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Mainstreaming Climate Change in Governance

Disruptive Technologies for Public Assets Governance (DT4PAG)

This Working Version: June 1, 2021

Module 9

Using Earth Observation layers to understand climate risks

Presented by:

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Learning Objectives

  • Appreciate the range and rapidly expanding set of Earth Observation (EO) resources available for climate change screening�
  • Understand the data pipelines needed to combine relevant screening layers with public infrastructure asset and investment data�
  • Provide examples of “for free” and “for fee” screening layers relevant for your work

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Marrying information needs to available sources

Data

Satellite Sensor

Processing

Hazard/Risk Insights

Or

Simple indicators/indexes

What is the relevant �local hazard to be captured?

How is it generated and served to the end-user (you!)?

Which sensor/mission is the source?

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A road project in Viet Nam

User

Need to understand hazards on area of an infrastructure/asset!

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Hazards identified by WBG 2021

  • Extreme temperature
  • Extreme precipitation and flooding
  • Droughts/water scarcity
  • Strong winds
  • Sea level rise
  • Forest fires
  • Shift in silviculture/growing zone
  • Pests

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Hazards identified by WBG 2021

  • Extreme temperature
  • Extreme precipitation and flooding
  • Droughts/water scarcity
  • Strong winds
  • Sea level rise
  • Forest fires
  • Shift in silviculture/growing zone
  • Pests

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What data are available out there?

Source: TRMM imagery (NASA & JAXA)

Resolution: 1 x 1 km

A static layer is provided for a year

User

Need to understand flooding events on a specific area of interest

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A road project in Viet Nam

Let’s assume

  • Data we want use are from NOAA
  • Requirement of a 10 year time series of rainfall data

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Precipitation data: A Richer View

A road project in Viet Nam.

  • Source: Daily Precipitation from NOAA (Hydro-Estimator) – Satellite based rainfall data
  • Resolution: 0.045 degrees (approx. 4.5x4.5km)

Note: >16,000 precipitation “pixels” for Vietnam 331,212km2)

  • Period: 1/2010 – 12/2020�

Identification of intensive monthly rainfall

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Aggregated information of precipitation values

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Daily values over a specific timeframe over a road project location

  • No of records: 3758
  • Max Daily value: 138mm
  • No of rainstorm days (50-100mm): 164
  • No of downpour days ( <100mm): 24
  • No of heavy rain days (25-50mm): 422

Precipitation data: daily/extreme values

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Precipitation data: Yearly aggregated

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Precipitation data: Monthly Aggregated

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What data are available out there?

Source: TRMM imagery (NASA & JAXA)

Resolution: 1 x 1 km

A static layer is provided for a year

Is there any other source?

User

Need to understand flooding events on a specific area of interest

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What data are available out there?

Source: TRMM imagery (NASA & JAXA)

Resolution: 1 x 1 km

A static layer is provided for a year

Are there any other sources available?

Source: ERA5 & ERA 5 Land

Resolution: 25x25km – 10x10km

Timeframe: 1979 - 2021

Source: GPM IMERG

Resolution: 10x10km

Timeframe: 2000 - 2021

Source: Hydro-Estimator

Resolution: 4.5x4.5km

Timeframe: 2000 - 2021

User

Need to understand flooding events on a specific area of interest

Source: CHIRPS

Resolution: 5x5km

Timeframe: 1981 - 2021

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Don’t forget to ground truth!

Source: Wikipedia, Rainfall Gauge

  • Ground based measure of local rainfall�
  • Required recording “technology” for each collection point (manual or automatic)�
  • Only available for locations where ground measurement infrastructure exists

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  • Data and products presented so far are being provided for free (except from the ground truth data)

from

Free

to

Fee

  • Ad hoc: Hazard Mapping, Exposure, Vulnerability, Monitoring a prone area, (Multi-) Risk assessment, Cascading effects, Early warning, Modelling

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…of Fee-based EO services to monitor hot-spot areas

A satellite based monitoring solution

Identify patterns and changes over a defined baseline timeframe using satellite based observations e.g. Inundation Monitoring Service for water bodies

Complete end-to-end multi-sourced monitored systems

Flood monitor system for Operational awareness picture in Near-real-Time

Only Satellite data

Satellite + In situ + simulation + Crowd data

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Inundation Monitoring Service

Minimum Maximum water extent

Water Frequency

Classification of permanent and temporary inundation

Time series of Wetness and Water bodies

High Spatial Resolution (10 Meters)

Satellite data (Sentinel 1 & 2)

Service Provision:

  • Monitor bi-weekly or monthly updates
  • Compare newly derived products with the observed time series analysis

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Why do real stories matters?

In-situ telemetry station AFTER the Flash Flood event

Not only an infrastructure/ asset disruption

Crowd Sourced data for staff and volunteers

Satellite data

Hydrologic & hydraulic simulation

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Near-Real-Time Flood Monitoring System

NRT ingestion and assimilation of data:

  • Hydrometeorological parameters (In-situ)
  • Satellite data (SAR and Optical)
  • Crowdsourced data

Flood Monitoring system

Simulation/modeling,

multi-source EO &

crowdsourced data

Operational awareness picture

delivering

Higher complexity but complete picture

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Copernicus Emergency Management Service

  1. EMSR384: Flood in Vietnam (2019-08-30)
  2. EMSR392 Flood in Can Tho (2019-09-30 & 2019-10-01)
  3. EMSR399 Flood in Can Tho (2019-10-27)
  4. EMSR402 Tropical Cyclone Matmo (2019-10-31)
  5. EMSR405 Tropical Cyclone Nakri (2019-11-10)
  6. EMSR464: Tropical cyclone Noul in Central Vietnam (2020-09-18)
  7. EMSR450: Flood in Vietnam (2020-08-02)
  8. EMSR469 Wind Storm in Central Vietnam (2020-10-07)
  9. EMSR472: Floods in Central Vietnam (2020-10-12 & 13)

Risk And recovery Activations

  1. EMSR475: Tropical cyclone MOLAVE in Vietnam (2020-10-28)
  2. EMSR472: Floods in Vietnam (2020-10-12)
  3. EMSR469: Wind Storm in Vietnam (2020-10-07)
  4. EMSR464: Tropical cyclone Noul in Vietnam (2020-09-18)
  5. EMSR450: Flood in Vietnam (2020-08-02)
  6. EMSR405: Tropical Cyclone Nakri in Vietnam (2019-11-10)
  7. EMSR402: Tropical Cyclone Matmo in Vietnam (2019-10-31)
  8. EMSR399: Flood in Can Tho, Vietnam (2019-10-27)
  9. EMSR392: Flood in Can Tho, Vietnam (2019-09-30)
  10. EMSR384: Flood in Vietnam (2019-08-30)

Rapid Mapping Activations

Global initiatives providing freely EO-based products

High (10-20 m) to

Very high (1-5 m) resolution

Outputs: Mapping service

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Flooded Areas

Free hazard layers for Vietnam

Global initiatives providing freely EO-based products

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Questions

  • What are you priorities for environmental context layers and specific indices?

  • Do you feel it is clear who you can access and customize these for end-user interfaces like ur-scape?�
  • Can you provide a specific use-case in term of spatial and temporal granularity you are looking for?