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Correction to Fire 2022, 5(6), 215.
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Correction

Correction: Wang et al. Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China. Fire 2022, 5, 215

1
State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230027, China
2
College of Forestry and Landscape Architecture, Anhui Agricultural University, Hefei 230036, China
*
Author to whom correspondence should be addressed.
Submission received: 9 February 2023 / Accepted: 14 February 2023 / Published: 21 February 2023
(This article belongs to the Special Issue Spatial Statistics and Operational Research for Wildfires Management)

Error in Figure

In the original publication [1], there was a mistake in Figure 1 as published. Some figure labels in Figure 1a are missing due to the resizing of Figure 1 for editing purposes. The corrected Figure 1 appears below.

Text Correction

There was an error in the original publication [1]. There was a lack of explanation on the abbreviations used as column captions in Table 2.
A correction has been made to 2. Materials and Methods, Paragraph below Table 1:
Detailed statistical data for the identified fire cases between 2003 and 2017 are reported in Table 2, and all the fire ignition causes are specified by their abbreviations so as to reduce the column spaces. Although natural ignition sources contain two items, i.e., lightning and spontaneous combustion of humic substances, the respective category was omitted from the table, solely because of the negligible fire case numbers and limitation of the page space.
Another error was found in the original publication [1]. There was a lack of indication of the sub-figure numbers in the description of the phenomena observed in Figure 1.
A correction has been made to 3. Results, 3.1. Characteristics of Forest Fire Causes and Their Distribution Patterns, Paragraph below Figure 1:
Fire incidents in relation to agricultural activities were contributed by nine items, including burning the grass in wasteland (uncultivated land) to produce charcoal (BGW), burning slash in the mountains for afforestation (BSA), burning pasture to generate fertile land (BPL), kilning (KLN), and burning surface fuels to create fuelbreaks (BCF). Among these items, the majority of fires were initiated by BGW, taking up a portion of ~77% on average (Figure 1b). Another nine items were sorted into the category of FUA, including smoking (SMK), cooking and heating in wildland (CHW), burning joss paper at grave sites (BJP), burning the mountain to repel beasts (BMB), children playing with fire (CPF), and fire ignited by people with dementia (FPD). Among them, SMK and BJP accounted for an accumulated portion of ~62% (Figure 1c). Fire incidents caused by SPC were rare by comparison with those induced by LTN (Figure 1d). The classification of all these fire causes and their contribution to the fire numbers were a true reflection of the agricultural production, living styles and culture in the remote areas. For instance, many graves are located at the forest edges, and the BJP activities are routinely carried out during the Qingming Festival and the Winter Solstice every year. A little carelessness could result in a fire causing damage to forest resources and human properties nearby.
One more error was found in the original publication [1]. There was a lack of explanation on some important features in Figure 3c.
A correction by adding one more paragraph has been made to 3. Results, 3.1. Characteristics of Forest Fire Causes and Their Distribution Patterns, The second paragraph after Figure 2:
As revealed in Table 2 and Figure 1c, the power line lodging (PLL) is also an ignition source that can cause forest fire, with its annual numbers fluctuating from several tens to more than one hundred. As a result, their ratios to the reference year vary irregularly in a narrow range (Figure 3c). Although the ratio of the fire numbers by NIS in 2017 is about three times higher than that in 2008, this does not mean there were very big fire numbers caused by natural factors in this year, given that the fire numbers caused by NIS in 2008 were less than one hundred. Furthermore, the significant increase in the fire numbers by NIS could be a reflection of the growing fire risk from natural sources due to the eminent climate change in recent years.
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Wang, H.; Jin, B.; Zhang, K.; Aktar, S.; Song, Z. Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China. Fire 2022, 5, 215. [Google Scholar] [CrossRef]
Figure 1. Averaged fire number distribution in terms of fire causes throughout the years studied: (a) among FAA, FUA, OHR, NIS and UNF, (b) within the fire causes of FAA, (c) within FUA and (d) from both OHR and NIS.
Figure 1. Averaged fire number distribution in terms of fire causes throughout the years studied: (a) among FAA, FUA, OHR, NIS and UNF, (b) within the fire causes of FAA, (c) within FUA and (d) from both OHR and NIS.
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Share and Cite

MDPI and ACS Style

Wang, H.; Jin, B.; Zhang, K.; Aktar, S.; Song, Z. Correction: Wang et al. Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China. Fire 2022, 5, 215. Fire 2023, 6, 80. https://doi.org/10.3390/fire6030080

AMA Style

Wang H, Jin B, Zhang K, Aktar S, Song Z. Correction: Wang et al. Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China. Fire 2022, 5, 215. Fire. 2023; 6(3):80. https://doi.org/10.3390/fire6030080

Chicago/Turabian Style

Wang, Haihui, Bangxin Jin, Kaixuan Zhang, Shamima Aktar, and Zhilong Song. 2023. "Correction: Wang et al. Effectiveness in Mitigating Forest Fire Ignition Sources: A Statistical Study Based on Fire Occurrence Data in China. Fire 2022, 5, 215" Fire 6, no. 3: 80. https://doi.org/10.3390/fire6030080

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