Hotspot Spatial Patterns Using SNNP-VIIRS for Fire Potential Monitoring

Kumalawati, Rosalina; Yuliarti, Astinana; Ali, Syamani D.; Murliawan, Karnanto Hendra; Rijanta, Rijanta; Susanti, Ari; Saputra, Erlis

doi:https://doi.org/10.1155/2023/3121862

International Journal of Forestry Research

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Abstract Introduction Experimental Discussion Conclusion Data Availability Conflicts of Interest Acknowledgments References Copyright Related Articles

Research Article | Open Access

Volume 2023 | Article ID 3121862 | https://doi.org/10.1155/2023/3121862

Hotspot Spatial Patterns Using SNNP-VIIRS for Fire Potential Monitoring

Rosalina Kumalawati,¹Astinana Yuliarti,²Syamani D. Ali,³Karnanto Hendra Murliawan,⁴Rijanta Rijanta,⁵Ari Susanti,⁶and Erlis Saputra⁵

Academic Editor: Nikolaos D. Hasanagas

Received11 Feb 2022

Revised03 Jun 2022

Accepted05 Apr 2023

Published24 Apr 2023

Abstract

The province of East Kalimantan is officially designated as the State Capital because the area has the least risk of disaster, even though it cannot be separated from disasters such as forest and land fires. This study aims to determine the spatial pattern of hotspots using SNPP-VIIRS for monitoring potential fires. The research used the descriptive-analytic method to identify the research area and collect secondary data. Secondary data is spatial and nonspatial data consisting of hotspot data from the recording of the SNPP -VIIRS image, including frequency and distribution of hotspots. The data usage from 2012–2021 using SNPP-VIIRS morning and evening recordings. The study results show that the spatial pattern of potential hotspots in the capital city of a new country is quite varied. The spatial pattern of hotspots shows that Kutai Kartanegara Regency as one of the locations for the new State Capital, has the highest number of hotspots, namely 38,970 with the highest accuracy in East Kalimantan Province, namely, 1,616 (low), 36,253 (nominal), and 1,101 (high). The potential for fire disasters in Kutai Kartanegara Regency as an IKN location is high, so planning is urgently needed for future fire prevention, mitigation, and prevention strategies. The spatial pattern of hotspots is known, so it can be used to monitor potential fires and minimize fire occurrences.

1. Introduction

Disasters occur in developed and developing countries, including fire disasters. Fire disasters have occurred in Indonesia since 1980, occur almost every year, and have become a national and international disaster [1–3]. This disaster not only threatens life but also damages buildings [4] and local people’s livelihoods [5, 6]. Forest and land fires have a detrimental impact on the environment [7–9], social and economic [7, 9, 10], health [9, 11], transportation [12], ecosystem damage leading to loss of biodiversity, and land degradation [2, 13–15].

The intensity of land and forest fires increases every year, especially during the dry season and when an el-Nino occurs [16]. Forests are an essential component of various ecosystem services [17, 18], such as for fauna and vegetation conservation [19] which increases significantly when the atmosphere changes and carbon dioxide concentrations increase. Namely to reduce greenhouse emissions [20–24], and it also reduces carbon sequestration, biodiversity conservation, supply water, and protection against soil erosion [25]. Forests are crucial for human welfare and environmental health [26]. Seeing this, forests must always be protected from disasters, including fires.

Fires in Indonesia are recurring events and contribute to the potential impacts of climate change [27–29]. The possible effects of climate change [30] from fires are numerous. Fires in Indonesia, including Kalimantan, have received international attention because they cause haze problems for neighboring countries [31–34], increase greenhouse gas emissions and CO2 concentrations, and raise the earth’s surface temperature. The greenhouse gas that significantly impacts the environment is carbon dioxide (CO2) [35].

The increase in temperature causes the El-Nino Southern Oscillation (ENSO) phenomenon, which impacts global ecology and climate [36, 37]. Global climate change causes prolonged drought, one of the triggering factors for land and forest fires [38]. Burning forests and lands results in adverse effects such as loss of biodiversity, unpredictable climatic conditions, and destruction of terrestrial biodiversity ecosystems [39, 40]. Fires often occur in peat areas because peat when dry conditions reduce groundwater, making it more easily burned.

Indonesia is one of the developing countries with the world’s largest peatland [41]. Peatlands in Indonesia are spread over Sumatra, Kalimantan, and Papua [42]. In 2015, the existing peatlands experienced fires and were damaged so that they decreased, including in East Kalimantan Province. Peat fires occur below the surface [43] and are difficult to extinguish. Subsurface peat fires will produce prolonged periods of smoke. Time to clear forest areas in peat ecosystems combined with fire results in uncontrolled fires [44]. Peatland fires in the long term will cause environmental degradation and cause environmental degradation. The most significant cause of environmental degradation is massive deforestation on peatlands.

In 2018, Forest Watch Indonesia (FWI) reported that East Kalimantan Province contributed the highest levels of deforestation and forest degradation. The deforestation and forest degradation rate doubled from 89 ha/year in 2017 to 157 ha/year in 2018. The official announcement of moving the capital city to East Kalimantan in 2019 added to the complexity of issues related to deforestation [45]. Many factors affect both physical and human forest fires in East Kalimantan [46–49]. Physical factors include fuel, land topography, hydrology, weather, and climate. Human factors are related to land management practices [48] and people’s ignorance of clearing land by burning for land preparation [50].

Moving the location of the national capital will result in the conversion of land functions. Most of the existing land will be converted into agricultural, industrial, and residential areas. This land conversion creates new problems for the Environment and humans, one of which is land fires. As a result of land fires, it can also cause various other issues that result in losses such as social, economic, and human health being disrupted because the smog causes respiratory problems, environmental pollution, and ecosystem damage [12, 51–53], transportation system disturbances, conflicts between neighboring countries, and others.

The province of East Kalimantan is designated as the capital city of the State because the area has the least disaster risk, even though it is one of the provinces that cannot be separated from disasters such as forest and land fires [45]. Fires can be detected from the number of hotspots in each area [54]. Fire incidents are identified through the presence and intensity of hotspots [33, 48, 55]. Hotspot data for each area can be obtained from recording optical remote sensing images [56] and radar sensors [57].

Remote sensing imagery is an appropriate and accessible geospatial technology for monitoring fires [58]. Fires usually occur in huge areas, so the use of geospatial technology, in this case, remote sensing imagery, is the most appropriate choice to deal with fires [59]. The remote sensing image used in this research is the SNPP-VIIRS image which is then mapped for monitoring and developing strategies [60] for dealing with disasters. SNPP-VIIRS is currently used for regional and global hotspot detection, with a focus on hotspot detection [61–64]. Existing hotspots don’t always appear as fires. Hotspots with a high level of confidence have a high potential to become fires [65–68]. The hotspots distribution in East Kalimantan is relatively high, especially in IKN locations (see Table 1).

It is feared that the distribution of hotspots is relatively high; it is feared that it will accelerate deforestation and land degradation, coupled with the relocation of IKN locations in the area. The rapid movement of deforestation and degradation will contribute to environmental damage, namely greenhouse gas emissions, loss of biodiversity, damage to peatlands, and a decrease in the quality of life of the world’s people. It is necessary to conduct a particular study on fire disasters for better development plans and monitoring of potential fires in the future of the new capital city. Based on the above background, it is necessary to conduct a study entitled “Spatial Patterns of Hotspots using SNPP-VIIRS for Monitoring Potential Fires.”

2. Experimental

2.1. Material

Globally [69], fire is a national and international disaster. The impact of haze fires reaches Malaysia, Singapore, and Brunei Darussalam, requiring serious attention [70–72]. Forest and land fires are a severe problem and have a significant impact on the ecosystem environment [52, 73]. The largest fires also occurred in Indonesia in 2015 due to El Nino [44, 74, 75]. Fires in Indonesia in 2015 mostly occurred in Kalimantan and Sumatra. Fires in Sumatra and Kalimantan occur almost every year, with large areas and long durations [76]. Fires occur due to natural and human factors [9, 77, 78].

Land fires after 2015 decreased from 2016 to 2018. Based on data released by Global Forest Watch, deforestation in Indonesia significantly decreased in 2017 and 2018. After 2018, deforestation increased again until 2019. Increased deforestation, followed by increased land degradation, caused long-term environmental problems. It is feared that deforestation and degradation will continue to grow as the National Capital City in DKI Jakarta will be moved to East Kalimantan Province. The reason for moving the state capital to East Kalimantan Province is the decline in environmental carrying capacity and capacity in DKI Jakarta, marked by traffic congestion, pollution, a lowering of groundwater levels, and the emergence of various disasters [79]. It is feared that the relocation of the location of the national capital will also be followed by the emergence of various types of disasters, including fires.

Fire disasters often occur in the dry season [15]. Apart from the dry season, fires are also caused by deforestation in peat ecosystems. Fires can be detected by the number of hotspots in each area. Not always existing hotspots can cause fires. Hotspot data is taken from the remote sensing satellite recording SNPP-VIIRS. Hotspot data obtained from SNPP-VIIRS provides information on the hotspot location and the fire incident location. The point of occurrence of fires reflects fire events that are separate from each other and describes fire events that are still ongoing and cannot be extinguished. The frequency of fires increases every year, so more in-depth research is needed to determine the spatial pattern of hotspots using SNPP-VIIRS (see Figure 1).

The spatial pattern of hotspots can be identified using geospatial technology at various scales [80]. Geospatial analysis related to the spatial design of hotspots can find out which areas have a high potential for fires so as to prevent future fires [81]. The spatial pattern of hotspots is known so that future fire prevention, mitigation, and prevention strategies can be planned [82–84]. Seeing this, it is imperative to research the spatial pattern of hotspots, especially in the capital city of a new country. This research on spatial patterns of hotspots is carried out to support the smooth development planning for the location of the national capital and prepare communities in IKN locations to be resilient to disasters.

2.2. Method

The research location includes the location of the New State Capital in the Province of East Kalimantan. East Kalimantan Province is one of the provinces with the potential for forest and land fires to occur almost every year. This study uses descriptive-analytical methods to identify research areas and collect secondary data. Secondary data were obtained from government agencies in the form of spatial and nonspatial data consisting of hotspot data from the recording of SNPP-VIIRS imagery, frequency, and hotspots distribution. The study took the observation time of hotspot distribution from 2012 to 2021 using SNPP VIIRS. SNPP VIIRS recorded morning and evening [85, 86]. Research variables can be seen in Table 2.

The spatial pattern of hotspots is seen from the intensity and distribution of fire occurrences in each region. The power and distribution of fires were carried out using a hotspot data approach [33, 48]. The hotspot data used is a hotspot with a confidence level of 30% [55, 87]. Hotspot data 30% belongs to the nominal to the high class, which shows a relatively high predictive rate of fire events in the field and requires precautions that require vigilance [54, 88–89] (see Table 3).

The analytical method used is spatio-temporal analysis to show the distribution of fire characteristics that occur, both spatially (space) and temporally (time) [33, 49, 55]. The data processing and analysis technique is based on the Geographic Information System, namely ArcGIS 10.1 software. The analysis is divided into two stages of modeling, namely the scoring and overlay models. The scoring model is the stage of scoring and weighting on raster data, in which there is a mathematical operation process according to the parameters. The overlay stage is combining the two layers to create a new output feature class that contains information from both inputs [90]. Density analysis of fire events was carried out [49, 91]. This is done to identify potential fires in each research area so that potential fires can be identified, which can then be monitored for fires.

3. Result and Discussion

Forest and peatland fires to overcome them by knowing the distribution of hotspots, making laws for those who burn land intentionally will be imprisoned, building canals/reservoirs, and constructing boreholes [92]. A hotspot is an area that has a higher temperature than its surroundings, has the potential to cause fires, and can be detected by satellite [66, 76]. The satellite used to detect hotspots in this study is SNPP-VIIRS.

The location of IKN is East Kalimantan Province, one of the provinces with forest and land fires that ranks third in Indonesia [93]. Seeing this, it is essential to conduct this research so that the planning and implementation of disaster management in the new IKN locations can be more effective. The research was conducted by taking hotspot data from 2012 to 2021. The existing hotspot data processing results obtained the distribution and distribution of hotspots in East Kalimantan in each district. The distribution of hotspots in East Kalimantan fluctuate every year. After 2015 had experienced a decline, in 2019 there was an increase again in each region. The results of hotspot processing in 2012–2021 show that Kutai Kartanegara Regency, as the new IKN location, has the highest number of hotspots, namely 38,970 (see Tables 4 and 5).

The rate of fire occurrence or the number of hotspots is identified using the fire density value. Fire density can be seen from the level of confidence, namely low, medium and high confidence levels. The higher the hotspot density and confidence level, the greater the potential fire threat [48, 55]. The greater the potential danger of fire in an area, the greater the environmental damage. The high number of hotspots in the research area is located in the new IKN location, namely, in Kutai Kartanegara Regency.

Kutai Kartanegara Regency has the highest number of hotspots with the highest accuracy in East Kalimantan Province, namely, 1,616 (low), 36,253 (nominal), and 1,101 (high) (see Table 5). The results of processing the spatial pattern of hotspots can be seen as the potential for fires in each existing area. The potential for fires from the results of spatial pattern processing using spatial analysis indicates that Kutai Kartanegara Regency is one of the locations that will become a new IKN location and has a high potential for fire disasters. Spatial analysis can determine fire density and the area burned repeatedly [94]. Spatial analysis helps determine priority areas in the handling forest and land fires [95]. Seeing the high potential for fire disasters in Kutai Kartanegara Regency, it is urgently needed to plan for future fire prevention, mitigation, and prevention strategies [82–84] (see Figure 2). In addition, it is also necessary to carry out regular monitoring and early warning quickly so that larger negative impacts can be minimized, including loss of life, property, and environmental damage [96].

4. Conclusion

(a)Kutai Kartanegara Regency as the new IKN location has the highest number of hotspots, namely, 38,970(b)Kutai Kartanegara Regency has the highest number of hotspots with the highest accuracy in East Kalimantan Province, namely 1,616 (Low), 36,253 (Nominal), and 1,101 (High)(c)The potential for fire disasters in Kutai Kartanegara Regency as an IKN location is high, so planning is urgently needed for future fire prevention, mitigation, and prevention strategies.

Data Availability

The data in this study were obtained from reading hotspots through SNPP VIIRS images.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This project is financially supported by the Research Program with contract number 362/E4.1/AK.04.PT/2021 on South Asian-Europe Joint Funding and Cooperation Indonesia-The Netherlands.

References

K. Budiningsih, “Implementasi kebijakan pengendalian kebakaran hutan dan lahan di Provinsi Sumatera Selatan,” Jurnal Analisis Kebijakan Kehutanan, vol. 14, no. 2, pp. 165–186, 2017.
View at: Publisher Site | Google Scholar
D. Dirhamsyah, D. B. Utama, N. Widyaningrum, and I. D. K. Widana, “Kearifan lokal dan partisipasi persekutuan dayak kalimantan timur dalam menghadapi bencana kebakaran hutan dan lahan,” PERSPEKTIF, vol. 9, no. 2, pp. 314–321, 2020.
View at: Publisher Site | Google Scholar
A. S. Thoha, B. H. Saharjo, R. Boer, and M. Ardiansyah, “Strengthening community participation in reducing GHG emission from forest and peatland fire,” IOP Conference Series: Earth and Environmental Science, vol. 122, no. 1, Article ID 012076, 2018.
View at: Publisher Site | Google Scholar
R. T. Hamad, A. Al-Rahim, S. Nagwa, M. H. Moghazy, and H. A. Al-Moneam, “Explosion effects on archaeological glass, conservation and protection strategy,” International Journal of Conservation Science, vol. 12, no. 1, 2021.
View at: Google Scholar
E. Saputra, “Beyond fires and deforestation: tackling land subsidence in peatland areas, a case study from Riau, Indonesia,” Land, vol. 8, no. 5, p. 76, 2019.
View at: Publisher Site | Google Scholar
A. Susanti, O. Karyanto, A. Affianto et al., “Understanding the impacts of recurrent peat fires in padang island–riau province, Indonesia,” Jurnal Ilmu Kehutanan, vol. 12, no. 1, pp. 117–126, 2018.
View at: Publisher Site | Google Scholar
K. M. Khalwani and L. Syaufina, “Kebakaran hutan gambut (studi kasus di Taman nasional sebangau, provinsi kalimantan tengah),” Risalah Kebijakan Pertanian dan Lingkungan, vol. 2, no. 3, pp. 214–229, 2015.
View at: Google Scholar
A. T. Ratnaningsih and S. R. Prastyaningsih, “Dampak kebakaran hutan gambut terhadap subsidensi di hutan tanaman industri,” Wahana Forestra: Jurnal Kehutanan, vol. 12, no. 1, pp. 37–43, 2017.
View at: Publisher Site | Google Scholar
L. Tacconi, “Preventing fires and haze in southeast asia,” Nature Climate Change, vol. 6, no. 7, pp. 640–643, 2016.
View at: Publisher Site | Google Scholar
R. P. Nugraha, A. Fauzi, and M. Ekayani, “Ekonomi pertanian, sumberdaya, dan lingkungan: analisis pendapatan usaha pertanian dan peternakan,” Jurnal Ekonomi Pertanian, Sumberdaya dan Lingkungan, vol. 2, pp. 1–14, 2019.
View at: Google Scholar
A. J. Wulan and S. Subagio, “Efek asap kebakaran hutan terhadap gambaran histologis saluran pernapasan,” Medical Journal of Lampung University, vol. 5, pp. 162–167, 2016.
View at: Google Scholar
A. A. Fitriany, P. J. Flatau, K. Khoirunurrofik, and N. F. Riama, Assessment on the Use of Meteorological and Social Media Information for Forest Fires Detection and Prediction in Riau, Indonesia, 2021.
R. Ajin, A.-M. Loghin, P. Vinod, and M. Jacob, “Forest fire, risk zone mapping, using RS and GIS techniques: a study in achankovil forest division, Kerala, India,” Journal of Earth, Environment and Health Sciences, vol. 2, no. 3, pp. 109–115, 2016.
View at: Publisher Site | Google Scholar
D. Sugiarto, K. Gandasasmita, and Lailan, “Analisis risiko kebakaran hutan dan lahan di Taman nasional rawa aopa watumohai dengan pemanfaatan pemodelan spasial,” Globe, vol. 15, no. 1, pp. 62–67, 2013.
View at: Google Scholar
N. Yulianti, “Pengenalan bencana kebakaran dan kabut asap lintas batas [studi kasus eks proyek lahan gambut sejuta hektar] terdapat dalam situs,” 2018, http://www.unesco.or.id/publication/shs/Final_Ver_Pengenalan_Karhutla.pdf.
View at: Google Scholar
H. Herawati and H. Santoso, “Tropical forest susceptibility to and risk of fire under changing climate: a review of fire nature, policy and institutions in Indonesia,” Forest Policy and Economics, vol. 13, no. 4, pp. 227–233, 2011.
View at: Publisher Site | Google Scholar
S. K. Chettri, G. Sharma, K. S. Gaira et al., “Forest resource use pattern in fringe villages of barsey Rhododendron sanctuary and singalila national park of khangchendzonga landscape, India,” International Journal of Financial Research, vol. 2021, Article ID 8856988, 11 pages, 2021.
View at: Publisher Site | Google Scholar
V. Kimpouni, J. D. D. Nzila, N. Watha-Ndoudy, M. I. Madzella-Mbiemo, S. Yallo Mouhamed, and J. P. Kampe, “Exploring local people’s perception of ecosystem services in djoumouna periurban forest, brazzaville, Congo,” International Journal of Financial Research, vol. 2021, Article ID 6612649, 17 pages, 2021.
View at: Publisher Site | Google Scholar
S. Tadese, T. Soromessa, T. Bekele, and G. Gebeyehu, “Woody species composition, vegetation structure, and regeneration status of majang forest biosphere reserves in southwestern Ethiopia,” International Journal of Financial Research, vol. 2021, Article ID 5534930, 22 pages, 2021.
View at: Publisher Site | Google Scholar
J. Campbell, G. Alberti, J. Martin, and B. E. Law, “Carbon dynamics of a ponderosa pine plantation following a thinning treatment in the northern Sierra Nevada,” Forest Ecology and Management, vol. 257, no. 2, pp. 453–463, 2009.
View at: Publisher Site | Google Scholar
D. W. Johnson and P. S. Curtis, “Effects of forest management on soil C and N storage: meta analysis,” Forest Ecology and Management, vol. 140, no. 2-3, pp. 227–238, 2001.
View at: Publisher Site | Google Scholar
T. Karjalainen, A. Pussinen, J. Liski et al., “An approach towards an estimate of the impact of forest management and climate change on the European forest sector carbon budget: Germany as a case study,” Forest Ecology and Management, vol. 162, no. 1, pp. 87–103, 2002.
View at: Publisher Site | Google Scholar
E. J. Sayer, L. Lopez-Sangil, J. A. Crawford et al., “Tropical forest soil carbon stocks do not increase despite 15 years of doubled litter inputs,” Scientific Reports, vol. 9, no. 1, pp. 18030–18039, 2019.
View at: Publisher Site | Google Scholar
G. K. Tarus and S. W. Nadir, “Effect of forest management types on soil carbon stocks in montane forests: a case study of eastern mau forest in Kenya,” International Journal of Financial Research, vol. 2020, Article ID 8862813, 10 pages, 2020.
View at: Publisher Site | Google Scholar
T. A. Olatoye, S. P. Mazinyo, A. S. Odeyemi, I. R. Orimoloye, and E. T. Busayo, “Forest systems services provisioning in africa: case of gambari forest reserve, ibadan, Nigeria,” International Journal of Financial Research, vol. 2021, Article ID 8823826, 6 pages, 2021.
View at: Publisher Site | Google Scholar
F. Mutesi, J. R. S. Tabuti, and D. Mfitumukiza, “Extent and rate of deforestation and forest degradation (1986–2016) in west bugwe central forest reserve, Uganda,” International Journal of Financial Research, vol. 2021, Article ID 8860643, 10 pages, 2021.
View at: Publisher Site | Google Scholar
B. Kumari and A. C. Pandey, “MODIS based forest fire hotspot analysis and its relationship with climatic variables,” Spatial Information Research, vol. 28, no. 1, pp. 87–99, 2020.
View at: Publisher Site | Google Scholar
H. Purnomo, B. Shantiko, S. Sitorus et al., “Fire economy and actor network of forest and land fires in Indonesia,” Forest Policy and Economics, vol. 78, pp. 21–31, 2017.
View at: Publisher Site | Google Scholar
Z. D. Tan, L. R. Carrasco, and D. Taylor, “Spatial correlates of forest and land fires in Indonesia,” International Journal of Wildland Fire, vol. 29, no. 12, pp. 1088–1099, 2020.
View at: Publisher Site | Google Scholar
R. H. Odom and W. M. Ford, “Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model,” International Journal of Financial Research, vol. 2021, Article ID 6650821, 16 pages, 2021.
View at: Publisher Site | Google Scholar
G. Meiwanda, “Kapabilitas pemerintah daerah provinsi riau: hambatan dan tantangan pengendalian kebakaran hutan dan lahan,” Jurnal Ilmu Sosial dan Ilmu Politik, vol. 19, no. 3, pp. 251–263, 2016.
View at: Publisher Site | Google Scholar
A. S. Suryani, “Penanganan asap kabut akibat kebakaran hutan di wilayah perbatasan Indonesia,” Aspirasi: Jurnal Masalah-masalah Sosial, vol. 3, no. 1, pp. 59–75, 2012.
View at: Google Scholar
L. Syaufina and I. S. Sitanggang, “Peatland fire detection using spatio-temporal data mining analysis in Kalimantan, Indonesia,” Journal of Tropical Forest Science, vol. 30, no. 2, pp. 154–162, 2018.
View at: Publisher Site | Google Scholar
V. Yuliarti and Irdayanti, “Peran Dinas Kota Pekanbaru dalam menanggulangi dampak kabut asap kebakaran hutan di Kota Pekanbaru,” Jurnal Penelitian Sosial Keagamaan, vol. 19, no. 1, 2016.
View at: Google Scholar
E. Missanjo and H. Kadzuwa, “Greenhouse gas emissions and mitigation measures within the forestry and other land use subsector in Malawi,” International Journal of Financial Research, vol. 2021, Article ID 5561162, 8 pages, 2021.
View at: Publisher Site | Google Scholar
C. D. Elvidge, D. Ziskin, K. E. Baugh et al., “A fifteen year record of global natural gas flaring derived from satellite data,” Energies, vol. 2, no. 3, pp. 595–622, 2009.
View at: Publisher Site | Google Scholar
M. J. Wooster, G. Roberts, G. L. W. Perry, and Y. J. Kaufman, “Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release,” Journal of Geophysical Research, vol. 110, no. 24, Article ID D24311, 2005.
View at: Publisher Site | Google Scholar
M. R. Amri, G. Yulianti, R. Yunus et al., Risiko Bencana Indonesia, BNPB, Jakarta, Indonesia, 2016.
W. Osei-Wusu, J. Quaye-Ballard, T. Antwi, N. L. Quaye-Ballard, and A. Awotwi, “Forest loss and susceptible area prediction at sefwi wiawso district (SWD), Ghana,” International Journal of Financial Research, vol. 2020, Article ID 8894639, 18 pages, 2020.
View at: Publisher Site | Google Scholar
R. Sousa-Silva, Q. Ponette, K. Verheyen, A. Van Herzele, and B. Muys, “Adaptation of forest management to climate change as perceived by forest owners and managers in Belgium,” Forest Ecosystems, vol. 3, no. 1, pp. 22–11, 2016.
View at: Publisher Site | Google Scholar
A. P. Widanarko, “Upaya badan restorasi gambut dan korea forest service dalam merestorasi lahan gambut melalui desa peduli gambut di Provinsi kalimantan barat 2016-2020,” Jurnal Ilmu Hubungan Internasional, vol. 8, no. 1, pp. 345–359, 2020.
View at: Google Scholar
M. Osaki, D. Nursyamsi, M. Noor, and H. Segah, “Peatland in Indonesia,” in Tropical Peatland Ecosystems, pp. 49–58, Springer, Tokyo, Japan, 2016.
View at: Google Scholar
M. Noor, Kebakaran Lahan Gambut [Peatland Fire] (In Bahasa), UGM Press), Yogyakarta, Indonesia, 2019.
S. E. Page, F. Siegert, J. O. Rieley, H. D. V. Boehm, A. Jaya, and S. Limin, “The amount of carbon released from peat and forest fires in Indonesia during 1997,” Nature, vol. 420, no. 6911, pp. 61–65, 2002.
View at: Publisher Site | Google Scholar
F. A. Hakim, J. Banjarnahor, R. S. Purwanto, H. K. Rahmat, and I. D. K. K. Widana, “Pengelolaan obyek pariwisata menghadapi potensi bencana di Balikpapan sebagai penyangga ibukota negara baru,” Nusantara: Jurnal Ilmu Pengetahuan Sosial, vol. 7, no. 3, pp. 607–612, 2020.
View at: Google Scholar
M. E. Cattau, M. E. Harrison, I. Shinyo, S. Tungau, M. Uriarte, and R. DeFries, “Sources of anthropogenic fire ignitions on the peat-swamp landscape in Kalimantan, Indonesia,” Global Environmental Change, vol. 39, pp. 205–219, 2016.
View at: Publisher Site | Google Scholar
R. B. Edwards, R. L. Naylor, M. M. Higgins, and W. P. Falcon, “Causes of Indonesia’s forest fires,” World Development, vol. 127, Article ID 104717, 2020.
View at: Publisher Site | Google Scholar
S. Oliveira, J. M. C. Pereira, J. San-Miguel-Ayanz, and L. Lourenço, “Exploring the spatial patterns of fire density in Southern Europe using geographically weighted regression,” Applied Geography, vol. 51, pp. 143–157, 2014.
View at: Publisher Site | Google Scholar
A. S. Thoha, B. H. Saharjo, R. Boer, and M. Ardiansyah, “Characteristics and causes of forest and land fires in kapuas district, central kalimantan province, Indonesia,” Biodiversitas, vol. 20, no. 1, pp. 110–117, 2019.
View at: Publisher Site | Google Scholar
J. Irwandi and B. dan Ismail, “Upaya penanggulangan kebakaran hutan dan lahan di Desa purwajaya kecamatan loa janan kabupaten Kutai kertanegara kalimantan timur,” Jurnal AGRIFOR, vol. 15, no. 2, pp. 201–210, 2016.
View at: Google Scholar
E. Frankenberg, D. McKee, and D. Thomas, “Health consequences of forest fires in Indonesia,” Demography, vol. 42, no. 1, pp. 109–129, 2005.
View at: Publisher Site | Google Scholar
A. P. Kirana, I. S. Sitanggang, and L. Syaufina, “Hotspot pattern distribution in peat land area in Sumatera based on spatio temporal clustering,” Procedia Environmental Sciences, vol. 33, pp. 635–645, 2016.
View at: Publisher Site | Google Scholar
N. A. Ulya and S. Yunardy, “Analisis dampak kebakaran hutan di Indonesia terhadap distribusi pendapatan masyarakat,” Jurnal penelitian sosial dan ekonomi kehutanan, vol. 3, no. 2, pp. 133–146, 2006.
View at: Publisher Site | Google Scholar
LAPAN, Informasi Titik Panas (Hotspot) Kebakaran Hutan/lahan, Pusat Pemanfaatan Penginderaan Jauh, Jakarta, Indonesia, 2016.
A. S. Thoha, B. H. Saharjo, R. Boer, and M. Ardiansyah, “Spatiotemporal distribution of peatland fires in kapuas district, central kalimantan province, Indonesia,” Agriculture, Forestry and Fisheries, vol. 3, no. 3, pp. 163–170, 2014.
View at: Publisher Site | Google Scholar
T. Waryono, “Pengembangan model identifikasi daerah bekas kebakaran hutan dan lahan (burned area) menggunakan citra modis di kalimantan (model development of burned area identification using modis imagery in kalimantan),” Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital, vol. 10, no. 2, 2013.
View at: Google Scholar
M. A. Belenguer-Plomer, E. Chuvieco, and M. A. Tanase, “Sentinel-1 based algorithm to detect burned areas,” in Proceedings of the Conference 11th EARSeL Forest Fires SIG, Chania, Greece, September, 2017.
View at: Google Scholar
F. Ahmad, L. Goparaju, and A. Qayum, “Himalayan forest fire characterization in relation to topography, socio-economy and meteorology parameters in Arunachal Pradesh, India,” Spatial Information Research, vol. 26, no. 3, pp. 305–315, 2018.
View at: Publisher Site | Google Scholar
A. Laha, S. Singh, U. Mishra, and M. Singh, in Estimating Spatiotemporal Dynamics of Forest Fire Hazard Using Analytical Hierarchy Process and Geostatistical Methods in Similipal Biosphere Reserve, India, EGU General, 2021.
H. Nguyen Trong, T. D. Nguyen, and M. Kappas, “Land cover and forest type classification by values of vegetation indices and forest structure of tropical lowland forests in central vietnam,” International Journal of Financial Research, vol. 2020, Article ID 8896310, 18 pages, 2020.
View at: Publisher Site | Google Scholar
D. Peterson and J. Wang, “A sub-pixel-based calculation of fire radiative power from MODIS observations: 2. Sensitivity analysis and potential fire weather application,” Remote Sensing of Environment, vol. 129, pp. 231–249, 2013.
View at: Publisher Site | Google Scholar
D. Peterson, J. Wang, C. Ichoku, E. Hyer, and V. Ambrosia, “A sub-pixel-based calculation of fire radiative power from MODIS observations: 1,” Remote Sensing of Environment, vol. 129, pp. 262–279, 2013.
View at: Publisher Site | Google Scholar
B. Zhukov, E. Lorenz, D. Oertel, M. Wooster, and G. Roberts, “Spaceborne detection and characterization of fires during the bi-spectral infrared detection (BIRD) experimental small satellite mission (2001–2004),” Remote Sensing of Environment, vol. 100, no. 1, pp. 29–51, 2006.
View at: Publisher Site | Google Scholar
M. Zhizhin, C. D. Elvidge, F. C. Hsu, and K. E. Baugh, “Using the short-wave infrared for nocturnal detection of combustion sources in VIIRS data,” Proceedings of the Asia-Pacific Advanced Network, vol. 35, no. 0, pp. 49–61, 2013.
View at: Publisher Site | Google Scholar
R. Kumalawati, Strategi penanganan hotspot pada setiap penggunaan lahan akibat kebakaran hutan dan lahan di Kabupaten Banjar Kalimantan Selatan. Project Report, LPPM Universitas Lambung Mangkurat, Banjarmasin. Indonesia, 2016.
R. Kumalawati, A. Dianita, and E. Elisabeth, “Penyebab kebakaran hutan dan lahan gambut di kabupaten barito kuala provinsi kalimantan selatan,” Prosiding Seminar Nasional Ilmu Sosial, Lingkungan dan Tata Ruang: Manajemen Bencana di Era Revolusi Industri 5.0, 2019.
View at: Google Scholar
R. Kumalawati, H. M. Karnanto, Y. Astinana, R. Ismi, and W. A. Ersis, “Disaster communication to support mitigation wetlands fire in the future,” in Proceedings of the 35th IBIMA Conference, Seville, Spain, April, 2020.
View at: Google Scholar
R. Kumalawati, Nasruddin, H. M. Karnanto, Y. Astinana, and N. P. alfio, “Sebaran hotspot dan komunikasi masyarakat dalam menyikapi bencana kebakaran lahan gambut,” Seminar Nasional Geomatika, 2020.
View at: Google Scholar
A. Hegyi, C. Bulacu, H. Szilagyi, A. V. Lăzărescu, D. E. Colbu, and M. Sandu, “Waste management in the context of the development of sustainable thermal insulation products for the construction sector,” International Journal of Conservation Science, vol. 12, no. 1, 2021.
View at: Google Scholar
H. Hayasaka, K. Yamazaki, and D. Naito, “Weather conditions and warm air masses during active fire-periods in boreal forests,” Polar Science, vol. 22, Article ID 100472, 2019.
View at: Publisher Site | Google Scholar
F. Rasyid, “Problems and impact of forest fires,” Widyaiswara Circle Journal, vol. 1, no. 4, pp. 47–59, 2014.
View at: Google Scholar
A. Rowell and P. F. Moore, Global Review of forest Fires, Forests for Life Programme Unit, WWF International, 2000.
A. P. Kirana, I. S. Sitanggang, L. Syaufina, and A. Bhawiyuga, “Spatial and temporal clustering analysis of hotspot pattern distribution of critical land in kalimantan, Indonesia,” IOP Conference Series: Earth and Environmental Science, vol. 528, no. 1, Article ID 012042, 2020.
View at: Publisher Site | Google Scholar
M. E. Harrison, S. E. Page, and S. H. Limin, “The global impact of Indonesian forest fires,” Biologist, vol. 56, no. 3, pp. 156–163, 2009.
View at: Google Scholar
A. Nurkholis, A. D. Rahma, Y. Widyaningsih et al., Analisis Temporal Kebakaran Hutan dan Lahan di Indonesia Tahun 1997 dan 2015 (Studi Kasus Provinsi Riau), 2016.
N. M. Sari, N. Rachmita, and M. D. M. Manessa, “Hotspot distribution analysis in East Kalimantan province 2017-2019 to support forest and land fires mitigation,” Indonesian Journal of Environmental Management and Sustainability, vol. 4, no. 1, pp. 28–33, 2020.
View at: Publisher Site | Google Scholar
P. N. Ceccato, I. Jaya, J. Qian, M. K. Tippett, A. W. Robertson, and S. Someshwar, “Early warning and response to fires in Kalimantan, Indonesia,” Tech. Rep., International Research Institute for Climate and Society, New York, NY, USA), 2010, IRI Technical Report 10-14.
View at: Google Scholar
A. S. Thoha, B. H. Saharjo, R. Boer, and M. Ardiansyah, “Forest and land fires hazard level modeling: case study of Kapuas, Central Kalimantan,” in Disaster Risk Reduction in Indonesia, Springer, Cham, Switzerland, 2017.
View at: Google Scholar
A. Kurniadi, “Pemilihan ibukota negara republik Indonesia baru berdasarkan tingkat kebencanaan,” Jurnal Manajemen Bencana (JMB), vol. 5, no. 2, 2019.
View at: Publisher Site | Google Scholar
F. Ahmad and L. Goparaju, “Forest fire trend and influence of climate variability in India: a geospatial analysis at national and local scale,” Ekológia, vol. 38, no. 1, pp. 49–68, 2019.
View at: Publisher Site | Google Scholar
O. Abdi, B. Kamkar, Z. Shirvani, J. A. Teixeira da Silva, and M. F. Buchroithner, “Spatial-statistical analysis of factors determining forest fires: a case study from Golestan, Northeast Iran,” Geomatics, Natural Hazards and Risk, vol. 9, no. 1, pp. 267–280, 2018.
View at: Publisher Site | Google Scholar
D. Arisanty, M. Muhaimin, D. Rosadi, A. N. Saputra, K. P. Hastuti, and I. Rajiani, “Spatiotemporal patterns of burned areas based on the geographic information system for fire risk monitoring,” International Journal of Financial Research, vol. 2021, Article ID 2784474, 10 pages, 2021.
View at: Publisher Site | Google Scholar
M. D. Shekede, I. Gwitira, and C. Mamvura, “Spatial modelling of wildfire hotspots and their key drivers across districts of Zimbabwe, Southern Africa,” Geocarto International, vol. 36, no. 8, pp. 874–887, 2021.
View at: Publisher Site | Google Scholar
D. K. Wright, J. Kim, J. Park, J. Yang, and J. Kim, “Spatial modeling of archaeological site locations based on summed probability distributions and hot-spot analyses: a case study from the Three Kingdoms Period, Korea,” Journal of Archaeological Science, vol. 113, Article ID 105036, 2020.
View at: Publisher Site | Google Scholar
C. D. Elvidge, M. Zhizhin, F. C. Hsu, and K. E. Baugh, “VIIRS nightfire: satellite pyrometry at night,” Remote Sensing, vol. 5, no. 9, pp. 4423–4449, 2013.
View at: Publisher Site | Google Scholar
R. Jeswani, A. Kulshrestha, P. K. Gupta, and S. Srivastav, “Evaluation of the consistency of DMSP-OLS and SNPP-VIIRSnight-time light datasets,” Journal of Geometry, vol. 13, pp. 98–105, 2019.
View at: Google Scholar
A. Indradjad, J. Purwanto, and W. Sunarmodo, “Analisis tingkat akurasi titik hotspot Dari S-Npp Viirs dan Terra/Aqua Modis terhadap kejadian kebakaran,” Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital, vol. 16, no. 1, pp. 53–60, 2019.
View at: Google Scholar
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.
View at: Publisher Site | Google Scholar
LAPAN, “Informasi titik panas (hotspot) kebakaran hutan/lahan [information of forest/land fire hotspot,” Deputi Bidang Penginderaan Jauh LAPAN, Jakarta, Indonesia, 1st edition, 2016.
View at: Google Scholar
M. H. Price, Mastering ArcGIS, McGraw Hill Education, New York, NY, USA, 7th edition, 2015.
M. Usman, I. S. Sitanggang, and L. Syaufina, “Hotspot distribution analyses based on peat characteristics using density-based spatial clustering,” Procedia Environmental Sciences, vol. 24, pp. 132–140, 2015.
View at: Publisher Site | Google Scholar
Z. Mubarak, R. Kumalawati, and S. Adyatma, “Analisis peta persebaran titik api untuk kesesuaian persebaran sumur bor di Kecamatan Landasan Ulin Kota Banjarbaru Kalimantan Selatan,” JPG (Jurnal Pendidikan Geografi), vol. 5, no. 3, 2019.
View at: Google Scholar
Endrawati, Analysis of 2016 Hotspots and Areas of forest and Land Fires, Directorate of Inventory and Monitoring of Forest Resource. Director General of Forestry Planning and Environmental Management Ministry of Environment and Forestry, Jakarta, Indonesia, 2016.
C. S. Reddy, N. G. Bird, S. Sreelakshmi et al., “Identification and characterization of spatio-temporal hotspots of forest fires in South Asia,” Environmental Monitoring and Assessment, vol. 191, no. S3, pp. 791–817, 2019.
View at: Publisher Site | Google Scholar
E. S. M. M. Zahran, S. Shams, S. N. M. B. M. Said, E. S. M. M. Zahran, B. Gadong, and B. D. Brunei-Muara, “Validation of forest fire hotspot analysis in GIS using forest fire contributory factors,” Systematic Reviews in Pharmacy, vol. 11, pp. 249–255, 2020.
View at: Google Scholar
D. Rogers and V. Tsirkunov, “Costs and benefits of early warning systems,” Global assessment report, 2011.
View at: Google Scholar

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Copyright © 2023 Rosalina Kumalawati et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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