The Green index is a process used to determine the amount of environmental impact a city has.
The vegetation index is an important indicator in crop development analytics. Of the many benefits of vegetation indices in remote sensing, the accuracy of the data and the ability to monitor remotely are the main reasons for the transition to this convenient technology.
As sensors improve, Earth observation satellites are fueling remote sensing developments with new data, improving the analysis methods already in place. With the introduction of ever-evolving innovations in vegetation index applications, companies that already have off-the-shelf index-based software, as well as those just planning to launch a new solution, can greatly increase the demand for their field monitoring applications.
Vegetation Index in Digital Agriculture Solutions
The integration of satellite analytics can increase the existing value of precision farming applications, as well as address certain limitations that are currently present in them. In particular, the use of vegetation indices in software gives software providers the following business management benefits:
- Quality data analysis;
- the ability to expand the range of services provided;
- access to a variety of satellite image sources in one location;
- Reducing internal costs;
- increasing the value of their products.
The many benefits of vegetation indices in remote sensing also help improve customer service. Unlike other aerial imagery, satellite imagery allows:
- Save money on drone operations, data processing, and interpretation;
- cover more territory compared to aerial imagery;
- reduce costs for field monitoring: additional use of UAVs is more expensive than regular satellite overflights
- obtain data analytics in a shorter timeframe and a preferred format;
- monitor fields regardless of wind strength.
With satellite imagery, agricultural software providers can greatly expand their existing aerial photo data pool and save time and resources, and end-users can access more data faster. For example, vegetation indices in remote sensing are used for qualitative remote analysis of crop conditions. If a problem arises, farmers can recheck only the marked areas rather than inspecting the entire field.
