What we do
We generate geo-intelligent products to enhance the work of decision makers.
We do this by embracing the following principles.
We spend a lot of time researching and developing solutions. For example, now we are testing how satellite borne radar can be used to measure the height of sugar crops. By tapping into the powerful new technologies such as daily satellite imaging, drones, artificial intelligence and cloud computing, we can develop new intelligence products for our clients.
In the immortal words of the geo-intelligence guru, MC Hammer, when we interact with a client we stop, collaborate and listen. We realise that our clients will know more about their environment. We analyse the data and work with our clients to help them interpret the results.
Our work can be broken down into three components
We generate data.
We map it.
We analyse it.
Geo Data: The Foundation
Reliable data is a valuable commodity in the context of developing countries. Where relevant data exists, it is often out of date, inaccessible or stuck in an unusable format.
Geo Gecko creates data. We use satellite data to generate building outlines, field data collectors with mobile devices to survey households and planes (LiDAR) & boats (bathymetric) to collect 3D data of terrain.
We acquire data from partners. We have strong relations with government authorities, satellite companies and private sector actors and use their data to bring insight for other interested parties.
We use these various datasets to generate new data and carry out our advanced analysis.
GEO Mapping: The Big Picture
The First Law of Geography, according to Waldo Tobler, is everything is related to everything else, but near things are more related than distant things. Maps help us to understand the environments in which we work and how features in those maps inter-relate.
Combining beauty and function, we create hard-copy and soft-copy cartographic products that inform and generate debate.
GEO Analysis: The Actionable Intelligence
A map will show the features and the data, e.g. the populated areas and the power lines.
The analysis will provide the actionable intelligence e.g. the number of businesses within 1000m of the power line and what is the statistical correlation between proximity to the grid and the financial turnover of these firms.