geoinfo in dm.ppt
TRANSCRIPT
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Geo informatics
Dr. Mukta Girdhar
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Geo informatics includes:
Remote Sensing(RS)Geographic Information System (GIS)
Global Positioning System (GPS)
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REMOTE SENSINGEarth observation from space can provide information to meet
meteorological needs, Resources Mapping, monitoring requirements and
sustainable development
-INSAT Satellite
-IRS Satellite
RemoteSensing is not alien to human beings. They make use of it in
their daily life. The three essential components of a remote sensing
system are inbuilt in every human being.
Non contact Sensors: Eye, ear and nose
Platform: Human body
Data acquisition and processing: Brain
Eyes respond to the electromagnetic Radiation (EMR) in the visible
spectrum of 0.4 to 0.7 and enable three dimensional visualization of
our surroundings.
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Uses of Remote Sensing in Disaster Management
Identify hazard and risk modeling of tsunamis,
hurricanes, earthquakes and disease pandemics etc.
Models of extreme oceanic, land and atmospheric
phenomena as well as pandemic outbreaks
Remote sensing based early warning systems for natural
disasters such as tsunamis, hurricanes, earthquakes,
floods, etc, when other network fails.
Satellite and/or airborne observations of extreme natural
events in support of disaster response
Damage and loss assessment using satellites and airborne
sensors for different disasters.
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Geographic Information System (GIS)
GIS is a system of hardware and software used for
storage, retrieval, mapping, and analysis of geographicdata. Practitioners also regard the total GIS as
including the operating personnel and the data that go
into the system. Spatial features are stored in a
coordinate system (latitude/longitude, state plane, UTM,
etc.), which references a particular place on the earth.
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GIS comes into the pictureWe know that any planning and managementprocess requires data as a support to takedecision. If the data is on paper or even in
computers in tabular format, it cant be asuseful as data represented on mapsbecausethis can enable us to create various thematicanalyses ad hoc.
It is said thatA Picture is worth a Thousand Words
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The GPS (Global Positioning System) is a "constellation" of24 well-spaced satellites that orbit the Earth and make itpossible for people with ground receivers to pinpoint theirgeographic location. The location accuracy is anywhere from100 to 10 meters for most equipment.
This is the only system today able to show your exactposition on the earth any where, in any weather
Where I am ?
How do I get to my destination?
Global Positioning System (GPS)Global Positioning System (GPS)
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Global Positioning System
Your location is:
17o23.323 N
78o32.162 E
532.456 m
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Disaster Management Cycle
Identification & Planning
Mitigation
Preparedness
Response
Recovery
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GIS in Disaster Relief / management
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Disaster Planning
Predicting The risk of event
Impact of event:
- Human Life- Property
- Environment
Response requirement study / Preparedness Alternate / Best route for sending relief
Evacuation routes
Protection needs Identifying affected vegetation in wildfire
Reinforcement of structures in case of earthquakes
Evacuation center development
( Earthquake, Landslides, Floods, Manmade Disaster.....)
http://e/Preparedness.avihttp://e/Preparedness.avi -
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GIS in Disaster Relief / management
Modeling & simulation (using GIS) Visualize the scope of disaster
High risk prone areas
Lives & property at higher risk
Response resources
Modeling Disaster assistance center
Number of people affected Availability of shelter facilities
Essential & affective preparedness
Communication Tools
Training Tools
Records management Post Disaster claims
Status of repairs
Staffing & organizing
Report generation
Visualization
Display damaged & unsafe structures
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Service Areas
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Fire Management System, Delhi
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Buildup area of Delhi.
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C.P. Area
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Fire stations
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Hospitals
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Police stations
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23Road Network
Major Roads
Minor roads
Bye lanes
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Water tanks
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Open/Greenareas
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All layers merged
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Focus Area:- C.P.
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3d Visualisations
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Development of the model (Fire support system)
The model is able to analyse the following queries.
1. Display information of various fire safety parameters of the affected
building.
2. Calculating point to point distances.
3. Analysing the nearest feature of interest with respect to the affectedarea.
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Database development:To develop a database on:-1. High rise buildings (initially for C.P.)
2. Fire stations.
3. Nearby hospitals.
4. Water tanks
5. Police stations.
6. Road network.7. Park/Open areas.(For rehabilitation)
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(1.) Instant display of the information
Info tool
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Display of the attributeBy placing the cursor on the affected building
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Instant display of all theInformation attached
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Plan of the constructionof the affected building
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2. Analysing the nearest
feature of interest
with respect to the affected area.
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Advantages of the system Instant display of all the fire safety parameters of the
concerned building.
Shortest route to the scene of incident.
Nearest fire station, hospitals, water tank etc.
Efficient management of resources available at thenearest fire stations.
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Preparation of a GIS based
inventory of hospitals
capable of handling of masscasualty in any eventuality
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The study undertaken included 62 hospitals with a total bed capacity of 13,739
beds with a mean of 193 beds and median of 60.5 to make an database on GIS
problem. All the CATS units were geocoded along with their base hospital units
and location and analysis was done .
The various buffers generated at different pre-determined distances were
analysed using buffers around the venue with respect to the CATS units and
hospitals facilities reflected the spatial inequality and the existing facilities where
affected can be mobilized effectively after Incident on site triage. The localization
of CATS at strategic locations can effectively minimize the response timings. Also
it is prudent to cluster the CATS units in a standard operating
procedure which is dynamic and evidence based rather than on basis of
assumptions and primary reflections of CATS team. The effectiveness of poolingin hospital ambulance units (dispatch units ) and synchronization with CATS can
yield very good results.
Defined input layers and attributes: Hospitals
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p y p
1.
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Defined input layers and attributes:
CATS Units
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Buffer at 500 meters
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Buffer zone at one km around the
venue
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List of hospitals in 2 Km buffer zone
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Buffer zone at Five kms around thevenue- List of Hospitals
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Spatial Reach; CATS at 3 km buffer
zone
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Spatial Reach; CATS at 3 km buffer
zone
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Buffer at 5 Km with Hosp & CATS
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The creation of data base of hospitals and contingent facilities need to be not only
geocoded but up-linked with web and updated periodically with hospital information
system to enable real time data analysis and retrieval. A possible GPS link up of CATS And
other ambulances in cluster if can be integrated together than a coordinated and effective
response mechanism would be a reality.
The buffer at one kilometer included only three hospitals and five CATS units. While
a total of 15 hospitals were found to be located in the buffer zone at two kilometreswith a bed capacity of 5955 and 9 hospitals having dedicated burns units with a mean
ambulance availability of 2.8. Although seven CATS units were located in the zone but
they were found clustered. The evidence of spatial modeling and decision making
was obvious here as the analysis showed that if CATS unit is stationed at Khel gaon
Marg , it could cater to DLTA, JLN stadia and Sirifort games complex.
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In the buffer zone at three kilometers, there were 33 hospitals with dedicated burns facility
in 19 with a mean of 301 beds and 16 CATS units . In addition to 2 km buffer segments
18 additional hospitals with a bed strength of 3944 were included in the zone.Three km buffer showed optimum response capabilities with few spatial hurdles which
could be rectified by changing the locations of the CATS units.
The spatial accessibility in this zone is better at Jawaharlal Nehru stadium
and RK khanna stadium with AIIMS & PSRI within reach respectively which
are both multi speciality hospitals capable of handling mass casualty with adequate care.
In addition to zone 3km , 5km buffer zone provides additional bed capacity of 1926
beds with mean of 143 and median of 70 with the coverage of three major multispeciality trauma and burns center. Even at 5km range the major response center
Of Guru Teg Bahadur Hospital remains elusive to Major Common Wealth Games site.
The central question of the study has been to address the spatial inequity in hospital
resources and response capability in the event of mass casualty. Poor locational decisions
are one of the important resons for poor access to health services. The locations of healthinfrastructure becomes crucial in times mass casulty, as the first responders have the
limitation of administering first aid in terms of standard guidelines.
Linkages to Mass Casualty Management
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Linkages to Mass Casualty Management
These events are complex, difficult to manage and require the involvement of many
agencies, many of which seldom work together outside a particular emergency. Preparingfor such events requires uncommon levels of collaboration, preparedness, and timely ability
to create a common vision of the what,where, and how that will guide effective
response. Of all the emergency events that remain most illusive to the first responder
community, bioterrorism is likely one of the most difficult to prepare for, protect against,
and respond to effectively.The agencies involved includes:
Hospital emergency departmentLaw enforcement department
Transportation services
Fire services
Medical and surgical facilities
Pharmacies
Public works departments
Public health agencies
Central health agencies
State public health agencies
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The major hurdles as recognised in the planning of a mass casualty response
are the overwhelming proportions, no/minimal facilities for triage, poor
emergency support network and a perennial resources crunch. Inevitably theability to manage such a situation is dependent on the existing infrastructure and
existing trauma and critical care systems in the affected area.
Similarly well tested emergency preparedness and response plans are necessary.
To reduce mortality and morbidity in the first hours and days following a disaster,local response capability and infrastructure management must be strengthened to
ensure the best outcomes for those severely injured in an event. And the
replicability of SDI and GIS platform as also the assistance for timely
interventions increases manifolds if above scientific platforms are used. As it can
provide assistance in mobilizing optimal resources, routing patients to the most
nearest and capable facility and provide a logical framework for Tier I and Tier IIworkers and law enforcement agencies.
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Bhiwani District- Haryana
Dengue fever (DF)
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Dengue fever (DF)
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The data collected through personal interviews from both dengueaffected samples
(DAS) and unaffected samples (UAS). Findings indicated that out of sixty
socioeconomic and socio-cultural variables, only sixteen were co-related significantly
with Dengue. These sixteen variables were used in the stepwise regression model;
only eight variables, namely, frequency of days of cleaning of water storage
containers, housing pattern, use of evaporation cooler, frequency of cleaning of
evaporation cooler, protection of water storage containers, mosquito protection
measures, frequency of water supply and waste disposal made a Dengue risk levels
associated with social and cultural parameters in Jalore significant contribution to
the incidences of DF/DHF/DSS. The geographical information system (GIS) has
been used to link the spatial and significant socio-cultural indicators with the
disease data. Using factorial discriminate analysis and spatial modeling with these
eight socio-cultural indicators, five classes of risk categories ranging from very
low to very high were identified based on the analysis of socio -cultural practices
adopted by DAS and UAS and from the application of GIS. Below figure shows the
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Malaria Mapping in Belize
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Malaria Mapping in Belize
This image taken over San Pedro, Belize, by a Landsat
satellite, shows the distribution of malaria cases in the
area. The yellow and orange dots show where most
outbreaks occurred per household. The vegetation in thesurrounding countryside is colored red in this image,
while human settlements and roads are light blue. (Image
courtesy Uniformed Health Services)
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Web - GIS applications inDisaster Management :
application to the Tsunami
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Next few slides show the creation of
base maps and showing different
features in different layers
A base map showing
th t l i
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the coastal region.Villages shown in Red are
the most affected
ones because they are about
5 km away from the coast.
Villages shown in Blue
can provide help to the affected
region as they lie within
5 to 10 km belt from the coast.
Map-Querying, ad-hoc, on-line
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Important information of the
map objects can be
instantly accessed by placing
the cursor on the objects.
Categorizing Villages
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Possible Shelters
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Hospitals and medical facilities
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Hospitals and medical facilities
Point-and-Clickshows the medical
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shows the medical
balance.
Before the event,
only the resources
would be shown. Afterthe event we would
update the Patients
field. More points
would be added as and
when emergencyclinics and First Aid
posts are set up.
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The 2x2 km grid
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cells give an idea of
the geographical
distribution ofPopulation. (Gives
an idea of the
potential number of
refugees.)(map created using the GC-GeoMiner module; size of grid is upto the user)
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Over-served and under-
served areas. (In this case for
Medical centres - we need
some more emergency
clinics.) The same analysis
could be done for Food
godowns and distribution
centres, etc.
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A 1 km Buffer Zone
around Creeks / riverbeds; locations
requiring study
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59 Villages are found
to be in the 1 km x 12
km buffer up the river
beds.
Hosting the maps on the Internet
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Hosting the maps on the Internet
A Web GIS
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Need ofWeb GIS in Disaster management Accessibility and dissemination of timely and accurate
information Centralized Control: A web GIS can disseminate informatio
from a control room which can reach everyone. Authenticit
and accuracy are guaranteed.
Only one map needs to be maintained at the server.
Changes made in the map are reflected everywhere
No need for a GIS Software with the users
No need for training the users in GIS
Instant Feedback and updation: The current status can be
updated from moment to momentWeb-based GIS play a vital role in this aspect providing timely and right information
to the concerned people and the emergency managers for taking necessary actions
Maps on a web browser ona Palmtop
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a Palmtop
These pictures show a simulated GeoConcept
Pocket GIS working on the Compaq palmtop. We are,
however, recommending that the palmtop be used with
only a browser.
The base-map. Each button is labelled.Clicking on it will bring up a specific map
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Clicking on it will bring up a specific map.
Result of pressing theMedical Facility button
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Medical Facility button
Service Area of a Hospital
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We spelled out the name of a
village; the map was re-centred on
that village; we clicked on it and the
attribute-data appears below.
Quick Navigation on themap
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map
Various positions on the map can
be saved which can be accessed
with a single mouse click
Viewing a map atdifferent zoom levels : More
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different zoom levels : Morefeatures may appear as you zoom
in.
Possible Shelters
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The High
Schools, Middle
Schools etc. andother Pucca
constructions can
be identified.
They can be
potential shelters.
Villages which are far fromthe coast might still beaffected because they are
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affected because they arenear the rivers.A 1-Km buffer on each sideof the river bed.
Showing the Population density byusing a Grid can be useful in
identifying what are likely to be the
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worst-affected areas
These areas are
densely populated and
are very near the
coastline
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The slides shown are only a few examples of using GIS
especially WEB-GIS - in Disaster Management with
special reference to Cyclones and the Tsunami. A similarcase could be made for GIS-aided management of other
natural disasters, such as Earthquakes and monsoon
flooding.
Effective use of GIS in advance of any actual event
enables one to plan the pre-deployment of things in the
right place telecom equipment, shelters, medicine,
jeeps; also to micro-manage information in the post-
disaster period - identify the most vulnerable locations;
direct traffic onto the routes that are open, etc.; and finally
to provide monitoring and evaluation support in the long-
term for rehabilitation.
Objective:
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Develop a Geospatial system to
meet the operational requirements of
different users involved in relief &
rescue, flood management and long
term flood control measures.
Functionalities: Access & update the spatial database;
Analysis of flood event;
Generate statistics and outputs for
presentation of flood information;
Facilitating Simple & complex queries.
Outputs:
Overview/regional inundation map;
Relief support inundation map;
Breach & embankment location map;
Seasonal flood summary;
Brief flood report with Hydrologic status.
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Base map
Land use map
Settlements
Road & Rail network
Flood inundation map
. ..
Damage information system
Main window with Navigation and Identify Tools
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Main window with Navigation and Identify Tools
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g y
Secured Logging for Data Management
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Secured Logging for Data Management
Authorized Data Viewing, Append and Update facility
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g, pp p y
Overview inundation Map
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Regional inundation Map
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Regional inundation Map
Relief support inundation map
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Targeting and Reaching out..
PUNJAB & HARYANA FLOODS 2010
http://timesofindia.indiatimes.com/Bihar_floods_Delay_in_relief_triggers_food_riots/articleshow/3431348.cms -
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PUNJAB & HARYANA FLOODS - 2010
Heavy torrential rain during the first week of July have Lashed
many parts of Haryana region, flooding lowlying areas . Ambala
and Kurukshetra districts were worst effected by floods. Most
rivers including seasonal Tangri, Ghaggar and Beng were reportedto be in spate. Several villages of Kurukshetra and Ambala districts
have been marooned in deep water due to a 100-feet breach in
Sutiej - Yamuna Link (SYL) canal at Gulabgarh village.
The Ghaggar innundated more villages due to its breaches at
several places .
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2005
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Flooding in Mozambique
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Flooding in Mozambique
(2000)
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Flooding in Mozambique
This pair of images from Landsat 7 shows the incredible
amount of flooding that occurred in March of 2000 in
Mozambique. A month of rains and two cyclones caused
the Limpopo River to swell to 80 km wide in places.Several hundred people were killed, and over a million
were forced from their homes. (Image courtesy of NASA)
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Components of Delhi Project
http://snellaa.com/images/2f1.gifhttp://images.google.co.in/imgres?imgurl=http://www.cabsa.co.za/Prisma/j0303484.gif&imgrefurl=http://www.cabsa.co.za/newsite/DisplayPage.asp%3FId%3D112&usg=___7Aj5iC6R4hrlmzevuHP7WT8GUc=&h=83&w=90&sz=16&hl=en&start=84&tbnid=8x8dIqIZz1GCdM:&tbnh=72&tbnw=78&prev=/images%3Fq%3Dproject%2BPlanning%2B%2526%2BMobilisation%26imgtype%3Dclipart%26as_st%3Dy%26gbv%3D2%26ndsp%3D20%26hl%3Den%26sa%3DN%26start%3D80http://images.google.co.in/imgres?imgurl=http://www.pcgiconsulting.bc.ca/web/images/gallery/puzzle1.gif&imgrefurl=http://www.pcgiconsulting.bc.ca/web/DesktopDefault.aspx%3Ftabindex%3D0%26tabid%3D262&usg=__D-C-5S-FBok6rg5bty8SREfgIqc=&h=88&w=143&sz=4&hl=en&start=128&tbnid=aXKkh3uT93tAHM:&tbnh=58&tbnw=94&prev=/images%3Fq%3DRequirement%2BAnalysis%26imgtype%3Dclipart%26as_st%3Dy%26gbv%3D2%26ndsp%3D20%26hl%3Den%26sa%3DN%26start%3D120http://sheqconsulting.co.za/images/kk.jpghttp://images.google.co.in/imgres?imgurl=http://w10.naukri.com/jg/atrenta/gifs/animcomp.gif&imgrefurl=http://www.naukrionline.com/jg/atrenta/career.htm&usg=__xzgjpcErc_y381JTC6vKCrGw5pg=&h=68&w=112&sz=7&hl=en&start=211&tbnid=gE1yaWRpApeV2M:&tbnh=52&tbnw=86&prev=/images%3Fq%3DDesign%2B%2526%2BPrototyping%26imgtype%3Dclipart%26as_st%3Dy%26gbv%3D2%26ndsp%3D20%26hl%3Den%26sa%3DN%26start%3D200http://crisys.cs.umn.edu/images/test-header.gifhttp://images.google.co.in/imgres?imgurl=http://www.emprower.com/images/Teamwork2.jpg&imgrefurl=http://www.emprower.com/solutions.html&usg=__RS4SMl1gkagzsRF7VVtwP-2xp7A=&h=300&w=300&sz=233&hl=en&start=37&tbnid=0RhAKUFHfAWtcM:&tbnh=116&tbnw=116&prev=/images%3Fq%3Dimplementation%26imgtype%3Dclipart%26as_st%3Dy%26gbv%3D2%26ndsp%3D20%26hl%3Den%26sa%3DN%26start%3D20http://images.google.co.in/imgres?imgurl=http://www.mhtc.net/~mcguirer/webquest/images/puzzled.gif&imgrefurl=http://www.mhtc.net/~mcguirer/webquest/credits.htm&usg=__b1crGdffdrLj-z55Ew2Y_zGbE98=&h=429&w=466&sz=9&hl=en&start=7&tbnid=8MdZAn25WVyMIM:&tbnh=118&tbnw=128&prev=/images%3Fq%3DEvaluation%26imgtype%3Dclipart%26as_st%3Dy%26gbv%3D2%26hl%3Denhttp://images.google.co.in/imgres?imgurl=http://www.watchworx.co.uk/images/webGraphics/frontImages/125Deployments/AutoDep-3.jpg&imgrefurl=http://www.watchworx.co.uk/pages/access/deploy.html&usg=__WgcSWqhzqhkJQh3ZHM1WDpkv-aM=&h=89&w=125&sz=21&hl=en&start=70&tbnid=i9NtYo4btxLeuM:&tbnh=64&tbnw=90&prev=/images%3Fq%3DDeployment%26imgtype%3Dclipart%26as_st%3Dy%26gbv%3D2%26ndsp%3D20%26hl%3Den%26sa%3DN%26start%3D60 -
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Delhi
SDI
PROJECT
COMPONENT A:
GPS Control, Aero Triangulation
/Digital Elevation
Model/Orthophoto
COMPONENT C :
PRIMARY DATA CAPTURE
3D Mapping, Property Survey, Utility
Survey, UIS & LIS
COMPONENT B :
SYSTEM DESIGN/
INTEGRATION
Database schema,
10 Monitoring Centers,
2 Control Centers, DSSDI
Geoportal, Training
COMPONENT D :
3D GIS
3D Topology,
Texturing, 3D
Visualisation, GIS
Application
Components of Delhi Project
Application Developmentfor Line Departments
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Metadata Creation
Property Survey
Attribute Data Attachment
Survey
Requirement analysis
Database Design Document
Utility SurveyPhotogrammetric
Survey
Spatial Data Generation - Categories
Field Validation
Application Development
for Line Departments
Cadastre
Hydrography
HypsographyImages
DEM
Framework
Boundary
Building
Transportation
Utility
Land Use
Census of India
Commonwealth Games Delhi 2010
Delhi Development Authority
Delhi Disaster Management Authority
Delhi Fire Services
Delhi Integrated Multi-Modal Transit System Limited
Delhi Jal Board
Delhi Metro Rail Corporation Ltd.
Delhi Police
Delhi Pollution Control Committee
Delhi State Industry & Infrastructure Dev. Corp. Ltd.
Delhi Tourism & Transport Dev Corporation Ltd.
Delhi Transco Limited
Delhi Transport Corporation
Department of Forests
Department of Health & Family Welfare
Department of Irrigation & Flood Control
Department of Trade and Taxes
Directorate of Education
Excise Entertainment and Luxury Tax Department
Indraprastha Gas Limited Mahanagar Telephone Nigam Ltd
Municipal Corporation of Delhi
New Delhi Municipal Council
North Delhi Power Limited
Office of the Chief Electoral Officer, Delhi
Office of the Labour Commissioner
Public Works Department
Revenue Department
Yamuna & Rajdhani BSES Power Limited
Line
Depts.
DSSDI - Generic Applications Details for Line
Departments of GNCTD
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Departments of GNCTDLine Department
Login
Map
Navigation
Query Analysis Report
Query Builder
Department
Specific Query
HelpAttribute
Update
Proximity
Analysis
Spatial
Analysis
Network
Analysis
Map
Classification
Address
Locator
Planning &
Monitoring
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DESERTIFICATION STATUS MAP
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4/4/2013 112
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4/4/2013 113
ORISSA CYCLONE, 1999
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ORISSA CYCLONE, 1999
A super-cyclone hit Orissa on 29.10.99
12 Districts Affected
About 10,000 killed
12.6 million people affected
1.2 million houses damaged
3.55 lakh cattle lost
SUPER CYCLONEOVER ORISSA
28 Oct-3gmt
28 Oct-6gmt
28 Oct-9gmt
29 Oct-3gmt
29 Oct-6gmt
29 Oct-9gmt
30 Oct-3gmt
30 Oct-6gmt
30 Oct-9gmt
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INSAT IMAGESSHOWING THECYCLONE MOVEMENTDURING 28 OCT TO30 OCT, 1999
...AND THE AFTERMATHNEARLY 3.75 LAKH Ha. INUNDATED
ROAD, POWER AND COMMUNICATIONNETWORKS SEVERELY AFFECTED IN 10
COASTAL DISTRICTS
OVER ORISSACOAST
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POST-CYCLONE SATELLITE DATA02 Nov,1999 04 Nov,1999 05 Nov,1999
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11708 Nov,1999 11 Nov,1999 13 Nov,1999
Radarsat Radarsat IRS-1D WiFS
IRS-1D WiFS IRS-1D WiFS IRS-1C WiFS
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Communication
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Earth Observation Satellite Communication
Disaster Education Health
Met DataUtilization
DisasterWarning
Flood mapDroughtBulletin
Local Nodes
Relief Agencies
Hurricane Katrina (August 2005)
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Hurricane Katrina (August 2005)
Began as tropical depression in central Bahamas
afternoon of 23 August 2005. Made landfall along SEcoast of Florida evening of 25th as Category 1 hurricane.
Regained hurricane status after emerging into Gulf of
Mexico, becoming Category 1 storm morning of 26th of
August. Conditions in Gulf were favorable for Katrinato intensify.
Evening of 26th, Katrina was Category 2 storm and
continued to move slowly W-SW in southeastern Gulf of
Mexico.
Morning of 27th, Katrina became Category 3 storm with
maximum sustained winds of 100 knots (115 mph).
Hurricane Katrina from
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TRMM (#1)
Hurricane Katrina from TRMM (#1)
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Hurricane Katrina from TRMM (#1)
This first image was taken at 03:24 UTC 28 August
2005 (11:24 pm EDT 27 August) just as Katrina wasabout to become a Category 4 hurricane in the centralGulf of Mexico. The image reveals the horizontaldistribution of rain intensity within Katrina as obtainedfrom TRMM's sensors. Rain rates in the central portionof the swath are from TRMM Precipitation Radar (PR).PR is able to provide fine resolution rainfall data anddetails on the storm's vertical structure. Rain rates in theouter swath are from the TRMM Microwave Imager
(TMI). The rain rates are overlaid on infrared (IR) datafrom the TRMM Visible Infrared Scanner (VIRS).TRMM reveals that Katrina has a closed eye surrounded
by concentric rings of heavy rain (red areas) that areassociated with outer rain bands.
Hurricane Katrina from
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TRMM (#2)
Hurricane Katrina from TRMM (#2)
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Hurricane Katrina from TRMM (#2)
The second image was taken at the same time as the
first image and shows a 3D perspective of Katrina witha cut-away view through the eye of the storm. Thevertical height is determined by the height of
precipitation-sized particles as measured by theTRMM PR. Two isolated tall towers (in red) arevisible: one in an outer rain band and the other in thenortheastern part of the eyewall. This area of deepconvection in the eyewall is associated with the area ofintense rainfall in the eyewall. The height of the
eyewall tower is 16 km. Towers this tall near the coreare often an indication of intensification as was truewith Katrina, which became a Category 4 storm soonafter this image was taken.
Hurricane Katrina from
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TRMM (#3)
Hurricane Katrina from TRMM (#3)
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u ca e a a o (#3)
The final image was taken at 02:29 UTC August 29th
(9:29 pm CDT August 28). The center of Katrina doesnot fall within the PR swath in this image. However,the large eye of the storm is clearly visible using TMI
by the large ring of moderate intensity rain, (green
annulus). The first outer rain bands with embeddedareas of heavy rain (red areas) are already impactingthe coast in southeastern Louisiana. At the time ofthis image, Katrina was at Category 5 intensity withmaximum sustained winds measured at 140 knots
(161 mph) by NHC. Katrina initially made landfall at6:10 am CDT along the Mississippi delta as a strongCategory 4 storm. (TRMM Imagery by
NASA/JAXA)
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KOSI FLOODS BIHAR
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Significant portion of theKosi (75%) is flowingThrough embankment
Around 25% in the mainchannel
The Current flow of the riverafter the embankmentbreach is following the oldcourse of 1926
-2008
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Image credit: Joint Typhoon WarningCenter. Storm summary: Rob Gutro,Goddard Space Flight Center.
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CHANGING NATURE OF FLOODPLAINS
Floodplains are neither static nor stable.
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Composed of unconsolidated sediments, they are rapidly
eroded during floods and
High flows of water, or they may be the site on which new
layers of mud, sand, and silt are deposited.
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IRS-1D LISS-III + PAN merged data of 08-Sep-03
A Close View of Embankment Breaches in part of Puri District
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g p
These LISS-III, PAN merged images show the breaches in embankments of Daya
River, a distributary of Mahanadi, near Pipli area in Puri district. Affected roads can
also be seen in the image.
Affected Road
Breach
Orissa Floods - 2007
Floods hit Orissa due to heavy rains in Orissa state during first week of July
2007 due to depression in Bay of Bengal.
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IRS-P6 AWiFS Image of 24-Mar-06 IRS-P6 AWiFS Image of 08-July-07
Flood Inundation
PRE-FLOOD DURING FLOOD
Rivers Subarnarekha and Baitarini were in spate. Subarnarekha had
crossed its previous HFL on 7th July 07
The worst affected districts were Balasore, Bhadrak, Jajpur, Keonjhar and
Mayurbanj
Bhadrak
Jajpur
Kendrapara
Balasore
Keonjhar
Flood Recedence in part of Khammam District, AP State
Flood Image Flood RecedenceFlood Image
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Flood
Inundation
IRS-P6 LISS-III Image of 08-Jul-06
Flood Image Flood Recedence
IRS-P6 AWiFS Image of 07-Jul-06
Flood Image
Flood Recession
Flood Inundation as on 08-Jul-06
River course
Flood
Inundation
Barmer Floods-2006
Village boundaries overlaid on IRS LISS 3 data
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Village boundaries overlaid on IRS LISS 3 data
Water spread as on 5th September and 15th September, 2006Kawas Uttarlai Malwa
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14.83 sq km17.25 sq km
19.53 sq km19.64 sq km
3.95 sq k4.66 sq km
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142
17.01.9817.05.98 08.10.98
False color composites
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143
Vegetation Index - NDVI
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Synoptic & Close View
of
Rockslide Around
Ghingran Uttaranchal
Recent Landslides in Uttarakhand
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Year Place Death
1998,
12-18th August
Malpa, Pithoragarh
district
210
1998,
12th August
Okhimath, Rudraprayag
district
107
2002,
10 -11th August
Ghansyali Tehsil, Tehri-
Garhwal
29
2003,Sept-Oct
Uttarakashi
2004,
1-6th July
Chamoli District 25
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Landslide Lake in Tibet Floods India
R hl ft
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Roughly a year after
forming behind a landslide
dam, the lake on thePareechu River in Tibet
began to drain on June 26,
2005. Water and mud gushed
down the Pareechu River into
the Sutlej, the major river thatflows through Indias
Himachal Pradesh state.
Thousands were evacuated
from the banks of the Sutlej,
and though several bridgesand buildings were damaged
or destroyed, no injuries were
reported in the flood,
according to news reports.
Uttarkashi Landslide
Already predicted in 2002
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IRS-LISS-III images taken before and after Varunavat landslide in 2003
Varunavat Landslide, Uttarkashi IRS-PAN image
Landslides in the Alkananda valley
Sliding started in Sept
2003
Continues till date
Property loss over 300crores
No lives lost
Questions ???
Is it related to Earthquakein 1991, 1999 and in recenttimes
A case study from Sikkim Himalayas
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SEWAGESC G
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161
MUMBAI CITY
SEWAGEDISCHARGE IN
MAHIM BAY
DISCHARGE
IRS-1D LISS-III IMAGE
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Korangi Mangrove forest near Kakinada
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IRS1D LISS-III AND PAN MERGED IMAGE
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A massive fire broke out at the Indian Oil Corporation depot in SitapuraIndustrial Area of Jaipur on Thursday night. This led to an
uncontrollable fire which engulfed 12 huge tanks.Nearly one lakhkilolitres of fuel, worth Rs 500 crore just burn out. The flames, hadthrown up huge columns of thick, black smoke which blocked sunlight.Officials and firefighters finally decided to wait for the burning fuel toget consumed and for the fire to extinguish by itself, as there seemed tobe no other alternative.An area of 5 km radius had been marked asdanger zone.
29/10/2009
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Map showing location of IOC depot at Jaipur and its adjoining areas
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Area where Fire smoke of IOC depot observed
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Satellite image overlay on land records map
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Forestry
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MODIS-detected real-time fire hot-spot image
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USEM
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USEM
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USEM
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Tsunami Damage
(December 2004)
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(December 2004)
Tsunami Damage
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177
The island of Phuket on the Indian Ocean coast ofThailand is a major tourist destination and was also in the
path of the tsunami that washed ashore on December 26,2004, resulting in a heavy loss of life. These simulatednatural color ASTER images show a 27 kilometer (17-mile) long stretch of coast north of the Phuket airport onDecember 31 (right), along with an image acquired twoyears earlier (left). The changes along the coast areobvious where the vegetation has been stripped away.
These images are being used to create damage assessmentmaps for the U.S. Agency for International Development(USAID) Office of Foreign Disaster Assistance. Imagecredit: NASA/JPL.
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USEM
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Before & After Disasters
Fukushima Daiichi Nuclear Plant
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North of SendaiThis area, which includes Minamisanriku and the
Onagawa nuclear plant, was closest to the epicenter of thequake. In Minamisanriku alone, more than 10,000 people
i i
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are missing
One of the hardest hit, this port town was completely devastated.
Self- Defence Force rescued 32 people around the quay near the
port. More than 4,400 people are sheltered in the town
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Sendai's city center, about 7 miles inland, remainedlargely intact after the quake, but there was massivedamage along the coast. Much of the airport, which is
less than a mile from the water, was also destroyed.
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In this town, search for survivors turned into
a search for bodies. Among the dead are
mostly elderly people. The Natori river heregrew from a sedate flow to a raging wall of
destruction
Japans eastern seashore that faced the fury ofFridays tsunami was left severely damaged.
Settlements were destroyed and farms were washed
away.
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The Arahama area of Sendai witness major havoc. Houses were flattened, green
cover destroyed and the beach washed away.
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Huge quake struck at 2.46pm, An hour later, a vast amount of
water rushed in. The waves did not stop till they had reached
three miles inland. Very few survivors likely.
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In this town, search for survivors turned into a search for bodies.
Among the dead are mostly elderly people. The Natori river here
grew from a sedate flow to a raging wall of destruction.
Yuriage Town
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The tsunami left a trail of devastation,reducing the airport to a water
world. The runway was inundated, aircraft swept away and the
terminal building badly damaged.
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Iwaki area
Whole neighborhoods were in ruin and cars and debriswere piled high around Iwaki.
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Early Tsunami Warning System
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193
y g y
Basis: Seismological waves move 30to 40 times faster (6 to 8 km per sec.)
than Tsunami waves (0.2 km per sec).
Lead time can be availed to warn
coastal community if quick detection
and rapid communication systems are
established.
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Towards Building Disaster ResilienceDisaster Management Support Programme National Database for
Emergency Mgt.
Hazard Zonation &
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195
Hazard Zonation &Early Warning
VPN Communications
Decision SupportSystem
Landslide HazardZonation
Cyclone warning
1 Hub at MHA
7 Expert Nodes atNRSA; IMD; CWC;INCOIS; GSI; NIDM; PMO4.5 M Antenna; 4 MbpsBandwidth
22 State EmergencyOperations Centres[SEOCs]1.8 M Antenna
Satellite based VPN for DMS
NIDM
IMD
CWC
PMO
MHA
[NEOC]
Drought Monitoring
Tsunami Response
Working with DoD for
Early Warning
System
Flood Management
Sea Surface Temperature
Land: green pixels show
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196
Land: green pixels show
where foliage is beingproduced due to
photosynthesis; tan pixels
show little or no productivity.
Ocean: red pixels showwarmer surface temperatures,
while yellows and greens are
intermediate values, and blue
pixels show cold water.
Credit: MODIS Instrument Team, NASA Goddard Space Flight Center.
Animation produced using 8-day composite of MODIS data acquired daily
over whole globe during first week in April 2000.
What is GPS
The Global Positioning System (GPS) is a
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197
Space SegmentControl Segment
User Segment
The Global Positioning System (GPS) is a
Constellation of Earth-Orbiting Satellites forthe Purpose of Defining Geographic
Positions On and Above the Surface of theEarth.
Examples of GPS Applications
Emergency Sport and Recreation
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198Environmental Issues Fishing
GPS for Disaster Support
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199
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G hi I f i S
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Map India 2003 201
Geographic Information Systems
Computer-based methodology for managing andanalyzing geographical data
Correlation between various layers of data
Various perspectives of presentation for effectiveinterpretation and analysis of data
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Map India 2003 202
GPS-GIS integration in fleet management
Real-time Automatic Vehicle Location
Position display on map
Driver and control-room interaction
In-vehicle routing and guidance
Monitoring driver and traffic characteristics
Security systems
GPS Augmentations andGIS Integration
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Map India 2003 203
Differential GPS
Beacons and antennae
GLONASS and Galileo Integration
Precise GIS-based mapsto snap back the obtainedpositions to the correct route
Fleet management
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Map India 2003 204
Public transport and utility fleetsBuses, trams, fire-brigade, police vehicles, ambulances
Tracking in case of accidents, thefts or hijackings
Fleet performance, detection of irregularities
Commercial fleetsSupply of raw materials and finished goods
Operations control in manufacturing
Logistics and SupplyChains
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Map India 2003 205
Dynamic routing and trip
allocation
Prompt supply of raw
material and finished Least storage time at
warehouses
Randomness of transit
times, equipment failuresand driver availability
Disaster Recovery (CaseStudy)
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Map India 2003 206
Ground Zero disaster due to the 9/11 attack
Removal of 1.8 million tonnes of debris
Enormous costs and management problems
Continuing search for human remains and debris testingfor evidence
Total loss of the fiber-optic network
Multiple disposal sites
Case Study - Solution
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Map India 2003 207
y Response center in the American Express building
connected to website server at Minneapolis by a fiber-
optic network.
GPS receivers on trucks capable of triggering alarmson signal loss, tampering, deviation from given route,
unauthorized dumping.
GIS maps displaying equipment status and tunnel
locations for lowering tracking levels
Case Study - Results
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Map India 2003 208
y First time use of GPS-based technology for disaster
recovery by Criticom International Corporation of
Minneapolis, Minnesota
Task accomplished in 8 months Cost $750 million Vs predicted $7 billion
Online access of audit data after closure
Pilot Experiment
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Map India 2003 209
p GPS readings for key landmarks and major roads to
check for signal availability in the IIT campus
Trimble GeoExplorer3 mapping-type hand-heldreceivers used to log data
GPS data processed by Pathfinder Office softwareversion 2.8
GPS data exported to GIS ArcView software version
3.1 to plot colour-gradation of PDOP and HorizontalPrecision values along the route
Pilot Experiment Results
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Map India 2003 210
Pilot Experiment Results (contd.)
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Map India 2003 211
Pilot Experiment Results (contd.)
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Map India 2003 212
Conclusions and Future
Work
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Map India 2003 213
Precision of positioning obtained in the pilot test goodenough for transportation purposes
Canopy problem can be solved using precise GIS-basedmaps
Real-time integration being pursued using rover receiver,modem and transmitter for transmission to base station
In times of emergency, knowing exactly where the
victim is could be the difference between life and
death. The global positioning system benefits
emergency responders with almost pinpoint accuracy
In Times of Emergency
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emergency responders with almost pinpoint accuracy.
This cuts down on response time, which couldultimately result in saving someone's life. GPS canbe used from the air, ground or sea.
Pinpoint Location of Emergency Reports: GPSequipped cell phones can transmit preciselocations. This allows the dispatcher to have animmediate and accurate location instead ofrelying upon descriptions of people who may be
unfamiliar with the area or too distraught toexplain their location. The same technology hasalso helped catch people who make crank callsfrom their GPS-enabled cell phone.
Speedy Arrival Thanks To GPS: GPS softwarecan be used to quickly tell which emergencyvehicle is closest to an accident or otheremergency. With GPS coordinates associated with
land-line telephone numbers, an emergencylocation can be quickly plotted on a map and theclosest emergency response vehicle can be quicklyidentified, saving precious minutes off of theresponse time.
Ground Emergency Response with Car Navigation
Step1: Turn the GPS on. Allow the deviceto track satellites. Once the system has
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y
tracked the satellites, it will display whereyou are. The GPS is now ready to use.
Step2: Locate where the emergency is.This information is usually provided bythe dispatcher. The street address can beentered into the GPS.
Step3: Follow the step-by-step directionsas the GPS guides you to the location ofthe emergency.
Very useful for Fire departments/Police
departments/Ambulances-Hospitals andother emergency services
Emergency Response Using GPSFrom Aircraft
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Step1: Turn on the GPS prior totake off. Allow the GPS to boot upand find your current location.
Step2: Check the coordinates ofthe emergency location. Relay the
coordinates to the emergencyresponse team on the ground. Theground team can then enter thelocation of the emergency into itsGPS to find the exact location.
Step3: Fly to the emergency site.
At-Sea Emergency Response
Step1: Boot up the GPS. Usually
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Step1: Boot up the GPS. Usually
during a response to an at seaemergency, a distress beacon fromthe boat or ship will emit thecoordinates.
Step2: Enter the coordinates into
the GPS to pinpoint the location ofthe distressed vessel.
Step3: Follow the guidance of theGPS to successfully respond to theemergency.
GPS Use in Law Enforcement
Tracking Suspected Criminals: GPS units have been used to record andmonitor the movements of crime suspects Use of such information to aid in a
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monitor the movements of crime suspects. Use of such information to aid in aconviction or an investigation has been challenged by defendants as aninfringement of their privacy.
Tracking Convicted Criminals: GPS bracelets can be placed on selected felonson parole to monitor their movements. For example: the system could monitorif criminals are staying away from the homes of their victims, travelling towork each day or going near schools. Such systems can be used to verify thatcertain restraining orders are being obeyed.
Online Crime Maps: The San Francisco police department is running an onlineGIS that allows the public to create maps of the locations of different categoriesof crimes which have occurred over the past 90 days. This is part of theirphilosophy of keeping the public well informed.
Appeal You Speeding Ticket With GPS Data: A few individuals cited forspeeding have produced GPS tracking information from their on-board GPS toappeal their ticket. Maybe the officer stopped the wrong car or his radar wasmalfunctioning?
Ground Emergency Response : GPS technology helpedthe forces to know the location and to respond quickly.It helped them to know the no. of EXIT points,topography.
GPS & MUMBAI ATTACK
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Tracking : It helped in geographically track via GPSavailable resources in real time and enabling thecreation of mini private networks that allow suchresources to be deployed in a manner which maximizesefficiency and effectiveness and minimizesduplication.The data available was also analysed howthe GPS was used to guide the terrorist to locationsacross Mumbai and on the costal belt. Thereby
ensuring proper security can be established at eachlocation in future by creating a GIS network
Prevention: The Mumbai attacks could have beenprevented if the governments of the Indian coastalstates had adopted the recommendation of the CoastGuard to fit all fishing boats with a low-cost GPS-enabled alarm system.The device known as low cost
Distress Alarm Transmitter (DAT), developed by SpaceApplication Laboratory, ISRO Ahmedabad is a smallGlobal Positioning System (GPS) based fisheries alertsystem.
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