Hetauda, Nepal, Forestry, MSc, GIS, GIS in NRM, Assignment, 3rd semester, third, semester, sem

1. Group Assignment Presentation
Presenters /Group Members
Hem Raj Awasthi
Rabina Khatiwada
Renuka Khatiwada
Samundra Khanal
Topic : Forest Fire Risk Mapping
Study Area : Kailali District
Submitted To
Jeetendra Gautam
Assistant Professor
AFU, FOF, Hetauda

2. PRESENTATION OUTLINE
Background
Objectives
Study Area
Data Collection
Data Analysis
Results
INTRODUCTION
METHODOLOGY
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3. BACKGROUND
• Repeated wildfires cause severe damage, hamper seedling
regeneration and growth, destroy non-timber forest products,
and in some cases foster invasive species (MoFSC, 2013).
• The spatial and temporal pattern of wildfire outbreaks is an
important factor in understanding the dynamics of wildfires
(Yang et al., 2007).
• Using Fire risk analysis, scientists and managers may gain a
better understanding of the location and possible
repercussions of forest fires on the economy, society, and
environment (Miller and Ager, 2012).
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4. OBJECTIVE
General Objective
The main objective of this study to understand forest fire
risk mapping using GIS and RS techniques through
ArcGIS Software.
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5. METHODOLOGY
1. Study Area
Selection
2. Selection of
fire influencing
factors and Data
Collection
3. Data Analysis
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6. Flowchart of methodology
Land Use
Land Cover
MODIS
hotspot
SRTM DEM
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7. Study area selection: Kailali District
• Kailali District, a part of
Sudurpashchim Province in
Terai plain, is one of the 77
districts of Nepal. Located
at Latitude 28° 34' 16"
northLongitude 80° 47' 42"
east.
• The district, with
Dhangadhi as its district
headquarters, covers an
area of 3,235 square
kilometres and
• The vegetation types found
in Kailali district of Nepal
include tropical and
subtropical forests,
grasslands, and wetlands Fig. 1: Map of the study area
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8. Following factors are selected based on literature review
1. Land Use Land Cover
2. Slope
3. Aspect
4. Elevation
5. Proximity to Settlement
6. Proximity to Road
Selction of fire influencing factors
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9. Table 1. Weight, value and rating assigned to
different influencing factors
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10. A. SRTM DEM, 30M data: for Slope, Aspect and Elevation Class Map
Source: https://portal.opentopography.org
Steps:
Step 1: open this link in your browser
https://portal.opentopography.org/raster?opentopoID=OTSRTM.082015.4326
.1
Selction of fire influencing factores and
data collection
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11. Step 2: Select Your Area of Interest form map below, here I select Kailali
Region
DATA COLLECTION
From here you can zoom
to your area and select
area of interest to
download as in this
figure
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12. Step 3: Enter your job title, job description and e-mail address then submit
this.
DATA COLLECTION
Fill this
form and
then
submit
after
entering
your e-
mail
address
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13. Step 4: Download requested DEM data
DATA COLLECTION
This types of
Raster job results
seen in your
browser and after
a few minutes a
download link will
be sent to you
provided e-mail
Youn download your data
from e-mail or from DEM
Results here
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14. B. Land Use Land Cover Data:
Source:http://rds.icimod.org/Home/DataDetail?metadataId=1972729
Step 1: Open above link in your browser
Step 2: download with your account if you don't have create account then
proceed to download
DATA COLLECTION
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15. C. Settlement Data:
Source: https://data.humdata.org/dataset/settlements-in-nepal
Step 1: open this link in your browser and download settlement data
DATA COLLECTION
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16. D. Road Network Data:
Source: https://data.humdata.org/dataset/nepal-road-network
Step 1: open this link in your browser and download road data
DATA COLLECTION
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17.  Add all data to ArcMap
Steps:
1. Open ArcMap and add Study area boundary from "Add Data"
2. Add SRTM DEM data, LULC map, Settlement data, Road Network data
form "Add Data"
DATAANALYSIS
Preparation of Reclassified Map of influencing factors
From this
we can add
data to
ArcMap
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18.  Add all data to ArcMap
Steps:
1. Open ArcMap and add Study area boundary
2. Add SRTM 30M DEM to ArcMap from "Add Data" in ArcMap
DATAANALYSIS
Preparation of Reclassified Map of influencing factors
Here area all
added data in
Table of
Contents
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19.  Clip added data by Study Area Boundary
For Raster Data i.e. SRTM DEM and LULC Data
1. Use "Clip" tool as in Data Management Tools in Search as in below
2. Repeat same process for clipping LULC data
DATAANALYSIS
Preparation of Reclassified Map of influencing factors
Add DEM
previously added
to ArcMap here
as a Input Raster
Study area
shapefile is
used in here
In output Raster Dataset give name
to output file with .tif extension
Then
click to
"Ok"
Type
"Clip"
here
Use this
Clip tool
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20. DATA ANALYSIS
Preparation of Reclassified Map of influencing factors
 Clip added data by Study Area Boundary
For Vector Data i.e. Settlement and Road Network
1. Use "Clip" tool as in "Geoprocessing"
2. Repeat same process for clipping Road Network data
Use this Clip tool to
Clip Vector Data
Use Settlement shapefile in input
features
Use Study area
Boundary in Clip
Features
In output feature class give name
to output file with .shp extension
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21. DATAANALYSIS
Preparation of Reclassified Map of influencing factors
 Prepare Reclassified map for all factors
For Slope, Elevation and Aspect, Clipped DEM data is used as Downloaded DEM is in
GCS ,WGS 1984 so we have to Project it to PCS UTM zone 44N
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22. DATAANALYSIS
Preparation of Reclassified Map of influencing factors
Prepare Reclassified map for all factors
For Slope, Elevation and Aspect, Clipped DEM data is used
1. For this Spatial Analyst Tool is used
2. Then Slope and Aspect are created from Spatial Analyst Tools Using Projected DEM
3. And Search for "Reclassify" Under Spatial Anlyst Tools and is used to Reclasiify Slope, Aspect and DEM
based on Table 1
4. This made reclassification of Slope, Aspect And DEM to give Relassified map of Slope, Aspect and
Elevation respectively
Set output raster name with .tif extension
After making 4 class then click to "ok"and
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23. DATA ANALYSIS
Preparation of Reclassified Map of influencing factors
 Prepare Reclassified map for all factors
For LULC Reclasisfied Map the CS of previously clipped LULC data is Changed to PCS,
UTM 44N as it is in Lambert_Conformal_Conic_Survey_Nepal and then Reclassified
based on Table 1
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24. DATAANALYSIS
Preparation of Reclassified Map of influencing factors
 Prepare Reclassified map for all factors
For Proximity to Road and Settlement data
 Clipped Road and Settlement data is in GCS then Project it to PCS, UTM
44N zone
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25. DATAANALYSIS
Preparation of Reclassified Map of influencing factors
 Prepare Reclassified map for all factors
For Proximity to Road and Settlement data
 for this first of all multiple ring buffers are created and
Select Meters
as a Unit
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26. DATAANALYSIS
Preparation of Reclassified Map of influencing factors
 Prepare Reclassified map for all factors
For Proximity to Road and Settlement data
 multiple ring buffers of Road and Settlement data are transferred to raster data
and then are reclassified raster based on Table 1
save with name
with .tif extension
Select cell size as of LULC
i.e. 30m*30m
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27. DATA ANALYSIS
 In this way Reclassified Map of all influencing factors are
created
 After this forest Fire Risk Index(FRI) is selected as based on
literature review
 Hence, the risk model will be developed with the equation
given below.
 Here, FRI = 40%LULC+ 20%S + 10%A + 10%E +
10%PR + 10%PS Equation (1)
Where, FRI is the fire risk index, LULC is the land use land
cover, S is the slope, A is the aspect, E is the elevation, PR means
the proximity to road and PS is the proximity to the settlement,
 After this Weighted Overylay is Carried out to develop fire
risk index map.
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28. DATAANALYSIS
Weighted Overylay: For this follow steps below
Step 1: search
"overlay"
Step
2:
Click
here
Step 3: Click here to
add reclassified data
Step 4: Add
reclassified
data then
click ok for
all data
Step 5: Set % influence
value to each Raster
data based on FRI
Equation so that total
sum equal to 100
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29. DATAANALYSIS
 After Completing Weighted Overlay analysis we get Fire Risk Index map
with values from 1 to 5
 where 1 is for Very low risk, 2 is for Low risk, 3 is for medium risk, 4 is for
High risk and 5 is for Very high risk zone
 Then this is validated with MODIS Active Fire Hotspot which can be
downloaded from FIRMS website (https://firms.modaps.eosdis.nasa.gov)
or this can be done with field data.
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30. Results
 Finally we FRI layer is reclassified to get 3 class i.e High Risk Class,
Medum Risk Class and Low Risk Class as below
 1 and 2 classes as Low Risk Zone, 3 class as Medium Risk Zone and 4 and 5
Classes as High Risk Zone and then clipped by Study area and result is as
below and then area of each class is calculated.
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Fire Risk Zone Area(sq.k
m.)
High Risk Zone 2514.876
Medium Risk
Zone
657.489
Low Risk Zone 108.146
Total 3280.5108

31. Fire Risk Zonation Map
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