BiGMAP - 2019

Over the past many decades, information in the form of digital data has become the foundation on which governments, industries, and organizations base many of their decisions. In our modern world, there exists a deluge of data, many technologies and tools that grows exponentially each day. Geospatial technologies have been identified as one of the most important emerging and evolving fields. From a technological perspective, geospatial technology went from the desktop to server and now incorporates everything from desktop, mobile, tablet, server and the cloud.

The most well known geospatial technologies are Global Positioning Systems, Geographic Information Systems, Remote Sensing, Modelling and Information Technology. Geospatial technology was traditionally confined to use by the military, intelligence agencies, maritime or aeronautical organizations etc. In the early days, geospatial technology was mainly used by cartographers, who needed a way to overlay multiple spatial datasets to produce a single map. It helps in forecasting the implications of planning or monitor any changing phenomenon. The practitioners and end users of Geospatial technology were one and the same: the scientific community. Over time, its user base became more diversified, attracting attention from all walks of user community, governmental agencies, academics, researchers and businesses. Geospatial data is highly influential in today’s processes of various themes that uses Geospatial data for planning, management and monitoring of government public and private service delivery. Geospatial technology is widely used in many sectors like agriculture, environmental management, forestry, urban planning, public safety, infrastructure, telecommunications and logistics to name a few.

Over the past decade, the Earth Observation (EO) data is managed and processed by information systems have increased from the terabyte level to the petabyte and hexabyte levels. It is well known that the EO data is generated by global and local sensor systems/networks. The data are not only bigger than before, but also have increased complexity due to their very special characteristics of volume, variety, velocity, value, veracity, and variability. The big EO data means that capabilities of traditional data systems and computational methods are inadequate to deal with these characteristics. Today, in addition to analysis of EO data only, scientists are also using socio-economic data to complement EO data to gain a better understanding of the socio-economic-environmental systems which also require the use of Geo-Analytics.

Big Data Geo-Analytics is a burgeoning science area that aims to solve complex problems by integrating many layers created using various tools of geospatial technology. Geospatial Data- Analytics and Modelling not only provide comprehensive mapping capabilities, but also move beyond visualization with built-in support for a broad range of advanced Geo-Analytics which help to reveal the crucial Geospatial information and expose hidden geographic relationships. The common examples of advanced Geo-Analytics are machine learning and artificial intelligence which have already been integrated into Geospatial technology.

The Ludhiana Chapter of Indian Society of Remote Sensing, in Collaboration with Punjab Remote Sensing Centre is organising a national conference on “Big Geospatial Data-Analytics, Modelling and Applications” from September 25 -26, 2019. This conference intends to identify the significant trends and technological approaches for application of Geospatial technology in management of natural resources, integrated modelling strategies, data management and big data analytics. The technical content will cover the application of multispectral, hyperspectral and microwave airborne and space borne data in natural resource management, the use of GIS in e-Governance, public utility and facility, preparation of WebGIS and mobile applications, and also the use of Geo Analytics borrowed from many machine learning techniques for Geospatial data processing and its management.


The main themes for Big Geospatial Data-Analytics, Modelling and Geospatial Applications will cover the following subthemes:
• Big Data Analytics
• Earth Observation Sensors and Data Processing: Thermal, Microwave and Hyperspectral
• LiDAR, Virtual GIS and 3-D Mapping
• Natural Resources and Environment Management
• Water Resource Management
• Open Source, Mobile Apps and Crowd Sourcing Data Management
• SMART Urbanization and Rural Development Planning
• UAV Data Processing and Applications
• Weather, Climate Change and Modelling

May 20, 2019 Start date of Abstract Submission
July 30, 2019 Last date of Abstract Submission
August 14, 2019 Notification of Acceptance of Submitted Abstracts
August 31, 2019 Last date of Full Paper Submission
September 25-26, 2019 Conference