🌍 GIS Conference Opportunity

📍 GeoInno 2026 | Geography of Innovation Conference
🗓️ Jan 28–30, 2026 | Corvinus University of Budapest, Hungary 🇭🇺

An international forum on innovation geography, spatial data, and regional development—bringing together academia, policy, and industry. 🚀

🔗 https://www.geoinno2026.com/

#GeoInno2026 #Geoinformatics #GIScience #Innovation #SpatialData #RegionalDevelopment

A growing list of 2026 geospatial conferences is live 🌍

URL: https://github.com/Nowosad/conferences_2026

If you know of additional GIS or remote-sensing events, please contribute. PRs and suggestions are welcome.

#GISchat #Geospatial #SpatialData #Conferences2026

Acabo de actualizar mi dataset sobre contaminación lumínica nocturna global generado con mi herramienta radiance-geojson (https://codeberg.org/imigueldiaz/radiance-geojson). Contiene archivos JSON (.json.gz) y un dump completo en PostGIS (restaurada ocupa 27GB, con casi 140 millones de puntos georreferenciados), con datos de radiancia, brillo del cielo y clasificación Bortle para 173 países a 0.5 km de resolución. Basado en imágenes VIIRS de Earth Observation Group, Colorado School of Mines.

Puedes descargarlo gratis desde: https://archive.org/details/radiance-geojson-data-2025

Ideal para análisis geoespaciales, ambientales y astronómicos, en mi caso lo usaré para astrofotografía si me da la vida. Licencia CC BY 4.0.

#opendata #geospatial #lightpollution #VIIRS #PostGIS #gis #spatialdata #dataset #CCBY4 #opensource #radiance #astrophoto #astrophotography

Geospatial Imaging Market Update

The global geospatial imaging market was valued at USD 2.36 billion in 2024. It’s projected to grow from USD 2.77 billion in 2025 to USD 7.42 billion by 2032, at a CAGR of 15.1%. North America held a 34.68% share in 2024.

Source: https://www.fortunebusinessinsights.com/geospatial-imaging-market-107834

#Geospatial #Imaging #RemoteSensing #SpatialData #GIS #MarketResearch #EarthObservation #Aerospace

🧩 New R package: h3sdm 🐦🌿

Model species distributions using the H3 hexagonal spatial index — a fast and scalable way to bring ecological modeling into the spatial data age!

🔹 Integrates easily with sf, terra, and tidymodels
🔹 Enables spatial cross-validation and H3-based predictors
🔹 Built for real-time or large-scale SDM applications

📦 GitHub: https://github.com/ManuelSpinola/h3sdm

#rstats #Ecology #SpatialData #SDM #OpenSource #GIS #Biodiversity #H3