Prediction of Peat Forest Fires Using Wavelet and Backpropagation

Novera Kristianti(1*), Albertus Joko Santoso(2), Pranowo Pranowo(3)

(1) Universitas Atma Jaya Yogyakarta
(2) Universitas Atma Jaya Yogyakarta
(3) Universitas Atma Jaya Yogyakarta
(*) Corresponding Author


One of the causes of smog as well as climate damage, particularly in Palangka Raya, Center Kalimantan, are peat forest fires. There are a lot of losses inflicted by the smog including the increasing number of people who suffer respiratory infection (ARI) due to polluted air and any other related aspects. Peat fires are problematic to overcome because the locations of fires are difficult to be accessed. This paper focuses on building the system to predict the distribution of peat forest fire hotspots by utilizing satellite imagery. In designing the system for predicting the fire hotspots distribution, wavelet orthogonal was used as the initial processing of mapping the distribution of peat forest fire hotspots. Meanwhile, backpropagation method was used to identify the fire hotspot distribution patterns of peat forest fire in this system. From the result of the data tested which had been done for predicting the peat forest fire hotspots, the decomposition image obtained using Haar wavelet had the highest percentage of accuracy to recognize the fire hotspots, which is 90%. The recency of this system was its ability to predict the peat forest fire hotspots distribution which can be used as peat forest fires prevention, especially in Palangka Raya, Central Kalimantan.


fire hotspots distribution, peat forest fire, wavelet orthogonal, backpropagation, Palangka Raya

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S. Kanga and S.K. Singh, "Forest Fire Simulation Modeling using Remote Sensing & GIS," International Journal of Advanced Research in Computer Science, Vol. 8, No. 2, pp. 326-332, May-June 2017.

P.J. van Mantgem, J.C.B. Nesmith, M. Keifer, E.E. Knapp, A. Flint, and L. Flint, "Climatic Stress Increases Forest Fire Severity Across the Western United States," Ecology Letters, Vol. 16, No. 9, pp. 1151-1156, 2013.

M. Castelli, L. Vanneschi, and A. Popovič, "Predicting Burned Areas of Forest Fires: An Artificial Intelligence Approach," Fire Ecology, Vol. 11, No. 1, pp. 106-118, 2015.

A. Kaur, R. Sethi, and K. Kaur, "Comparison of Forest Fire Detection Techiques Using WSNs," International Journal of Computer Science and Information Technologies, Vol. 5, pp. 3800-3802, 2014.

W.A. Hoffmann, E.L. Geiger, S.G. Gotsch, D.R. Rossatto, L.C. R. Silva, O.L. Lau, M. Haridasan, and A.C. Franco, "Ecological Thresholds at the Savanna ‐ Forest Boundary: How Plant Traits, Resources and Fire Govern the Distribution of Tropical Biomes," Ecology Letters, Vol. 15, pp. 759-768, 2012.

A. Ganteaume, A. Camia, M. Jappiot, J.S.-M. -Ayanz, M.L. -Fournel, and C. Lampin, "A Review of the Main Driving Factors of Forest Fire Ignition Over Europe," Environmental Management, Vol. 51, No. 3, pp. 651-662, 2013.

L.K. Sharma, S. Kanga, M.S. Nathawat, S. Sinha, and P.C. Pandey, "Fuzzy AHP for Forest Fire Risk Modeling," Disaster Prevention and Management, Vol. 21, pp. 160-171, 2012.

S. Anitha, S. Soujanya, and G.B. Rajkumar, "An Approach for Identifying the Forest Fire Using Land Surface Imagery by Locating the Abnormal Temperature Distribution," IOSR Journal of Computer Engineering (IOSR-JCE), Vol. 14, No. 3, pp. 06-12, 2013.

N. Baranovskiy and M. Zharikova, "A Web-Oriented Geoinformation System Application for Forest Fire Danger Prediction in Typical Forests of the Ukraine," in Thematic Cartography for the Society, Cham, Switzerland: Springer, 2014, pp. 13-22.

C. Yuan, Y. Zhang, and Z. Liu, "A Survey on Technologies for Automatic Forest Fire Monitoring, Detection, and Fighting Using Unmanned Aerial Vehicles and Remote Sensing Techniques," Canadian Journal of Forest Research, Vol. 45, pp. 783 - 792, March 2015.

T.F. Keenan, D.Y. Hollinger, G. Bohrer, D. Dragoni, J.W. Munger, H.P. Schmid, and A.D. Richardson, "Increase in Forest Water-Use Efficiency as Atmospheric Carbon Dioxide Concentrations Rise," Nature, Vol. 499, No. 7458, pp. 324-327, 2013.

P Ganesan, B.S. Sathish, and G. Sajiv, "A Comparative Approach of Identification and Segmentation of Forest Fire Region in High Resolution Satellite Images," 2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare (Startup Conclave) , 2016, pp. 1-6.

Y. Kaufman and C. Justice, "Algorithm Technical Background Document: MODIS Fire Products," MODIS Technical Document, pp. 1-77, November 1998.

T. Ahmed, S.V. Naidu, D. Singh, and R. Balasubramanian, "An Approach to Detect Hotspots with INSAT-3D Data," 2015 National Conference on. IEEE Recent Advances in Electronics & Computer Engineering (RAECE), 2015, pp. 267-270.

C.M. Frey, C. Kuenzer, and S. Dech, "Cross-Comparison of Daily Land Surface Temperature Products from NOAA-AVHRR and MODIS," in Thermal Infrared Remote Sensing, Dordrecht, Netherlands: Springer, 2013, pp. 215-231.

Rajeshwari A. and Mani N.D., "Estimation of Land Surface Temperature of Dindigul District Using Landsat 8 Data," International Journal of Research in Engineering and Technology, Vol. 3, No. 5, pp. 122-126, 2014.

J.A.M. Ruiz, D. Riaño, M. Arbelo, N.H.F. French, S.L. Ustin, and M.L. Whiting, "Burned Area Mapping Time Series in Canada (1984–1999) from NOAA-AVHRR LTDR: A Comparison with Other Remote Sensing Products and Fire Perimeters," Remote Sensing of Environment, Vol. 117, pp. 407-414, 2012.

S.-B. Duan, Z.-L. Li, B.-H. Tang, H. Wu, and R. Tang, "Generation of a Time-Consistent Land Surface Temperature Product from MODIS Data," Remote Sensing of Environment, Vol. 140, pp. 339-349, 2014.

L. Giglio, W. Schroeder, and C.O. Justice, "The Collection 6 MODIS Active Fire Detection Algorithm and Fire Products," Remote Sensing of Environment, Vol. 178, pp. 31-41, 2016.

S. Veraverbeke, F. Sedano, S.J. Hook, J.T. Randerson, Y. Jin, and B. Rogers, "Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data," International Journal of Wildland Fire, Vol. 23, No. 5, pp. 655-667, 2014.

Q. Renard, R Pélissier, and B.R. Ramesh, "Environmental Susceptibility Model for Predicting Forest Fire Occurrence in the Western Ghats of India," International Journal of Wildland Fire, Vol. 21, pp. 368-379, 2012.

V. Vipin, "Image Processing Based Forest Fire Detection," International Journal of Emerging Technology and Advanced Engineering, Vol. 2, No. 2, pp. 87-95, February 2012.

G. Qiu, T. J. Terrell, and M.R. Varley, "Improved Image Compression using Backpropagation Networks," Workshop on Neural Network Applications and Tools, 1993, pp. 73-81.

Y. Bai, Y. Li, X. Wang, J. Xie, and C. Li, "Air Pollutants Concentrations Forecasting Using Back Propagation Neural Network Based on Wavelet Decomposition with Meteorological Conditions," Atmospheric Pollution Research, Vol. 7, No. 3, pp. 557-566, May 2016.

"Modul Kebakaran Hutan dan Lahan," Pemerintah Provinsi Kalimantan Tengah, pp. 1-67, 2017.

T. Handayani, A.J. Santoso, and Y. Dwiandiyanta, "Pemanfaatan Data Terra Modis untuk Identifikasi Titik Api pada Kebakaran Hutan Gambut (Studi Kasus Kota Dumai Provinsi Riau)," Seminar Nasional Teknologi Informasi dan Komunikasi, 2014, pp. 461-467.

G. Strang, "Wavelets and Dilation Equations: A Brief Introduction," SIAM Review, Vol. 31, No. 4, pp. 614-627, 1989.

P. Rieder, J. Gotze, J.A. Nossek, and C.S. Burrus, "Parameterization of Orthogonal Wavelet Transforms and Their Implementation," IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Vol. 45, No. 2, pp. 217-226, 1998.

S.P. Kosbatwar and S.K. Pathan, "Pattern Association for Character Recognition by Back-Propagation Algorithm Using Neural Network Approach," International Journal of Computer Science and Engineering Survey, Vol. 3, No. 1, pp. 127-134, 2012.

M.A. Hossain, M.M. Rahman, U.K. Prodhan, and M.F. Khan, "Implementation of Back-Propagation Neural Network for Isolated Bangla Speech Recognition," International Journal of Information Sciences and Techniques (IJIST), Vol. 3, No. 4, pp. 1-9, 2013.


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