Regional Mapping
Day 1-3. Variable Selection and GIS Processing
1. Discuss V mapping goals, targeted system
(what is vulnerable?), framework
2. Choose data layers (criteria: resolution,
timeliness, robustness & accuracy of the data)
3. Convert all data layers to grid (raster) format
with consistent resolution
4. Convert all raster layers to CSV text files
Day 4-5. Data exploration in R Statistics
1. Import all CSV into R data frames
2. Use data exploratory tools to identify the
statistical distribution of each indicator
3. Use winsorize and / or rescale techniques to
calculate the indicators on a 0-100 scale
Day 6. Create Regional Vulnerability Map
1. Calculate the sensitivity, adaptive capacity,
and exposure components and vulnerability
index in R
2. Import R vulnerability index to GIS
3. Create regional vulnerability map
4. Discuss regional vulnerability map
Day 7. Regional Map Normalize by country
1. Discuss normalizing the Regional Vulnerability
map by country methodology
2. Generate normalized country vulnerability
maps from the Regional Vulnerability Map
3. Compile Normalized Regional Vulnerability
Map
Country and Sector Mapping
Day 8. Country / Sector level Vulnerability
Mapping
1. Discuss available country data sets
2. Identify processing methods for each
country
3. Begin variable processing in GIS
Day 9. Create Country / Sector level
Vulnerability Maps
1. Complete Variable Processing in GIS
2. Import CSV files into R
3. Process Vulnerability components and
Indices in R
Day 10. Discussion of Vulnerability Mapping
Process
1. Regional and normalized country
vulnerability maps
2. Country / Sector vulnerability maps
Daily plan of activities
•
Before Nairobi
– Variable selection and collection
•
Day 1
– Introduce Vulnerability hotspot mapping
– Discuss variable selection and collection process
– Start variable synthesis & harmonization discussion
•
Day 2
– Conclude variable synthesis and harmonization
•
Day 3
– Process variables in GIS
•
Day 4 -5
– Data exploration and processing in R for regional Vulnerability map
•
Day 6
– Component creation in R (regional map)
– Mapping components in GIS
•
Day 7
– Normalize regional map by country
•
Day 8 -9
– Country and thematic vulnerability mapping
•
Day 10
– Sensitivity Analysis and Evaluation
Variable Selection and harmonization
Day 1&2
• Discuss VA mapping goals & process
• Create preliminary list of candidate variables
• Assess suitability of candidate variables
– Spatial and temporal coverage
– Thematic relevance
– Availability and access
• Synthesize and harmonize of country data sets
to create regional input layers
Synthesis and harmonizing datasets
steps:
• TBD
GIS Processing of variables
Day 3
• GIS processing of each input variable
– Processing steps vary with input layer (see next
slide)
– Each layer is processed to a 0.1deg raster
• Convert rasters to CSV tables
Data
Is data
point
Yes
Interpolate
Emp. Bayesian
RASTER
0.1deg
No
Is data
polygon
Yes
Convert to
Raster
No
Is data
Raster
Yes
Is it GCS?
No
Project Raster
& Resample
Yes
cell size
> 1km?
Yes
Resample
No
cell size
<1km?
Yes
Aggregate &
Resample
Data Processing in R Statistics
Day 4 &5
• Import CSV files into R Statistics
• Explore variables stats and define processing
methods
– Generate exploratory statistics
– Create histograms and charts
– Discussion to define R processing methods
• Process variables and create vulnerability
components
– Scale and Winsorize variables as needed
– Combine variables to create components
– Combine components to create vulnerability Index
Create Regional Vulnerability Map
Day 6
• Create components of vulnerability Index
– EXPOSURE = sum(all exposure input variables)
– SENSITIVITY = sum(all sensitivity variables)
– ADAPTIVE CAPACITY = sum( all adaptive capacity
variables)
• Calculate Vulnerability Index
– VULNERABILITY = EXPOSURE + SENSITIVITY +
ADAPTIVE CAPACITY
– Import and map components and Index in ArcGIS
Regional map normalize by country
Day 7
• Discuss the normalize by country
– Goal of the normalization process
– Mechanics of the normalization process
• Extract regional Vulnerability map using country masks
• Apply normalization function to country rasters
– (grid_value – country_min)/(country_max –
country_min)*100
– Function results in all min=0 and all max = 100
• Combine country rasters to create a normalized
regional Vulnerability map (This will create a
Vulnerability map with 0 being the least vulnerable in a
any country and 100 the most vulnerable)
Country and/or sector Vulnerability
mapping (Day 8 & 9)
•
Work on prepping each country specific data will begin on day 3 of the workshop.
– We will meet with individual countries separately to help identify processing methods for their
data.
– Countries will be encouraged to start GIS processing during week 1 and over the weekend
– During the week 1 there will be evening sessions to give direct support to those in need
•
Variable selection and GIS processing
– Discussion to select variables
– Processing in GIS according to preset methods
– Export processed files CSV files
•
Create components of vulnerability in R.
– Exploratory statistics in R
– Process variables and create components in R
– Map components in ArcGIS
Sensitivity Analysis and Evaluate
Results (Day 10)
• Sensitivity analysis
– Explore methods used in sensitivity analysis
– Perform sensitivity analysis for Regional Map
• Discussions and evaluation of results
– Discuss on vulnerability mapping results (Regional
and country maps)
– Workshop evaluation
Sensitivity Analysis methods