FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA
<p align="justify">Fire is one of the major natural disturbances in forest areas in Indonesia. Fires occur frequently and widely especially in the El-Nino period. In 2015, Indonesian forest fires spread extensively, including in Mount Masigit Kareumbi (MMK). As MMK is a conservation...
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id-itb.:276482018-09-26T13:33:57ZFIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA (NIM : 11514057), HAIRATUNNISA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/27648 <p align="justify">Fire is one of the major natural disturbances in forest areas in Indonesia. Fires occur frequently and widely especially in the El-Nino period. In 2015, Indonesian forest fires spread extensively, including in Mount Masigit Kareumbi (MMK). As MMK is a conservation area, forest fire potentially threaten biodiversity conservation inside the area. In order to support an effective fire prevention, the characteristics of fire distribution within the area should be properly understood. This study aims to estimate the burnt areas during the 2015 fire, to map fire risk, and to analyze variables that contribute to the distribution of fire risk in MMK. The burnt areas were identified by using the change of Normalized Burn Ratio (NBR) index derived from Landsat 8 OLI satelite imagery that was recorded pre and post fire 2015, followed by verification and vegetation analysis using transect method in some locations with fire occurences in 2015. Maximum Entropy (Maxent) was applied to map the probability of fire occurrence by using presence point of fire occurences in 2015 and some predictor variables, which include both natural factors (topography, climate, and fuel) and human factors (accesibility). Based on the change of NBR index, the estimated burnt areas in MMK and surrounding area can be identified with normalized distance value (D) of 1.37. Maxent modelling shows that high risk of fire mostly distributes around the boundary of MMK with the average annual precipitation variable having the highest contribution (36%) to the risk distribution. We used the Area Under ROC Curve (AUC) to evaluate the performance of the model, and obtained an AUC of 0.976, which indicates a high accuracy. Vegetation analysis shows that several pioneers species such as Trema orientalis, Schima wallichii, Visenia umbellata, and Homalanthus populneus dominate the burnt areas. In relation to fire control, this study suggests to prioritize the high risk areas, among others by accelerating the growth of some dominant species, including by replanting program. <br /> <p align="justify"> text |
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<p align="justify">Fire is one of the major natural disturbances in forest areas in Indonesia. Fires occur frequently and widely especially in the El-Nino period. In 2015, Indonesian forest fires spread extensively, including in Mount Masigit Kareumbi (MMK). As MMK is a conservation area, forest fire potentially threaten biodiversity conservation inside the area. In order to support an effective fire prevention, the characteristics of fire distribution within the area should be properly understood. This study aims to estimate the burnt areas during the 2015 fire, to map fire risk, and to analyze variables that contribute to the distribution of fire risk in MMK. The burnt areas were identified by using the change of Normalized Burn Ratio (NBR) index derived from Landsat 8 OLI satelite imagery that was recorded pre and post fire 2015, followed by verification and vegetation analysis using transect method in some locations with fire occurences in 2015. Maximum Entropy (Maxent) was applied to map the probability of fire occurrence by using presence point of fire occurences in 2015 and some predictor variables, which include both natural factors (topography, climate, and fuel) and human factors (accesibility). Based on the change of NBR index, the estimated burnt areas in MMK and surrounding area can be identified with normalized distance value (D) of 1.37. Maxent modelling shows that high risk of fire mostly distributes around the boundary of MMK with the average annual precipitation variable having the highest contribution (36%) to the risk distribution. We used the Area Under ROC Curve (AUC) to evaluate the performance of the model, and obtained an AUC of 0.976, which indicates a high accuracy. Vegetation analysis shows that several pioneers species such as Trema orientalis, Schima wallichii, Visenia umbellata, and Homalanthus populneus dominate the burnt areas. In relation to fire control, this study suggests to prioritize the high risk areas, among others by accelerating the growth of some dominant species, including by replanting program. <br />
<p align="justify"> |
format |
Final Project |
author |
(NIM : 11514057), HAIRATUNNISA |
spellingShingle |
(NIM : 11514057), HAIRATUNNISA FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA |
author_facet |
(NIM : 11514057), HAIRATUNNISA |
author_sort |
(NIM : 11514057), HAIRATUNNISA |
title |
FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA |
title_short |
FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA |
title_full |
FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA |
title_fullStr |
FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA |
title_full_unstemmed |
FIRE RISK ANALYSIS IN MOUNT MASIGIT KAREUMBI, WEST JAVA |
title_sort |
fire risk analysis in mount masigit kareumbi, west java |
url |
https://digilib.itb.ac.id/gdl/view/27648 |
_version_ |
1822922320753197056 |