Remote Sensing Data Analyst


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About FluroSat

FluroSat is building decision support systems utilising the analysis of remote sensing data (aerial and/or satellite imagery). We provide agronomists with information on stress levels and nutrient content distribution around the paddock (e.g., crop health maps, N or chlorophyll levels maps) calculated using our advanced modelling and processing tools. We go into in-depth analysis, extending NDVI to the identification of individual stressors.

What is different about us, is that we want to build reliable correlations combining multiple sources of hyperspectral / multi-spectral imagery (drone, satellite, ground-based sensors) and do it step by step for various crop types. Currently, we are looking for partners working with farm management software and agronomists keen to trial our solution.

This unique crop health monitoring and data processing system for early stress identification will enable farmers to save on fertiliser and pesticides through variable application and improve crop yields. Project stages include field trials (in progress), testing of the technology using a UAV and a weather balloon with the final stage of the project being monitoring and analysis of global crop coverage using space-borne data.

For more information, please visit our website:

Job description

If you are keen to see drone and satellite data put together in front of your eyes and changing the future of modern industries, you are the right person. The position involves processing of the data and making sure pictures are nicely aligned and the numbers are flowing. More details below:

Your role

  • Cross-calibration of multi-scale spatial data
  • Processing of multi-spectral and hyperspectral satellite/drone/plane imagery
  • Development of automated data processing routines using Python in GIS environment

Your experience

  • Degree in Data Analytics or Earth Science field
  • Experience with processing remote sensing data and using GIS software, e.g. QGIS * - required
  • Previous experience with spatial data sets (satellite/aerial data) - highly valuable
  • Strong Python abilities; experience in GDAL - desirable
  • (If you have worked with Google Earth Engine or Google Cloud this job is for you) - winner
  • Sydney, New South Wales, Australia
  • Web Development
  • Software Development
  • Database Administration
  • Systems Analysis
  • Machine Learning