We will be providing pre-processed data and GPU compute. 

• Landsat 8 (and 9 when available) imagery – publicly available

• LiDAR point cloud (QL2) – publicly available

• Jurisdictional boundaries – publicly available

  • LA County boundary

  • Santa Monica Mountains National Recreation Area boundary

  • Unincorporated areas LA County boundaries

  • 88 cities of LA County boundaries

• Tree infestation – provided by the County
  

  • ISHB infestations – excel file with information on known ISHB infestations, including coordinates, date of detection, infestation severity, and tree species

  • GSOB infestations -- GIS files with information and visual examples of known GSOB infestations
  • The lat/long and time stamps of the ISHB and GSOB infestations are available as pre-processed chips, with the data mapping to Landsat time series data.
• Lenovo Data Science Workstation
  • Specs: Dual Socket Xeon GOLD 8 Core, 196GB DDR4 Ram, 1TB NVME SSD, and Dual Nvidia Quadro RTX 8000

Academic References and Resources:

• Opensource Geo tools: https://www.osgeo.org/
• Open Topography: https://opentopography.org/
• R Statistics: https://www.r-project.org/
• perhaps not necessary but can be useful for large dataset https://www.geomesa.org/
• if you’re using R, this is good for visualization and analysis https://cran.r-project.org/web/packages/ggmap/index.html

The Esri Living Atlas of the world has lots of datasets shared from around the world, along with pre-trained deep learning models that can be used to perform that kind of detection, data collection, analysis: https://livingatlas.arcgis.com/en/browse/?q=tree#d=2&q=tree

...along with a free developer subscription to ArcGIS that gives you access to those things, along with cloud storage of your maps, data, and tools, available here: https://developers.arcgis.com