Artificial Intelligence (AI) has become a buzzword that symbolizes the next stage of innovative technological transformations and how the industry in the future would be driven. Using intelligent algorithms, data classification and smart predictive analysis, AI has its utility in a large number of sectors.
A more specific subset of AI that combines the exactitude of GIS with the razor-sharp analysis and solution-based approach of AI is termed Geospatial AI, or simply Geo.AI.
The main consequence of electricity theft is widespread power outages. Also, electric utility companies across Nigeria struggle with illegal connections to the power grid that generate huge losses and are a hazard for locals. GIS Cloud a software development company from Croatia is joining the fight to help mitigate this problem.
The Enugu Electricity Distribution Company utilized their GIS solution to map the entire distribution network and enumerate customers, an important step in tackling the rampant electricity theft in Nigeria.
Yes, when it comes to flood detection, CYGNSS is proving to be better than the mighty Landsat birds operated by USGS and NASA, or even the European Space Agency’s Sentinel 1 and 2 satellites. Unlike Landsat (which cannot see through clouds) or Sentinel (which draws a blank on hitting vegetation), the CYGNSS satellites can see through all things – clouds, rain and vegetation – that could obscure floodwaters.
There are dozens of websites that NASA uses to host its remote-sensing data and tools (more than 50, we kid you not!). So, for someone not too familiar with the geospatial industry, making sense of all this information or even figuring out which asset can be located where could be an overwhelming exercise. Not surprisingly, NASA has not been able to make startups or other small businesses tap into its full commercialization potential, even though these companies could benefit greatly from access to free and open remote-sensing data.
Despite what you may have heard, there’s A LOT more to GIS than “maps and data”: That’s why we’ve put together this comprehensive list of GIS definitions: We give you stunning visualizations so you can have 20/10 vision of each definition term.From A to Z, GIS professionals, students and everyone with an interest can sharpen their GIS knowledge with these GIS dictionary definitions and meanings.
These trends are shaping the face of urban planning all over the world.
Geographic Information System is fast becoming the tool to use for sustainability and planning as we seek to maximise the efficiency of the environment around us and protect what needs to be protected while maintaining health and jobs in the modern economy. People who work in Sustainability know that many disparate elements must come together in order to keep the mechanics of the world around us functioning in the way we want it to function; today, this includes the ecology.
Urban planning focuses on the design and regulation of the use of space that focus on the physical form, economic function and social impact of the urban environment and on the location of different activities within it. Urban planning is more than physical planning, the effect of urban planning is felt in every sectors.
Mapfit – a New York-based startup is quietly disrupting the map making industry. For the past two years, the company has been developing the platform that can automatically analyze and make sense of hundreds of IoT data sources and seamlessly generate map updates. None of the big mapping companies: Google, Apple, TomTom and HERE, with all their resources, was able to achieve that.
You’ve probably heard about machine learning (ML). But you’re not exactly sure how to use it in the context of GIS.
Simply, machine learning makes sense out of noisy data finding patterns that you’d never think existed. In other words, it’s software that writes software. Instead of applying a pre-built function, ML gains experience through repeated seen conditions and builds a model to apply in new situations. For example, Google might use Bayesian classification to filter spam emails. Alternatively, Facebook might use it for facial recognition and automatically identify faces in images. And ML can even render Nicholas Cage in every movie ever made.