National Spatial Data Infrastructure (NSDI)

Census of India

Survey of India Topographic Maps

All of the above

Ministry of Earth Sciences (MoES)

Department of Science and Technology (DST)

Indian Space Research Organization (ISRO)

All of the above

To collect data on population and housing

To create a comprehensive database of demographic information

To assist in planning and policy-making

All of the above

Survey of India (SOI)

National Remote Sensing Centre (NRSC)

Indian Institute of Remote Sensing (IIRS)

None of the above

The use of NSDI for disaster management

The application of Census data for urban planning

The integration of Survey of India Topographic Maps with GIS

All of the above

To provide real-time information on natural disasters

To assess the impact of disasters on infrastructure and population

To facilitate coordination between disaster response agencies

All of the above

To identify areas with high population density

To analyze trends in population growth and migration

To project future population estimates

All of the above

It has enabled the creation of detailed topographic maps

It has facilitated the analysis of spatial data

It has supported the development of 3D models of terrain

All of the above

Data inconsistency and lack of standardization

Limited access to data due to privacy concerns

Technical challenges in data integration and analysis

All of the above

By promoting data sharing and collaboration among different organizations

By investing in data quality control and standardization

By enhancing data accessibility and user-friendliness

All of the above

Disaster management and risk assessment

Urban planning and development

Environmental monitoring and conservation

All of the above

By providing information for evidence-based decision-making

By supporting the development of policies and strategies for sustainable development

By facilitating the monitoring and evaluation of sustainable development initiatives

All of the above

The use of big data and artificial intelligence for data analysis

The development of cloud-based geospatial platforms

The integration of geospatial data with other types of data

All of the above

By identifying areas with high levels of social vulnerability

By analyzing patterns of social exclusion and discrimination

By supporting the development of policies and programs for social inclusion

All of the above

Data privacy and security concerns

Lack of skilled professionals in geospatial technologies

Limited funding for geospatial data collection and management

All of the above