & Zhou, C. (2023). Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications. Reviews of Geophysics, 61(1), 1–77. https://doi.org/10.1029/2022RG000777
Muharrama, D., & Widjonarko, W. (2023). Risiko Bencana Kebakaran Hutan dan Lahan Gambut di Kabupaten Kubu Raya, Provinsi Kalimantan Barat. Teknik PWK (Perencanaan Wilayah Kota), 12(2), 160–170. https://doi.org/10.14710/tpwk.2023.32816
Mutthulakshmi, K., Wee, M. R. E., Wong, Y. C. K., Lai, J. W., Koh, J. M., Acharya, U. R., & Cheong, K. H. (2020). Simulating forest fire spread and fire-fighting using cellular automata. Chinese Journal of Physics, 65(April), 642–650. https://doi.org/10.1016/j.cjph.2020.04.001
Nugroho, S. P. (2019). 99% Penyebab Kebakaran Hutan dan Lahan Adalah Ulah Manusia. BNPB.Go.Id. Retrieved from https://bnpb.go.id/99-penyebab-kebakaran-hutan-danlahan-adalah-ulah-manusia
Pemerintah Kabupaten Kubu Raya. (2024). Geografi. Humas Kabupaten Kubu Raya. Retrieved from https://prokopim.kuburayakab.go.id/page/geografi
Pham, H. T. T., & Tran, H. T. (2021). Application of Remote Sensing Imagery and Algorithms in Google Earth Engine platform for Drought Assessment. Journal of Mining and Earth Sciences, 62(3), 53–67. https://doi.org/10.46326/jmes.2021.62(3).07
Pietersz, J. H., Pribadi, R., & Pentury, R. (2024). Estimasi Tutupan Kanopi Berdasarkan NDVI dan Kondisi Tutupan Tajuk Pada Ekosistem Mangrove Negeri Passo, Teluk Ambon Dalam. Jurnal Kelautan Tropis, 27(2), 197–208. https://doi.org/10.14710/jkt.v27i2.22090
Prayoga, M. B. R., & Koestoer, R. H. (2021). Improving Forest Fire Mitigation in Indonesia: A Lesson from Canada. Jurnal Wilayah dan Lingkungan, 9(3), 293–305. https://doi.org/10.14710/jwl.9.3.293-305
Przezdziecki, K., Zawadzki, Jdeteksi . J., Urbaniak, M., Ziemblinska, K., & Miatkowski, Z. (2023). Using temporal variability of land surface temperature and normalized vegetation index to estimate soil moisture condition on forest areas by means of remote sensing. Ecological Indicators, 148(March), 0–3. https://doi.org/10.1016/j.ecolind.2023.110088
DOI: https://doi.org/10.26760/elkomika.v12i4.1023
Refbacks
- Saat ini tidak ada refbacks.
_______________________________________________________________________________________________________________________
ISSN (print) : 2338-8323 | ISSN (electronic) : 2459-9638
Publisher:
Department of Electrical Engineering Institut Teknologi Nasional Bandung
Address: 20th Building Institut Teknologi Nasional Bandung PHH. Mustofa Street No. 23 Bandung 40124
Contact: +627272215 (ext. 206)
Email: jte.itenas@itenas.ac.id________________________________________________________________________________________________________________________
Jurnal ini terlisensi oleh Creative Commons Attribution-ShareAlike 4.0 International License.