This proposal aims to analyze the spatial and temporal distribution of forest fires in Province 1 of Nepal using remote sensing and GIS. The study will use MODIS data from 2017-2022 to determine burnt area patterns and identify high-risk fire zones. Fieldwork will collect primary data on fire drivers through surveys and discussions. Data will be analyzed in GIS and statistics software to map fire trends, hotspots, and create a fire risk zonation map. The results will help authorities implement effective fire management and the report will be disseminated by June 2023.
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Fire Presentation.pptx
1. Forest Fire Distribution and Risk
Zonation of Province 1
A Research Proposal Presentation on
Presenter : Raj Kumar Shrestha
B.Sc. 4th year 1st semester
Purbanchal University College of Environment and Forestry
Advisor:
Prabin Pandit
Lecturer
Department of Silviculture and Forest Biology
2. Outline of the Presentation
Introduction
Rationale of study
Objectives
Methodology
Expected Outcomes
Time and Budgeting
References
2
3. Introduction
Forest fire is an any form of uncontrolled wildfire that burns in
the wildland vegetation.
Forest fires are a major natural hazard that affect the forest
ecosystem and cause damage to biodiversity, environment,
and wildlife. (Odum and Barrett, 2010)
Fire is a major factor in shaping the history of vegetation
globally, but can be destructive when uncontrolled. (Butry et
al. 2001)
Forest fires can be caused by both natural and human
activities and are dependent on various factors such as
topography, climate, land features, and season. (Dale et al.
2001)
Annually, approximately 0.4% of the global land surface is
burned, with tropical countries at high risk during dry and hot
seasons. (Randerson et al. 2012)
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4. Introduction
In Nepal, forest fires are a common and significant threat to the forest cover.
The highest density of forest fire in Nepal was in the Terai region with 6.4 hectares burnt per
km2. (Bhujel et al. 2017)
In 2016, there was a high incidence of forest fires in Nepal resulting in a loss of 268,618 ha
of forest cover during January-May. (Mandal 2019)
Remote Sensing and GIS are quick, cheap, and reliable tools for monitoring and detecting
forest fires.
There have been limited studies on the spatial and temporal distribution and risk assessment
of forest fires in Nepal.
This study aims to map the forest fire prone areas in Province One of Nepal using Remote
Sensing and GIS.
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5. Rationale of Study
The Department of Forests has recognized fire as a threat to ecosystems and biodiversity and
has allocated budget for fire control.
The mean annual temperature is increasing across the Terai and all four seasons are also
warming up (Jones et al., 2004).
The year 2009 was exceptionally disastrous with regard to forest fires in Nepal, with 358 fires
occurring in a single day in April 25, 2009. A total of 49 persons, including 13 army personnel,
died in 2009.
In 2016, forest fires destroyed 1.3 million hectares of forest, and killed eleven people.
Thousands of hectares of forest are destroyed by fire every year and produce more carbon
monoxide than automobile traffic.
Wildfire is emerging as burning issues in the present days of Province 1.
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6. Rationale of Study
Illam and Udayapur district are very high-risk forest fire zone (Martin et al, 2016).
There is a lack of systematic and complete studies regarding forest fires within the province
One.
The purpose of this study is to establish baseline data on forest fire information and understand
the causes, hotspots, and seasonality.
The results of the study will assist in prediction of future forest fires, reducing damage and cost
of firefighting, and preparation of fire strategies and plans.
The study will also help ensure the preservation of wild vegetation and prevent introduction of
invasive plants or diseases through fire suppression.
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7. Rationale of Study
General objective:
The general objective of this study is to analyse spatial and temporal forest fire trends and
susceptibility of Province One, Nepal.
Specific objective:
To compare the magnitude and temporal distribution pattern of forest fires in Province 1.
To identify the driving factors of forest fire incidence.
To prepare forest fire risk zonation map.
Research question
What is the distribution pattern, trend, factors responsible and major consequences of forest
fire?
What are the challenges in controlling forest fire? 7
8. Rationale of Study
Study Area
Province 1 of Nepal is located at 87°16'47" East
longitude and 26°27'15" North longitude
It covers an area of 25905 sq. km, making up
17.5% of the total area of Nepal
Elevation ranges from 70m to 8848m and 43.33%
of the area is forest with a tropical climate
The area is high in forest fire incidents and facing
issues of forest resource severity due to forest
fires
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9. Methodology
Data collection
Primary data collection
The primary data collection will be done through Focus
Group Discussion, Key informant, and direct field
observation.
Checklist and questionnaires will be prepared to achieve
the research objectives and will be pre-tested for
accuracy.
Biophysical data will be collected through randomly
chosen sample plots in the forest using the biomass
inventory guideline.
Field samples will be chosen in areas with homogeneous
land-use and the sample size will be 100*100 meters.
9
Secondary data collection:
The secondary data collection will be done through Fire
Information for Resource Management System (FIRMS)
MODIS data from NASA’s Terra and Aqua earth
monitoring satellites will be used to extract the location,
range, and distribution of fires.
Nepal’s digital map, digital topographic map, elevation
map, aspect map, slope map, proximity to road and
settlement, land cover map, and forest types will be
obtained from various departments.
Meteorological data like rainfall, humidity, and
temperature will be obtained from the Department of
Hydrology and Meteorology.
10. Methodology
Data analysis
Both qualitative and quantitative data will be analyzed
using excel and SPSS whereas the result will be
presented in bar graph, pie charts etc.
MODIS shape file will be overlaid on ArcGIS for spatial
and temporal analysis.
Ground truth verification will be done using GPS points
overlayed in MODIS data
Results will include: average count of forest fire per
month, monthly and yearly distribution of forest fire,
fire detection according to major forest type, frequency of
fire detection according to development region, seasonality of
fires and land cover of fires. 10
Burnt area Detection:
• The burnt area of the study area between 2017-
2022. Maximum and Minimum burnt area will
be counted throughout the period.
Trend Analysis:
• Trend of forest fire will be analyzed according to
year wise, month wise, forest type and season
wise through ARC GIS, EXCEL and SPSS.
Fire risk zone map preparation:
• Isarithmic map will be prepared from the data
obtained with categories the zones into 1. Very
high risk, 2. High risk, 3. Medium risk and 4.
Low risk.
11. Methodology
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Specific Objective Data Needs Data Collection Method(s) Method(s) of Data Analysis
1.To Identify trend and
burnt area patterns of
fire incidents.
FIRMS Provide
information on active fire
using MODIS and
ICIMOD provide information of active
forest fire in Nepal ( Arc GIS 10.8) Will
be used.
Total burnt area and total count will be
determined and trend will be analysis
2.To identify the
Perception of People
towards Forest Fire.
To know which factor is
creating more or less
forest fire in the district.
Primary (Focus Group Discussion
including local representatives and
CFUGS Members).
Likert Scale will be used.
3 .To Understand risk
pattern in Locality
factors.
To find out the major
hotspot area in the
Province 1.
Digital map, Topographic map –
Department of survey. Elevation map ,
Aspect map ,Slope map – Prepared from
DEM Using GIS 10.8
Distance from road and Settlement –
ICIMOD and Department of Survey.
Metrological data- Department of
Hydrology and Metrology.
Martin et al 2017, will be used. In this
study we use vegetation type, elevation ,
slope, temp., distance from road and
settlement to calculate the Fire Risk Index.
FRI= wi *Ci Where,
Wi= Relative weight of variable.
Ci= Rating for different class for each
variables.
4 .To Prepare Forest
Fire risk Zonation Map.
To run the management
plan accordingly.
Secondary ( GPS Point will be
overlayed in MODIS data and accuracy
will be tested.
MODIS historical Fire data is reclassify
based on fire risk rating & weighted
overlay to analysis the forest fire risk
zonation map.
12. Time Frame
S.N. Activities of the Research Months in Year 2023
Feb Mar Apr May June
1
Literature Review
2
Data Acquisition
3
Field work (data collection)
4
Data Analysis
5
Final report preparation
6
Report dissemination
13. Expected Outcomes
Forest fire is increasing globally due to various factors such as forest resources, topography, and weather
conditions.
A study will analyze forest fire in Province One of Nepal from 2017-2022 using MODIS data.
The study will determine the total burnt area and the active period of forest fire in the province.
The study aims to establish baseline data of forest fire information, understand the causes of forest fire
drivers, and identify hotspot fire risk zones.
The study will also create a fire risk zonation map and analyze its temporal and spatial patterns.
The findings will benefit authorities and the local/federal government in implementing an effective forest
fire management program in the province.
The final report will be completed by June 2023 and disseminated to the Ministry of Industry, Tourism
and Forest of Pradesh Province 1 and PU college of Environment and Forestry
14. Budgeting
S.N. Particulars Unit Number of Unit Rate Total Justification
1. Food and Accommodation Day*Person 20*1 1000 20000 Lodging and fooding for researcher.
2. Travel cost Trip 15*1 500 7500 Travel cost including field and local
for two persons
3. Communication Lumpsum 1000 Communication with local people and
advisor while in field.
4. Stationery Lumpsum 3000 Cost for stationery materials and
questionnaire photocopies.
5. Report Printing and binding Set/copy 4 900 3600 To print and bind final research report
6. Focus group discussion No. 8 800 6400 For tea and snack cost
7. Ground Truthing and Topo
sheet
Lumpsum 5 5000 To hire GPS and buy Top map of
entire area for field work
8. Cost for Local resource person Day*person 10*1 800 8000 Payment to LRP for ground truthing
Total cost Rs.54,500
15. References
DFRS. 2015. State of Nepal's Forests. Forest Resource Assessment (FRA) Nepal,
Department of Forest Research and Survey (DFRS). Kathmandu, Nepal.
Parajuli, A., D. B. Chand, B. Rayamajhi, R. Khanal, S. Baral, Y. Malla, and S. Poudel. 2015.
Spatial and temporal distribution of forest fires in Nepal. In XIV World Forestry Congress,
Durban, South Africa. (pp. 7 11).
Martin et al. Understanding Forest Fire Patterns and risk in Nepal Using Remote Sensing,
Geographic Information System, International Journal of wildfire. 2017; 26:276-286.
ICIMOD, 2012. Forest Fire Detection and Monitoring System in Nepal. Brochure. International
Centre for Integrated Mountain Development, Kathmandu, Nepal