Precision Elevation Data for Forest Giants: LiDAR vs ETH Global Canopy Height in Mata do Buçaco (Portugal)

High‑resolution elevation data underpins almost every spatial analysis we do in GIS—especially in forests where vertical structure defines habitat, biomass, wind exposure, fire behavior, hydrology, and the microclimates that sustain rare species. In rugged or densely vegetated environments, a coarse or biased elevation model propagates error everywhere: orthorectification drifts, hillshades mislead, slope/aspect misclassify, and canopy metrics saturate. The result is decisions made on blurred terrain that hides the very patterns we seek to manage. Precision elevation—derived from airborne LiDAR (Light Detection and Ranging)—solves this by separating the ground from the vegetation and delivering both a bare‑earth Digital Terrain Model (DTM) and a Digital Surface Model (DSM). Subtracting DTM from DSM gives a Canopy Height Model (DHM) that captures the true vertical architecture of the forest at sub‑meter resolution.

Agricultura de Precisión. Uso del Satélite para la toma de decisiones en el campo

Quieres conocer cuál es el momento óptimo para plantar? Para fumigar? Para recolectar?. Sabías que dos de cada tres agricultores no cosechan en la fase de madurez adecuada?. Aquí abajo te describo un método completamente automatizado mediante el uso combinado de varios índices de vegetación como NDVI, NDWI, SAVI y EVI que podemos extraer del Satétile SENTINEL-2 en la plataforma COPERNICUS de la UE para conocer exactamente y anticipar las mejores decisiones de intervención sobre tus tierras.

Water Quality Viewer (UWQV) for Sentinel -2

The Ulyssys Water Quality Viewer harnesses the power of Sentinel-2 satellite data to provide comprehensive and accurate water quality assessments. Its intuitive legend and visualization capabilities significantly enhance the user’s ability to interpret and act on environmental data, contributing to better water management and conservation efforts worldwide, particularly in ecologically and economically significant areas like La Mata and Torrevieja salt lagoons.

Faible taux d’humidité au Pays Basque. Sérieux ?

Quand vous venez passer le week-end dans un village du Pays Basque et que vous voyez cette image verte ci-dessous, vous vous dites, ho-ho, ici ils n’ont pas eu les problèmes de chaleur et de manque de pluie que nous avons subis dans le centre et le sud de la péninsule. Mais tout à coup, ils vous disent que oui, ils ont aussi souffert et qu’il est impossible qu’ils aient atteint les niveaux d’humidité des autres années…

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

Wildfires in the sub-Saharan region

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.

Allocation analysis: Attaching customers to facilities

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.

Réalisation du carte de densité pour vérifier Localisation des colonnes aériennes de Nantes Métropole

Localisation et caractéristiques des colonnes d’apport volontaire aériennes de Nantes Métropole utilisées pour la collecte des déchets. Outil de visualisation Global Mapper 17 Format SHP champ: VOLUME http://data.paysdelaloire.fr/donnees/detail/localisation-des-colonnes-aeriennes-de-nantes-metropole/ Ces colonnes sont implantées sur l’ensemble du territoire et sont destinées à la collecte du verre et des emballages recyclables (papier, carton, plastique). C’est genial jouer unContinue reading “Réalisation du carte de densité pour vérifier Localisation des colonnes aériennes de Nantes Métropole”

Creating value through Open 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”

Comparación de DTM usando Global Mapper 17.0.1

Comparar, primero visualmente y después cuantitativamente dos DTM. Por un lado elegimos una fuente muy usual, SRTM con un DTM derivado de Fotogrametría Stereo.