The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008
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emergency managers. Data standards are often inconsistent, and
users are sometimes unaware of the limitations and
uncertainties in data or are presented with conflicting
interpretations of data without the means to assess the reliability
of the sources. All of these issues reduce the efficacy of the
decision-making process at an emergency situation. The need of
the hour is organization of geospatial data and use location
information to integrate varied data sources and make these data
sets accessible for the decision makers. In the pursuit of
institutionalizing, mitigation and preparedness to natural as well
as manmade disasters more efficiently, emphasis has been made
on development and organization of comprehensive Geospatial
databases. In spatial domain, it is envisaged to have a number of
digitized layers on 1:50000 scale for entire country, 1:10000
scale for multi-hazard prone districts and 1:2000 scale for mega
cities, relating to hazard zonation, transportation networks,
settlements, natural resources, hazardous industries, resource
inventories, etc. Although an extensive amount of digital spatial
data has been already developed by various government
agencies, it needs to be collected and compiled. These spatial
data are to be linked dynamically with corresponding non-
spatial information such as socio-economic and infrastructure to
enable decision making processes more efficient and objective.
The integration of geospatial information from multiple sources,
often with varied formats, semantics, precision, and coordinate
systems is a key issue. It is also envisaged to analyze
emergency trends, demographic patterns, economic profiles,
infrastructure status, communication networks, public utilities
etc so that the database could also be shared in coupling disaster
reduction and economic development, especially in the
vulnerable areas.
For hazard/emergency management the data requirements can
be grouped into two categories i.e. core data sets and
hazard/emergency specific geospatial data. The geospatial data
organization for emergency management include identification
of data sets, its availability and gap areas, bringing the diverse
data sets into a common platform with some standards and
develop mechanism for data access and dissemination at the
time emergency situation.
Core data sets are those which are commonly required to handle
most of the emergency situations. The core data sets may not be
specific to a particular emergency. The creation and
organization of this kind of data sets need unique standards. The
required core data sets have to be created/ organized in three
different scales i.e. 1:50,000, 1:10,000 and 1:2000. The data
sets at 1:50,000 scale will be used for first cut assessments and
preparation of overall mitigation/ relief planning. The data sets
at 1:10,000 scale will be used in implementation of relief and
rescue operations for multi-hazard prone areas. The data sets at
1:2000 scales will be used in implementation of relief and
rescue operations for mega cities.
Hazard specific data sets may be required to handle a particular
emergency situation. The hazard specific geospatial data sets
have been identified to handle the particular hazard/emergency,
like cyclone, flood, landslide, earthquake, fire, structural
collapse etc. Standardization and organization of hazard
specific data play a vital role in damage assessments, relief,
mitigation and rescue of life in the event of an emergency
situation. An exhaustive list of database elements pertaining to
both core and hazard specific data have been identified through
brainstorming required for addressing emergencies arising out
of natural and man-made disasters. Figure-1 shows the core and
hazard specific data sets.
Further it is also envisaged integration of real time of data from
a variety of measuring stations from filed such as Automatic
Weathering Stations, in situ sensors etc. besides remote-sensing
data, aerial and lidar data. Some of the datasets such as location
of medical facilities, relief shelters, civil supply godowns in
spatial format is not available which needs to be generated
using appropriate technologies. Further the amount of data to be
organized is quite extensive and is difficult to collect physically
from various sources and convert to the required format for
organizing into database especially for a large country like
India. Hence it is proposed to use web interface for data
collection and organisation wherever applicable.
3. DECISION SUPPORT TOOLS
One of the most important elements in emergency management
is the availability of information at right time for taking
appropriate decisions. Whenever a flood / cyclone threat is
sounded, necessary actions should be initiated to minimize the
impact for which scientific inputs should be made available in a
ready to use format to the district officials. The primary
information will be on the likely impact of the event in terms of
the extent of the area affected, location specific details,
population affected, availability of resources for evacuation of
the people & relief and quick assessment of damages. The
process of collection of basic information at the time of the
event may not be possible. Most of the times, the required
information is not available in the required format due to
various reasons, and decisions are being taken based on the
knowledge and experience. Hence, there is a need to make
available the required information to the key persons in the
disaster management activity with appropriate tools to support
the decision making process based on scientific inputs. Early
warning, risk prediction, situational analysis, damage
assessment, thematic hazard maps etc. are some of the major
activities of the data management system of emergency data
and information system configuration. To achieve these
objectives there is a need to develop software applications to
support decision-making using available data sets in centralized
data server. Spatial Decision Support System (SDSS) is a class
of computer systems that combine the technologies of GIS and
Decision Support System to aid decision-makers with problems
that have spatial dimensions. It is a central database, where data
and information can be made available on-line. It is an
intelligent system, to help planning activities. It is also an
electronic-based correspondence system and report generator
that can be modified according to the user. Emergency response
applications will require not only real-time collection and