Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model
The Chure region, among the world's youngest mountains, stands out as highly susceptible to natural calamities, particularly forest fires. The region has consistently experienced forest fire incidents, resulting in the degradation of valuable natural and anthropogenic resources. Despite its vul...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844024045560 |
| _version_ | 1797226630902448128 |
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| author | Khagendra Prasad Joshi Gunjan Adhikari Divya Bhattarai Ayush Adhikari Saurav Lamichanne |
| author_facet | Khagendra Prasad Joshi Gunjan Adhikari Divya Bhattarai Ayush Adhikari Saurav Lamichanne |
| author_sort | Khagendra Prasad Joshi |
| collection | DOAJ |
| description | The Chure region, among the world's youngest mountains, stands out as highly susceptible to natural calamities, particularly forest fires. The region has consistently experienced forest fire incidents, resulting in the degradation of valuable natural and anthropogenic resources. Despite its vulnerability, there have been limited studies to understand the relationship of various causative factors for the recurring fire problem. Hence, to comprehend the influencing factors for the recurring forest fire problem and its extent, we utilized generalized linear modeling under binary logistic regression to combine the dependent variable of satellite detected fire points and various independent variables. We conducted a variance inflation factor (VIF) test and correlation matrix to identify the 14 suitable variables for the study. The analysis revealed that forest fires occurred mostly during the three pre-monsoon periods and had a significant positive relation with the area under forest, rangeland, bare-grounds, and Normalized Difference Vegetation Index (NDVI) (P < 0.05). Consequently, our model showed that the probability of fire incidents decreases with elevation, precipitation, and population density (P < 0.05). Among the significant variables, the forest areas emerges as the most influencing factor, followed by precipitation, elevation, area of rangeland, population density, NDVI, and the area of bare ground. The validation of the model was done through the area under the curve (AUC = 0.92) and accuracy (ACC = 0.89) assessments, which showed the model performed excellently in terms of predictive capabilities. The modeling result and the forest fire susceptible map provide valuable insights into the forest fire vulnerability in the region, offering baseline information about forest fires that will be helpful for line agencies to prepare management strategies to further prevent the deterioration of the region. |
| first_indexed | 2024-04-24T14:27:58Z |
| format | Article |
| id | doaj.art-755e9f2b48ac4fd594e182e49bc31558 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-24T14:27:58Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-755e9f2b48ac4fd594e182e49bc315582024-04-03T04:26:58ZengElsevierHeliyon2405-84402024-04-01107e28525Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear modelKhagendra Prasad Joshi0Gunjan Adhikari1Divya Bhattarai2Ayush Adhikari3Saurav Lamichanne4Kathmandu Forestry College, Tribhuvan University, Kathmandu, 44600, NepalInstitute of Forestry, Pokhara Campus, Tribhuvan University, Pokhara, NepalFaculty of Forestry, Agriculture and Forestry University, Hetauda, 44100, Nepal; Nepal Conservation and Research Center, Ratnanagar-6, Sauraha, Chitwan, NepalEnviromatics Nepal, Kathmandu, 44100, NepalFaculty of Forestry, Agriculture and Forestry University, Hetauda, 44100, Nepal; Nepal Conservation and Research Center, Ratnanagar-6, Sauraha, Chitwan, Nepal; Corresponding author. Faculty of Forestry, Agriculture and Forestry University, Hetauda, 44100, Nepal.The Chure region, among the world's youngest mountains, stands out as highly susceptible to natural calamities, particularly forest fires. The region has consistently experienced forest fire incidents, resulting in the degradation of valuable natural and anthropogenic resources. Despite its vulnerability, there have been limited studies to understand the relationship of various causative factors for the recurring fire problem. Hence, to comprehend the influencing factors for the recurring forest fire problem and its extent, we utilized generalized linear modeling under binary logistic regression to combine the dependent variable of satellite detected fire points and various independent variables. We conducted a variance inflation factor (VIF) test and correlation matrix to identify the 14 suitable variables for the study. The analysis revealed that forest fires occurred mostly during the three pre-monsoon periods and had a significant positive relation with the area under forest, rangeland, bare-grounds, and Normalized Difference Vegetation Index (NDVI) (P < 0.05). Consequently, our model showed that the probability of fire incidents decreases with elevation, precipitation, and population density (P < 0.05). Among the significant variables, the forest areas emerges as the most influencing factor, followed by precipitation, elevation, area of rangeland, population density, NDVI, and the area of bare ground. The validation of the model was done through the area under the curve (AUC = 0.92) and accuracy (ACC = 0.89) assessments, which showed the model performed excellently in terms of predictive capabilities. The modeling result and the forest fire susceptible map provide valuable insights into the forest fire vulnerability in the region, offering baseline information about forest fires that will be helpful for line agencies to prepare management strategies to further prevent the deterioration of the region.http://www.sciencedirect.com/science/article/pii/S2405844024045560Forest fireBinary logistic regressionSpatial modelingSusceptible map |
| spellingShingle | Khagendra Prasad Joshi Gunjan Adhikari Divya Bhattarai Ayush Adhikari Saurav Lamichanne Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model Heliyon Forest fire Binary logistic regression Spatial modeling Susceptible map |
| title | Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model |
| title_full | Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model |
| title_fullStr | Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model |
| title_full_unstemmed | Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model |
| title_short | Forest fire vulnerability in Nepal's chure region: Investigating the influencing factors using generalized linear model |
| title_sort | forest fire vulnerability in nepal s chure region investigating the influencing factors using generalized linear model |
| topic | Forest fire Binary logistic regression Spatial modeling Susceptible map |
| url | http://www.sciencedirect.com/science/article/pii/S2405844024045560 |
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