In recent years, there has been an explosion of geo-datasets derived from an increasing number of remote sensors, field instruments, sensor networks, and other GPS-equipped “smart” devices. Processing “Big GeoData” of this kind requires flexible tools that combine efficient programming on either personal or supercomputers.
Open Source geo-software such as GRASS and PKTOOLS allow for the fast and efficient processing of geo-datasets found as rasters and vectors, which are layers key to the visualisation of each dataset and can be overlaid in any combination. Such software can be integrated into complex workflows using a Bash or Python interface.
Cross-disciplinary researchers and analysts are often unable to design and implement their own complex geospatial workflows given the dearth of fundamental programming proficiency. To address this educational need, the Spatial Ecology team offer intensive geospatial training workshops.
We offer training programmes tailored to your project needs:
- Open-source GIS and spatio-temporal data processing
- Machine learning, data mining and predictive modelling
- High performance computing / cloud computing
- Implementation of Open Data strategies
Data applications include:
- Natural resource & disaster management
- Agriculture & Agroforestry
- Defence & Security
- Ecosystem services, and others
Past course offerings are listed here: https://spatial-ecology.net/training/past-courses-reviews/
For additional information, please email Tushar Sethi, Head of Operations at Spatial-Ecology: firstname.lastname@example.org