Geo-informatics based multi-criteria decision analysis (MCDA) through analytic hierarchy process (AHP) for forest fire risk mapping in Palamau Tiger Reserve, Jharkhand state, India

2020 ◽  
Vol 129 (1) ◽  
Author(s):  
Binita Kumari ◽  
Arvind Chandra Pandey
Keyword(s):  
Analytic Hierarchy Process ◽  
Decision Analysis ◽  
Forest Fire ◽  
Fire Risk ◽  
Risk Mapping ◽  
Analytic Hierarchy ◽  
Multi Criteria Decision Analysis ◽  
Tiger Reserve ◽  
Hierarchy Process ◽  
Forest Fire Risk

scholarly journals Forest Fire Risk Assessment using Fuzzy Analytic Hierarchy Process

2018 ◽  
Vol 13 (3) ◽  
pp. 307-316 ◽  
Author(s):  
DIVYA MEHTA ◽  
PARMINDER KAUR BAWEJA ◽  
R K AGGARWAL
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
High Risk ◽  
Analytic Hierarchy Process ◽  
Forest Fire ◽  
Fire Risk ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Forest Fire Risk

Forest fires in the mid hills of Himachal Pradesh are mostly related to human activities. More than 90% of fires are originated from either deliberate or involuntary causes. The purpose of study is linked to identification of forest fire risk factors in 19 villages under Nauni and Oachhghat Panchayats. The methodology paradigm applied here is based on knowledge and fuzzy analytic hierarchy process (FAHP) techniques. Knowledge-based criteria involve socio-economic and biophysical themes for risk assessment. The risk factors are identified according to past occurrence of fire. Fuel type scores highest weight (0.3109) followed by aspect (0.2487), agricultural workers (0.1865), nutritional density (0.1244), population density (0.0622), elevation (0.0311), literacy rate (0.0207) and distance from road (0.0155) in descending order. In the study area applying FAHP, 24.96% of total area was classified under high-risk prone area, 21.69% area classified under high-risk, 34.63% area under moderate risk, while 18.61% area under low risk. The results were in accordance with actual fire occurrences in the past years.

scholarly journals Modelagem espacial de risco de incêndio florestal para o município de Inhambupe, Bahia, Brasil

2016 ◽  
Vol 36 (85) ◽  
pp. 41 ◽  
Author(s):  
Larissa Alves Secundo White ◽  
Benjamin Leonardo Alves White ◽  
Genésio Tâmara Ribeiro
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Risk Map ◽  
Map Algebra ◽  
Analytic Hierarchy ◽  
Land Occupation ◽  
Forest Protection ◽  
Burned Areas ◽  
Hierarchy Process ◽  
Forest Fire Risk

A modelagem do risco espacial de incêndios florestais tem o objetivo de determinar as regiões mais susceptíveis ao fogo, baseando-se em variáveis que representam a facilidade de ignição e de propagação do fogo. Nesse contexto, utilizando-se das variáveis: sistema viário, densidade demográfica, uso e ocupação do solo, malha hidrográfica, inclinação e orientação das encostas, foram elaborados mapas de riscos preliminares, que, posteriormente à ponderações das mesmas pelo método AHP, foram integradas por meio da calculadora Raster em um mapa final de risco de incêndio florestal para o município de Inhambupe, Bahia, Brasil. Com base no modelo utilizado, 75,46% da área de estudo apresenta-se classificada como de maior risco, representado pelas classes “alto”, “muito alto” e “extremo”. Ao comparar o mapa final do risco de incêndio florestal para a área de estudo com o histórico de áreas queimadas, verificou-se que 94,83% dos registros de incêndios florestais estão alocados nas áreas de maior risco.Spatial modeling of forest fire risk for the Municipality of Inhambupe, Bahia State, BrazilSpatial modeling of forest fire risk has the aim to determine areas most susceptible to fire based on variables that represent facility of ignition and propagation. This work developed a forest fire risk map for the Municipality of Inhambupe, Bahia State, Brazil, by elaborating thematic maps of the following variables: road system, population density, land occupation and use, watershed network, slope and aspect. These were evaluated by the analytic hierarchy process and integrated with map algebra. Based on the developed model, 75.46% of the studied area was classified as “high”, “very high” and “extreme high” fire risk. When comparing the forest fire risk map with historical data of burned areas, 95% of the fires were in these areas.Index terms: Forest protection; Fire susceptibility; Risk map

scholarly journals Model Perangkingan Proyek Kontruksi Pada Asosiasi Kontraktor Menggunakan Fuzzy AHP

2016 ◽  
Vol 2 (1) ◽  
pp. 73-81 ◽  
Author(s):  
Denny Jean Cross Sihombing ◽  
Albertus Joko Santoso ◽  
Sapty Rahayu
Keyword(s):  
Analytic Hierarchy Process ◽  
Decision Analysis ◽  
Fuzzy Ahp ◽  
Fuzzy Analytic Hierarchy Process ◽  
Analytic Hierarchy ◽  
Multi Criteria Decision Analysis ◽  
Hierarchy Process

Pemilihan proyek potensial dari paket lelang konstruksi yang ditawarkan merupakan permasalahan yang kompleks pada asosiasi kontraktor. Paket lelang yang ditawarkan oleh pemerintah melalui Kementerian Pekerjaan Umum (PU) untuk wilayah Sumatera Utara tahun 2013 terdapat 96 paket, tahun 2014 terdapat 69 paket. Dari banyaknya paket yang ditawarkan, masing-masing paket memiliki beberapa kriteria sebagai persyaratan, salah satunya adalah pengalaman perusahaan. Artikel ini fokus pada perangkingan proyek berdasarkan evaluasi proyek yang sudah dikerjakan sebelumnya. Keberhasilan suatu proyek ditentukan oleh beberapa kriteria, maka pendekatan yang digunakan Multi Criteria Decision Analysis (MCDA) dengan metode Fuzzy Analytic Hierarchy Process (FAHP), data diperoleh dari Asosiasi Kontraktor Air Indonesia (AKAINDO) Sumatera Utara. Hasilnya adalah rekomendasi proyek potensial berdasarkan skor tertinggi, yaitu sub-bidang perpipaan.

scholarly journals GIS-BASED MULTI-CRITERIA DECISION ANALYSIS FOR FOREST FIRE RISK MAPPING

2017 ◽  
Vol IV-4/W4 ◽  
pp. 25-30 ◽  
Author(s):  
A. E. Akay ◽  
A. Erdoğan
Keyword(s):  
High Risk ◽  
Decision Analysis ◽  
Forest Fire ◽  
Forest Fires ◽  
Tree Species ◽  
Fire Risk ◽  
Multi Criteria Decision Analysis ◽  
Extreme Risk ◽  
Forested Areas ◽  
Forest Fire Risk

The forested areas along the coastal zone of the Mediterranean region in Turkey are classified as first-degree fire sensitive areas. Forest fires are major environmental disaster that affects the sustainability of forest ecosystems. Besides, forest fires result in important economic losses and even threaten human lives. Thus, it is critical to determine the forested areas with fire risks and thereby minimize the damages on forest resources by taking necessary precaution measures in these areas. The risk of forest fire can be assessed based on various factors such as forest vegetation structures (tree species, crown closure, tree stage), topographic features (slope and aspect), and climatic parameters (temperature, wind). In this study, GIS-based Multi-Criteria Decision Analysis (MCDA) method was used to generate forest fire risk map. The study was implemented in the forested areas within Yayla Forest Enterprise Chiefs at Dursunbey Forest Enterprise Directorate which is classified as first degree fire sensitive area. In the solution process, "extAhp 2.0" plug-in running Analytic Hierarchy Process (AHP) method in ArcGIS 10.4.1 was used to categorize study area under five fire risk classes: extreme risk, high risk, moderate risk, and low risk. The results indicated that 23.81 % of the area was of extreme risk, while 25.81 % was of high risk. The result indicated that the most effective criterion was tree species, followed by tree stages. The aspect had the least effective criterion on forest fire risk. It was revealed that GIS techniques integrated with MCDA methods are effective tools to quickly estimate forest fire risk at low cost. The integration of these factors into GIS can be very useful to determine forested areas with high fire risk and also to plan forestry management after fire.

scholarly journals Correction to: Application of GIS and AHP Method in Forest Fire Risk Zone Mapping: a Study of the Parambikulam Tiger Reserve, Kerala, India

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
S. Nikhil ◽  
Jean Homian Danumah ◽  
Sunil Saha ◽  
Megha K. Prasad ◽  
A. Rajaneesh ◽  
...  
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Ahp Method ◽  
Risk Zone ◽  
Tiger Reserve ◽  
Forest Fire Risk ◽  
Application Of Gis
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