2014 marked the time when the EU took the title from NASA when they launched the Copernicus Program and their network of upgraded satellites. NASA’s LandSat held that rank for decades with the LandSat Program which was much loved by scientist groupies everywhere. Recently, however, some VC backed new-kids-on-the-block have begun to shake things up in the space space with their unorthodox methods; shoe box size satellites, low cost and quick turnaround images. Can this scrappy newbie really compete at this level? Do they have what it takes?
Satellite imagery is becoming a more critical component to a vast array of sectors in tackling the fundamental challenges we face today. Gargantuan quantities of imagery have and is being collected and resources like machine learning and cloud computing are becoming available that will allow us to process and utilize this data in operational ways.
This raw satellite imagery has typically been collected in extremely standardized ways with hardware and software that has been calibrated over years by leading scientists. This standardization in collection can make the processing of it a more straightforward process; especially when one is analysing it from a temporal perspective.
New, disruptive entrants to the market, such as Planet have not adhered to the same principles. They developed low cost, shoebox size satellites that record the earth on an almost daily basis and they have done this in a record time. They are the pioneers of the mini and micro satellites.
What does this alternative approach to satellite surveillance mean for the processing of the imagery and the reliability of the results? Desire Rukudde will talk about his experience with both types of imagery for the conservation and forestry sectors. No technology is suitable for every scenario so Desire will guide us as to where best Sentinel and where best Planet imagery be deployed. He will also talk about the likely evolution of these technologies and what that means for us on the ground who are working with that imagery.
Casual but interesting but humorous but serious
Evet Naturinda is a GIS analyst at Geo Gecko, I mainly analyse big data and process satellite imagery using machine learning algorithms and cloud computing to come up with insights that help different stakeholders in decision making. Part of my work is the research paper I wrote entitled ‘Assessment of the impact of deforestation on forest carbon storage, A case study of mabira forest, Uganda’. The aim of this study was to provide a better understanding and quantifiable information on the economic consequences of deforestation in Uganda.
My home country is Uganda and outside work am interested in traveling, reading and watching.