Forest and land fires spatial model in Riau Province , Indonesia (original) (raw)
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Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue Department Malaysia can use the end result of this study in preparation for the land and forest fires in the future.
Probabilistic modelling of wildfire occurrence based on logistic regression, Niassa Reserve, Mozambique., 2019
Fires are one of the main factors for disturbances in Niassa Reserve-Mozambique, with economic and environmental impacts. There are cyclical records of fire occurrences across the reserve. However, studies on the main causative factors and identification of more susceptible locations are very limited. In this perspective, this study had as objectives: (1) determine the main significant factors for wildfire occurrences; (2) Map the probability of wildfire occurrences, using logistic regression. Independent variables included vegetation index (NDVI), climatic, topographic and socioeconomic data. The analysis period was from 2001 to 2015 and comprised the months with more occurrences of wildfire (May to December). According to the results, the main factors that determine the occurrence of fires were: NDVI, temperature, elevation, followed by precipitation, slope, relative humidity and human settlements. The spatial distribution of probability of fire occurrence reveals that zones with high and very high risk are located at the west and central west zones (areas with higher accumulation of dry biomass); medium risk zones are located in the centre of the reserve, while in central east and east zones the probability of fire occurrence is low and very low risk. Results showed that the expectation of wildfire ignition using logistic regression presented good precision (area under the curve 74%). ARTICLE HISTORY
2001
Analisis pemetaan lengkap (Cemplete Mapping Analysis) yang berbasis sistem informasi geografis (SIG) digunakan untuk melakukan pembobotan terhadap nilai “vulnerability” dari faktor-faktor resiko dalam rangka membangun suatu model dan memetakan kelas-kelas resiko kebakaran liar. Ada dua faktor utama, yaitu faktor lingkungan fisik dan aktifitas manusia yang sangat mempengaruhi terjadinya kebakaran hutan. Model yang ditemukan pada saat ini memperlihatkan bahwa kelembaban relatif adalah faktor terpenting diantara faktor lingkungan fisik, sementara jarak terhadap pusat-pusat pemukiman merupakan faktor terpenting diantara faktor aktifitas manusia. Diketahui juga bahwa, terjadinya kebakaran liar lebih banyak dipengaruhi oleh faktor aktifitas manusia daripada faktor lingkungan fisik. Pada studi ini, wilayah resiko kebakaran liar dibagi atas 3 kelas, dimana ditemukan bahwa kelas resiko kebakaran tertinggi mendominasi lokasi penelitian, selanjutnya diikuti dengan kelas resiko sedang dan renda...
Indonesian Forest Fire - A Quantitave Assessment
2003
The Indonesian forest fires have affected the environment since biomass burning has released aerosol, black carbon, and other particles to the atmosphere. In this research, an algorithm for assessing forest fire potential is tested for Kalimantan Island, Indonesia. It is based on a fuel model map modified from the US-National Fire Danger Rating System (US-NFDRS), Normalized Difference Vegetation Index (NDVI), and weather data. The Indonesian fuel model map was derived using the global 4-minute land cover data set consisting of 13 classes. The NDVI data was derived from the global 4-minute NOAA-AVHRR data. The output is presented as a monthly Fire Potential Index (FPI) from 1981 to 1993 and compared with trends in fire occurrences over the same time period. A case study illustrates correlation between the FPI and the hot-spot distribution derived from AVHRR data, as well as between the FPI and the Total Ozone Mapping Spectrometer (TOMS) Aerosol Index.