Disaster Management Support Services

P.V.N. Rao Remote Sensing Applications Area

National Remote Sensing Centre, ISRODept. of Space, Balanagar, Hyderabad - 500 037

rao_pvn@nrsc.gov.in

National Conference on Flood Early Warning for Disaster Risk Reduction, 30-31 May 2019, Hyderabad

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India and the Natural Disasters

Drought

Cyclones

Floods

Cyclones

Earthquakes,Landslides

Drought

Earthquake

EarthquakesLandslides

Tsunami

Tsunami

Average Annual Loss• Direct: Loss of life: 4350 ; Crop area affected: 1.42 Mha; Houses damaged: 2.36 M; Direct

loss: 2 % of the GDP (Rs. 25000 Cr)• Indirect: Expenses on emergency response and relief ; diversion of developmental fund;

Indirect socio-psychological losses that can not be quantified

Disaster Risk in the country• 12% of land area (40 mha) - Flood prone• 8% of land area (along 5,500 km long

coast tract) - Cyclone prone• Over 65% of land under cultivation -

Drought prone• Around 25% land area - Earthquake

prone ( Seismic zone IV-V); Himalayan and Western Ghats region - Landslide prone

• Andaman Nicobar Islands, parts of East Coast, and Gujarat coast – Tsunami

ISRO-Disaster Management Support Programme (DMSP)

Major components of • Earth observation (EO)

satellites for thematic inputs

• Weather inputs from meteorological satellites

• Communication support through communication satellites

• A single window EO information through the Decision Support Centre (DSC) at NRSC

Conceived and implemented during the 10th Five Year Plan

• GIS based National Database for Emergency Management (NDEM) at NRSC• ISRO Bhuvan Geoportal at NRSC enables data visualisation, access & support• Disaster management support also through international charter, Sentinel Asia, UN-SPIDER

and UNESCAP, • Aerial support for high resolution terrain data and • R&D for early warning using space inputs

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Space inputs through DSC for Disaster Management

NRSC is the single delivery point forsatellite derived disaster inputsthat include

• Near real time monitoring offloods, cyclones, forest fires,landslides, earthquakes etc.

• Generation of vulnerability andhazard zonation maps

• Develop disaster early warningmethods

• Provide information for planningdisaster mitigation measures

•MHA, MoWR, MoES, MoEF&CC,State & Central Govt department

Fire

Cyc

lone

Floods in Bihar, Aug 2016

Active forest fire monitoring - 2017

Kotropi Landslide, HP- Aug 2017

Land

slid

e

Flood

Floods in Bihar - Aug 2017

02-Mar-2017 17-Aug-2017

Cyclone Vardah, Dec 2016

Aug., 2017

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Space Technology Inputs for Flood Early Warning

Data Type/Category

Satellite Data derived Parameter

Inputs for Flood Early Warning

Meteorologicaldata(Now-cast)

• Precipitation • Rainfall quantity and spatial distribution

• Surface Temperature

• Energy balance parameters, Evapotranspiration

Meteorologicaldata(Forecast)

• LULC • Input for Weather Forecast Models Mesoscale Model compatible LULC was generated by NRSC over Indian Region

• Atmospheric & Cloud Parameters

• Input for Weather Forecast Models

Terrain/Surface Characteristics

• Land Use / Land Cover

• Hydrological response as a function of in-situ land use/land cover

• Partitioning of Precipitation • Impact of changes in LULC • Surface roughness

Hydraulic parameters

• Digital Elevation Model

• Terrain slope, aspect• River channel profile• Surface/River channel flow parameterization• Spatial flood inundation simulations

Space Technology Inputs for Flood Early Warning

Data Type/ Category

Satellite Data derived Parameter

Inputs for Flood Early Warning

Soil Conditions • Surface Soil Moisture

• Antecedent soil moisture conditions• Varying catchment rainfall-runoff response• Soil moisture accounting models

River/Reservoir Water Level

• Altimeter Observations

• River water level• River discharge• Reservoir water level & Storage

Catchment/ Flood Plain Conditions

• Inundated area • Flood inundation maps• Flood frequency/hazard

• Surface water • Surface water spread• Surface water storage

• Glacial Lakes/Waterbodies

• Formation of new lakes/water bodies• Expansion of lakes/water bodies• GLOF risk

• Flood plain Structures(Embankments, Dykes, Bridges, Culverts, Weirs, …)

• Flood wave propagation• Inundation Simulation• Flood control

Near real time flood monitoring & inundation mapping nrscnrsc

During last 5 years more than 650 disaster maps covering nearly 16 states were disseminated

Flood Hazard Zonation Map of Odisha nrsc

Cyclone FANI and its impact

As seen by Sentinel-1 C-band SAROn 3 May 2019

Pre & Post with Inundation Damage caused to infrastructure due to

Cyclonic wind

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Near real-time forest fire alert system

• A joint initiative of ISRO and FSI andOperational from 2006

• 6 Observations of active forest firesdaily at 0130, 1030, 1230, 1330,1430 and 2230 hrs using MODIS andVIIRS

• Bhuvan Geo-portal provides onlineservices – Near real-time basis,MODIS alerts are sent within 30mins of satellite observation

Active forest fire alerts - 2017

• 55 % of Forest area in India are prone to Forestfires

- 10 % affected by Frequent fires

- 45 % affected by Occasional fires

• Strong seasonal and diurnal pattern of fires FireSeason – February to June

• Fires are mostly ground fires and tree mortality is low

• Loss of life or damage to property is fortunatelylimited and rarely occurs

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Seasonal Landslide Inventory Mapping (SLIM) Mobile technology for field data capture

A B29 Nov 2014 (Pre) 16 Jul 2017 (Post)

Cyclone Mora (June-July, 2017) induced landslides in Mizoram ~10,000

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Landslides in Kerala (August, 2018)

1. A total of 4700 landslides mapped in 8 districts of Kerala.2. Previously 18,000 landslides are mapped in 17 Indian states 3. Landslide early warning is active in parts of UP, Uttarakhand

and NER.

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Regional landslide early warning(LEWS - An experimental system in Bhuvan)

Landslide Susceptibility Map Daily warning for advance 3 days

02 September 2017

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Ochki Cyclone -Inputs for missing boats

Monitored Ochkicyclone during 01-12Dec, 2017 and inputswere provided to theAir force in missing boatsearch operations.

Flood Hazard Assessment of the Lake Near Gomukh on Bhagirathi River due to landslide

• Lake area was monitoredusing temporal data.

• Estimated approximatecapacity of the lake andflood discharge usingempirical methods to assessthe flood threat

• Inputs provided to UK State

Satellite based monitoringof fire on-board oil tankerMT GENESSA near KandlaPort

• DSC continuouslymonitored the situationusing multi-resolution,spectral & temporalremote sensing data fromIndian and foreignsatellites.

Agriculture Crop Residue Status Monitoring - Resourcesat-2 AWiFS Data – SWIR NIR RedAgriculture Crop Residue Status Monitoring - Resourcesat-2 AWiFS Data – SWIR NIR RedParts of Kapurthala District, Punjab

Burnt AreaLeft over stubble

Obj

ectiv

esA GIS based National Repository for entire country with a set of DecisionSupport System tools to assist in disaster management.

National Database for Emergency Management (NDEM)

Multi-scale geospatial database at •1:50,000 scale for the entire country •1: 10,000 scale for 350 multi-hazard prone districts•1:2,000 scale for Delhi, Mumbai, Kolkata, Bengaluru,

Hyderabad

DSS tools for disaster/emergency management

Information dissemination

NDEM Version 3.0 is released by Hon’ble Union Home Minister on 15 May 2017

NDEM services are extended to 718 districts across 36 States/ UTs, NDRF, SDRF and Central Departments

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Salient Features of NDEM Version 3.0 NDEM V 3.0 is equipped with comprehensive multi-scale database,decision tools and Mobile Apps.

“”

Data VisualizationMulti-Scale Geospatial Data

Services, Satellite Imagery.

Mobile ApplicationsApps for Relief Management,

Attribute Collection & Geo-tagging of emergency facility.

Resource Management, Resource allocation,

Organisation and tracking of essential commodities

Disaster Dashboard Alerts & Warning, Disaster

related Current News.

Incident Reporting Disaster event reporting through Mobile Apps, SMS, Portal.

Decision Support ToolsCustomized GUI based tools for decision making

Interaction ServicesCommunication & data exchange among users.

RFRainfall ForecastRainfall Forecast & alerts for heavy & extreme rainfall.

Data Inventory Geo-spatial data statistics, charts

Damage Statistics Submission of damage statistics

by States to MHA DS

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NDEM Stakeholders

1 Monitoring Departments MHA,NDMA,PMO,NIDM,IDS

2 Forecasting Departments IMD, CWC, INCOIS, SASE

3 Relief & Rescue Forces NDRF, SDRF

4 State Disaster Departments All 36 State/UTs DM Dept. officials

5 District Disaster Departments 718 Districts from all 36 state & UTs

MHA – Ministry of Home AffaireNDMA – National Disaster Management AuthorityPMO – Prime Minister OfficeNIDM – National Institute of Disaster ManagementIDS – Indian Defence Services

IMD – Indian Meterolocal DepartmentCWC – Central Water CommissionINCOIS - Indian National Centre for Ocean Information ServicesSASE - Snow & Avalanche Study EsttNDRF – National Disaster Response Force

NDEM V 3.0 is with comprehensive multi-scale database, decisiontools and Mobile Apps.

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NDEM Information Dissemination

DMS- VPN network

Bhuvan web portal Bhuvan web portal (bhuvan.nrsc.gov.in) NDEM web portal (ndmcc.gov.in)

NRSC website (www.nrsc.gov.in) E-mail

FTP process

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NRSC/ISRO in Sentinel Asia

• Total disaster events - 58

• Disaster emergency requests responded - 18

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Thank You

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In Conclusion

• Continuous efforts to improve DM services through space inputs

• NRSC has

• Huge repository of long term RS & Thematic data

• Will to participate in application development across themes

• We welcome collaboration on mutually interesting areas of R&D