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 The potential of this 10m “clutter” source is being able to acquire data from a few days ago instead of using outdated “very old” 2020 vintage datasets.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
This image, acquired by one of the Copernicus Sentinel-2 on 8 February 2022, shows ongoing wildfires in the Boma National Park in South Sudan. Fires are common at this time of year in the sub-Saharan region.
Allocates a set of demand points (Customers) to user specified number of supply points (Facilities) out of a Facilities point dataset based on the Euclidian distance between the Customers and Facilities.
Me vinieron a entrevistar de SOYDATA.net para hablar de temas relacionados con la Geovisualización como el Big Data o el Open Data y su implicación con el Control de Calidad o el Software libre. Gracias a Jorge Ubero de SoyData por la misma. Espero que os guste, ya sabéis que si tenéis algún comentario o algoContinue reading “Entrevista en ‘Soy Data’”
The benefits of Open Data are diverse and range from improved efficiency of public administrations, economic growth in the private sector to wider social welfare (Source: http://www.europeandataportal.eu/) Performance can be enhanced by Open Data and contribute to improving the efficiency of public services. Greater efficiency in processes and delivery of public services can be achieved thanks toContinue reading “Creating value through Open Data”
THE IDEA: DEMONSTRATING HOW DYNAMIC A CITY IS, THUS HOW IMPORTANT IS HAVING AN UPDATED DATASET THE FACTS: THE CITY OF BOGOTÁ IN COLOMBIA 2012-2014 Overall growth rate: -0.12% ONLY HAVING INTO ACCOUNT THE DIFFERENCE OF BUILDINGS CAPTURED BETWEEN 2012 AND 2014 (We can do this because we have used the same data capture model in both years) (DeContinue reading “Change detection – Detección de cambios en polígonos”
Hi guys, Surfing the internet is great when you need to figure out something. I needed to validate some DTM from unknown sources against an also unknown source (but at least a kind of reliable one, Google Earth). All we need is Google Earth TCX converter ARcGIS Excel This is the procedure i have followed:Continue reading “DTM validation using Google Earth (and RMSE extraction)”