Google Earth Engine and Dynamic World

Let me please introduce you this “new” LULC source I have come across with recently. The potential of this 10m “clutter” source is being able to acquire data from a few days ago instead of using outdated “very old” 2020 vintage datasets. I know if these days something 2020 is very old then myself, born in 1972 then i’m older than the riverside, older than peeing in a wall, even older than Methuselah. Yes, that’s the way it is nowadays.

Google Earth Engine is a geospatial processing service where you can perform geospatial processing at scale, powered by Google Cloud Platform. The purpose of Earth Engine is to:

Provide an interactive platform for geospatial algorithm development at scale
Enable high-impact, data-driven science
Make substantive progress on global challenges that involve large geospatial datasets

Supervised Classification using the Google Earth Engine, analysis by Mijanur Raman

What I like the most from Google Earth Engine is how powerful can be. You can take i.e all images from the whole Sentinel 2 series over certain spot and measure NDVI throughout time or you can take an analysis you first thought it was ideal over India and then you can use it anywhere else in the world.

Google Earth Engine y los incendios de verano: el caso de Cadalso de los Vidrios, Madrid (Julio 2019)

Gracias a la inestimable ayuda de mi compi de co-working Pablo Martín -ingeniero Forestal- con Google Earth Engine hemos modelado este NBR (Normalized Burn Ratio) que usa los canales NIR y SWIR de Sentinel-2 para medir la severidad del incendio de la semana pasada en mi pueblo, Cadalso de los Vidrios (Madrid, España). Rozamos la tragedia en lo personal pero sin duda fue terrible a nivel material. Tardaremos décadas en revertir este funesto incendio…