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