Central Mine Planning & Design Institute Limited (CMPDI), a subsidiary of Coal India, now maps major coalfields by using satellite data, and then integrates that data with machine-generated data from remote sensors and airborne, surface, and subsurface geological, geophysical, and geotechnical data from geographic information systems (GIS).

By integrating diverse big data sources into a composite picture, CMPDI’s 360-degree visibility of its mining operations enables it to identify target drilling sites, to plan and develop mines, and to follow its entire mining life cycle all the way through to mine decommissioning and reclamation. CMPDI can also do this with less risk, because it further enriches its geospatial data with risk management information on potential environmental, regulatory, and safety impacts of mining in specific areas.

Other earth-and-soil industries such as agriculture are also seeing the benefits of expanded geospatial visibility that focuses on big data aggregation.

In agriculture, new precision farming techniques utilize expanded big data visibility that is organized around geospatial data integration. This enables farmers to see the quality variability of their fields so they can better optimize their farming strategies and investments in order to maximize production yields. The goal is to pinpoint the most fruitful areas of land to cultivate and to invest resources there, since in a large tract of farmland, different areas of the land possess different variations of soil types, moisture content, and nutrient availability. By using integrated geospatial data, precision farming technology can superimpose remote sensing technology that can “gauge” the characteristics of the land tracts on GIS and global positioning systems (GPS) that map out different arable areas and also indicate which areas are most optimal for certain types of crops and crop growing investments.

The increased use of geospatial analysis with inclusion of big data from sensor-based, satellite-based, and data repository-based information is providing more 360-degree insights into mining and farming opportunities than ever before. Yet, as companies reach these new heights of enhanced visibility, they are also recognizing that the quest for everything they need to know is still in front of them.

For instance, in farming, agriculture insurance companies first looked at historical data on rainfall and crops and satellite information, but they quickly found that there were limits to the satellite data when it came to interpreting rocky landscapes or cross comparing these to landscapes covered by grasses or trees. They found that they needed more accurate geospatial information in order to arrive at a truer 360-degree view of land tracts, so they began to collect on the ground observations in certain areas that could “correct” the inaccuracies of the satellite data.

Two big takeaways

First, the 360-degree view of what is happening in the field — even when facilitated with today’s big data aggregation and processing technologies — is a moving target. Part of what we see with this data is a new horizon of visibility that we still need to get to. Some of this new 360-degree reaching is simply error correction techniques that are undertaken to correct misperceptions that can be created by “unedited” big data as in the agricultural information. In other cases, new questions are raised that the boundaries of the data analytics have yet to answer.

Secondly, manual intervention and interpretation of computed data is an important part of big data analytics. Whether data verification and correction is done on the ground or in an office, the unpredictable and creative properties of human thought continue to generate new possibilities for working the data that pushes the 360-degree view of business into unexplored frontiers.

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