Implementation DBSCAN algorithm to clustering satellite surface temperature data in Indonesia

Authors

  • Ariel Kristianto Universitas Kristen Satya Wacana, Salatiga
  • Eko Sediyono Universitas Kristen Satya Wacana, Salatiga
  • Kristoko Dwi Hartomo Universitas Kristen Satya Wacana, Salatiga

DOI:

https://doi.org/10.26594/register.v6i2.1913

Keywords:

cluster, DBSCAN, forest fire, Landsat-8, silhouette

Abstract

Forest and land fires are national and international problems. The frequency of fires in one of Indonesia's provinces, Riau, is a significant problem. Knowing where to repair the burn is essential to prevent more massive fires. Fires occur because of a fire triangle, namely fuel, oxygen, and heat. The third factor can be seen through remote sensing. Using the Landsat-8 satellite, named the Enhanced Vegetation Index (EVI) variable, Normalized Burn Area (NBR), Normal Difference Humidity Index (NDMI), Normal Difference Difference Vegetation Index (NDVI), Soil Adapted Vegetation Index (SAVI), and Soil Surface Temperature (LST). DBSCAN, as a grouping algorithm that can group the data into several groups based on data density. This is used because of the density of existing fire data, according to the character of this algorithm. The selected cluster is the best cluster that uses Silhouette Coefficients, eps, and minutes value extracted from each variable, so there is no noise in the resulting cluster. The result is more than 0, and the highest is the best cluster result. There are 5 clusters formed by clustering, each of which has its members. This cluster is formed enough to represent the real conditions, cluster which has a high LST value or has an NBR value. A high  LST value indicates an increase in the area's temperature; a high NBR value indicates a fire has occurred in the area. The combination of LST and NBR values indicates the area has experienced forest and land fires. This study shows that DBSCAN clustered fire and surface temperature data following data from the Central Statistics Agency of Riau Province. Proven DBSCAN can cluster satellite imagery data in Riau province into several clusters that have a high incidence of land fires.

Author Biographies

Ariel Kristianto, Universitas Kristen Satya Wacana, Salatiga

Department of Information Systems

Eko Sediyono, Universitas Kristen Satya Wacana, Salatiga

Department of Information Systems

Kristoko Dwi Hartomo, Universitas Kristen Satya Wacana, Salatiga

Department of Information Systems

References

D. F. Pramesti, M. T. Furqon and C. Dewi, "Implementasi Metode K-Medoids Clustering Untuk Pengelompokan Data Potensi Kebakaran Hutan/Lahan Berdasarkan Persebaran Titik Panas (Hotspot)," Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, vol. 1, no. 9, pp. 723-732, 2017.

H. K. Muchtar, H. Ibrahim and S. Raodhah, "Analisis Efisiensi Dan Efektivitas Penerapan Fire Safety Management Dalam Upaya Pencegahan Kebakaran di PT. Consolidaetd Electric Power Asia (Cepa) Kabupaten Wajo," Higiene: Jurnal Kesehatan Lingkungan, vol. 2, no. 2, pp. 91-98, 2016.

D. R. Amliana, Y. Prasetyo and A. Sukmono, "Analisis Perbandingan Nilai Ndvi Landsat7 dan Landsat8 Padakelas Tutupan Lahan (Studi Kasus: Kota Semarang, Jawa tengah)," Jurnal Geodesi Undip, vol. 5, no. 1, pp. 264-274, 2016.

M. T. Mustafa, K. I. Hassoon, H. M. Hussain and M. H. Abd, "Using Water Indices (NDWI, MNDWI, NDMI, WRI and AWEI) to Detect Physical and Chemical Parameters by Apply Remote Sensing and Gis Techniques," International Journal of Research - Granthaalayah, vol. 5, no. 10, pp. 117-128, 2017.

D. Arisanty, S. Adyatma, M. Muhaimin and A. Nursaputra, "Landsat 8 OLI TIRS Imagery Ability for Monitoring Post Forest Fire Changes," Pertanika J. Sci. & Technol, vol. 27, no. 3, pp. 1105-1120, 2019.

M. A. Ganie and A. Nusrath, "Determining the Vegetation Indices (NDVI) from Landsat 8 Satellite Data," International Journal of Advanced Research (IJAR), vol. 4, no. 8, pp. 1459-1463, 2016.

E. K. Andana, "Pengembangan Data Citra Satelit Landsat-8 untuk Pemetaan Area Tanaman Hortikultura dengan Berbagai Metode Algoritma Indeks Vegetasi (Studi Kasus: Kabupaten Malang dan Sekitarnya)," in Prosiding Seminar Nasional Manajemen Teknologi XXI, Surabaya, 2015.

S. M. C. Nogueira, M. A. Moreira and M. M. L. Volpato, "Relationship Between Coffee Crop Productivity and Vegetation Indexes Derived from Oli/Landsat-8 Sensor Data with and without Topographic Correction," Engenharia Agrícola, vol. 38, no. 3, pp. 387-394, 2018.

N. R. Apriyanti, R. A. Nugroho and O. Soesanto, "Algoritma k-Means Clustering dalam Pengolahan Citra Digital Landsat," KLIK (Kumpulan jurnaL Ilmu Komputer), vol. 2, no. 2, 2015.

P. P. Adikara, R. C. Wihandika, F. Utaminingrum, Y. A. Sari, M. A. Fauzi, D. Syauqy and R. Maulana, "Regresi linier berbasis clustering untuk deteksi dan estimasi halangan pada smart wheelchair," Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 3, no. 1, pp. 11-16, 2017.

M. Mustaqim, B. Warsito and B. Surarso, "Kombinasi Synthetic Minority Oversampling Technique (SMOTE) dan Neural Network Backpropagation untuk menangani data tidak seimbang pada prediksi pemakaian alat kontrasepsi implan," Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 5, no. 2, pp. 116-127, 2019.

N. M. A. S. Devi, I. K. G. D. Putra and I. M. Sukarsa, "Implementasi Metode Clustering DBSCAN pada Proses Pengambilan Keputusan," Lontar Komputer, vol. 6, no. 3, pp. 185-191, 2015.

I. D. Id, "Modifikasi DBSCAN (Density-Based Spatial Clustering with Noise) Pada Objek 3 Dimensi," Jurnal Komputer Terapan, vol. 3, no. 1, pp. 41-52, 2017.

K. N. Ahmed and T. A. Razak, "An Overview of Various Improvements of DBSCAN Algorithm in Clustering Spatial Databases," International Journal of Advanced Research in Computer and Communication Engineering, vol. 5, no. 2, pp. 360-363, 2016.

D. Poursanidis, N. Chrysoulakis and Z. Mitraka, "Landsat 8 vs. Landsat 5: A comparison based on urban and peri-urban land cover mapping," International Journal of Applied Earth Observation and Geoinformation, vol. 35, pp. 259-269, 2015.

G. Mancino, A. Ferrara, A. Padula and A. Nolè, "Cross-Comparison between Landsat 8 (OLI) and Landsat 7 (ETM+) Derived Vegetation Indices in a Mediterranean Environment," Remote Sens, vol. 12, no. 2, p. 291, 2020.

T. D. Acharya and I. Yang, "Exploring Landsat 8," International Journal of IT, Engineering and Applied Sciences Research (IJIEASR), vol. 4, no. 4, pp. 4-10, 2015.

A. Zubaidah, S. Sulma, Suwarsono, Y. Vetrita, M. Priyatna and K. A. D. Sukowati, "Akurasi Luas Areal Kebakarandari Data Landsat-8 Oli di Wilayah Kalimantan," Majalah Ilmiah Globë, vol. 19, no. 1, pp. 21-32, 2017.

U. Avdan and G. Jovanovska, "Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data," Journal of Sensors, vol. 2016, 2016.

D. Jeevalakshmi, S. N. Reddy and B. Manikiam, "Land Surface Temperature Retrieval from LANDSAT data using Emissivity Estimation," International Journal of Applied Engineering Research, vol. 12, no. 20, pp. 9679-9687, 2017.

D. K. Sunaryo and M. Z. Iqmi, "Pemanfaatan Citra Landsat 8 untuk Pendeteksian dan Mengetahui Hubungan Kerapatan Vegetasi Terhadap Suhu Permukaan (Studi Kasus: Kota Bandar Lampung, Provinsi Lampung)," Spectra, vol. 25, no. 13, pp. 55-72, 2015.

D. P. Wiguna, "Identifikasi Suhu Permukaan Tanah dengan Metode Konversi Digital Number Menggunakan Teknik Penginderaan Jauh dan Sistem Informasi Geografi," Jurnal Teknologi Informasi dan Komunikasi, vol. 6, no. 2, pp. 59 - 69, 2017.

S. Rahman and V. Mesev, "Change Vector Analysis, Tasseled Cap, and NDVI-NDMI for Measuring Land Use/Cover Changes Caused by a Sudden Short-Term Severe Drought: 2011 Texas Event," Remote Sensing, vol. 11, no. 19, 2019.

T. Long, Z. Zhang, G. He, W. Jiao, C. Tang, B. Wu, X. Zhang, G. Wang and R. Yin, "30 m Resolution Global Annual Burned Area Mapping Based on Landsat Images and Google Earth Engine," Remote Sensing, vol. 11, no. 5, 2019.

L. Gowri and K. R. Manjula, "Evaluation of Various Vegetation Indices for Multispectral Satellite Images," International Journal of Innovative Technology and Exploring Engineering (IJITEE), vol. 8, no. 10, pp. 3494-3500, 2019.

M. Hahsler, M. Piekenbrock and D. Doran, "dbscan: Fast Density-Based Clustering with R," Journal of Statistical Software, vol. 91, no. 1, 2019.

X. She, L. Zhang, Y. Cen, T. Wu, C. Huang and M. H. A. Baig, "Comparison of the Continuity of Vegetation Indices Derived from Landsat 8 OLI and Landsat 7 ETM+ Data among Different Vegetation Types," Remote Sens, vol. 7, pp. 13485-13506, 2015.

M. Arekhi, C. Goksel, F. B. Sanli and G. Senel, "Comparative Evaluation of the Spectral and Spatial Consistency of Sentinel-2 and Landsat-8 OLI Data for Igneada Longos Forest," ISPRS Int. J. Geo-Inf, vol. 8, no. 2, 2019.

Z. Wu, B. Middleton, R. Hetzler, J. Vogel and D. Dye, "Vegetation Burn Severity Mapping Using Landsat-8 and WorldView-2," Photogrammetric Engineering & Remote Sensing, vol. 81, no. 2, p. 143–154, 2015.

U. C. Nugroho and D. D. Domiri, "Identification of Land Surface Temperature Distribution of Geothermal Area in Ungaran Mount by using Landsat 8 Imagery," International Journal of Remote Sensing and Earth Sciences, vol. 12, no. 2, p. 143–150, 2015.

S. Wang, M. H. A. Baig, S. Liu, H. Wan, T. Wu and Y. Yang, "Estimating the area burned by agricultural fires from Landsat 8 Data using the Vegetation Difference Index and Burn Scar Index," International Journal of Wildland Fire, vol. 27, p. 217–227, 2018.

T. A. Warner, N. S. Skowronski and M. R. Gallagher, "High spatial resolution burn severity mapping of the New Jersey Pine Barrens with WorldView-3 near-infrared and shortwave infrared imagery," International Journal of Remote Sensing, vol. 38, no. 2, pp. 598-616, 2017.

C. E. Blinn, M. N. House, R. H. Wynne, V. A. Thomas, T. R. Fox and M. Sumnall, "Landsat 8 based leaf area index estimation in loblolly pine plantations," Forests, vol. 10, no. 3, 2019.

P. Stych, J. Lastovicka, R. Hladky and D. Paluba, "Evaluation of the Influence of Disturbances on Forest Vegetation Using the Time Series of Landsat Data: A Comparison Study of the Low Tatras and Sumava National Parks," ISPRS Int. J. Geo-Inf., vol. 8, no. 2, 2019.

N. Kaoungku, K. Suksut, R. Chanklan, K. Kerdprasop and N. Kerdrasop, "The silhouette width criterion for clustering and association mining to select image features," International journal of machine learning and computing, vol. 8, no. 1, pp. 1-5, 2018.

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Published

2020-07-02

How to Cite

[1]
A. Kristianto, E. Sediyono, and K. D. Hartomo, “Implementation DBSCAN algorithm to clustering satellite surface temperature data in Indonesia”, Register: Jurnal Ilmiah Teknologi Sistem Informasi, vol. 6, no. 2, pp. 109–118, Jul. 2020.

Issue

Vol. 6 No. 2 (2020): July

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Article

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