Unlocking the value of Geospatial big data

Author: Ernest

Geospatial big data refers to spatial data that exceeds capacities of current computing systems. The rapid raise in the availability of locational data with data sources becoming endless brings new opportunities to push geospatial applications to solve global problems and derive revenue for businesses.

With advances in technology, source of locational data is becoming diverse, advances in space imaging technology now supports rapid collection of massive satellite images almost in near real-time, Internet of Things (IoT), Smartphones, Wearables, RFID Sensors are generating massive real-time, spatial temporal and Rapidly changing data with geolocation.

Opportunities in Geospatial big data

Access to massive geospatial big data integrated with analytics tools can immensely benefit businesses across various industries. Businesses are faced with decisions that largely depends on location as key variable making it the focal point between relational data and geospatial technology e.g.

  • Traffic managers are everyday faced with challenges regarding decisions on how to manage busy highways-route public vehicles, ambulances for fast mobility and how it lowers pollution and loss in revenues for  various economies. Road user’s data is critical in generating traffic congestion models, high peak and low peak fluctuations data among other rich datasets.

Practitioners in these sectors often undertake one time traffic surveys on a number of busy highways to generate vehicle volumes data for design and improvement of highways. How can geospatial big data  be integrated with inputs from other sectors to improve transportation planning, traffic management ?

 

  • Analysis of huge, dynamic satellite images e.g. Sentinel Satellite coupled with Artificial Intelligence and Machine Learning Algorithms is changing the way farmers monitor growth of their cross fields, enabling them make critical decisions regarding the crop health at every stage of growth, when to apply fertilizers and when to apply aerosols and ability to estimate crop yields.
  • Health care providers, disease surveillance teams and field volunteers faced with a killer infection often need to reach remote and inaccessible villages to collect data, make diagnosis, formulate interventions to combat spread of epidemics e.g. Ebola in the recent past. With the penetration of mobile technology and Internet volumes of data can be produced from patients, close relatives, health professionals and policy makers. Location becomes key in generating statistics, models, maps that can help analyse, monitor and avert rapid spread of killer epidemics.

The opportunities in geospatial big data lies in the technologies and tools that ingest, integrate and analyses massive datasets delivered on user friendly platforms through a number of media.