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Tsunami Evacuation Guidance System

PreProcess Manual (2021.Aug2)

  • Run preProcess.py in the case folder
  • Requires createLinksAndNodes.py, getPopulation.py,setActionsAndTransitions.py
  • Run main.py in the main folder

Tsunami Simulation outputs:

  1. arrivaltime.dat.asc: This is a raster file with the arrival time.
    What is the arrival time?
    ==It is the first time when an inland grid is inundated.==

  2. inund5.dat.asc:
    This is a raster file with the maximum inundation depth at each inland grid.

Preprocess for Evacuation:

Tsunami attribute to road network

Tsunami inundation depth and the arrival time in a 10m resolution size are included as attributes in the nodes contain in a grid.

Possible problems here are:

  1. One node is exactly in the middle of two or more grids. Duplicate attribute.

Area split

Divide the computation area.

Some notes here:

  1. How to divide the areas?
  2. Based on road-connectivity (graph-theory) or with regular grid.
  3. If regular grid, what to do with interrupted graphs?

Population selection

Find the population inside the inundation area.

  • Are we using only these population? Shall we include a shadow?
  • How big of a shadow? Tsunami runup uncertainty = buffer

Notes (2021.07.20)

  1. Abe san data is on EPSG: 2446 (JGD2000 / JPR CS IV) and OSMNX downloads the graph in WGS84 EPSG 4326.
  2. The OSMNX data can be projected and exported to shp, then the CRS is EPSG 32653 - WGS84 / UTM zone 53N
  3. Kochi polygon shp is in EPSG 4612 - JGD2000
  4. The file lib_ImportOSM.py works in Terminal but not from VS Code. VS Code terminal shows another interpreter Python 3.8.2 compared to one in conda 3.7.7
  5. The file preprocess.ipynb also can generate a linksdb.csv file.

Issues

  1. Project all to same CRS (WGS84? JGD2000?)

https://epsg.org/home.html

  • ==JGD2011 / UTM zone 53N (EPSG: 6690)==
  • JGD2000 / JPR CS IV (EPSG: 2446)
  • WGS84 / UTM zone 53N (EPSG: 32653)
  • ==JGD2011 (EPSG: 6668) (Geographic 2D)==
  • JGD2000 (EPSG: 4612) (Geographic 2D)
  • WGS84 (EPSG: 4326) (Geographic 2D)

Preprocess for Population

  1. SetDatabaseBldMeshCodes.py
  2. SetpopDB.py
  3. DisaggregationLibrary.py

Kochi data

  • Area code polygons (WGS84 - EPSG:4326):

Dropbox/zDATA/PAREA_Town_2018/Shape形式/Shape形式/世界測地系/39/A3924POL.shp

to Obtain Population within inundation area

  1. Use getPopulatio.py>getPopulationArea to extract population within the 'aos' --> areaPop
  2. Use the feature areaPop and the raster inund5 to Add values to feature
  3. Select features >-99 Note: This is a bit overestimated since areas near the river or at the edge of the inundation line are also included. A shadow for evacuation.