A Convolutional Neural Network approach for downscaling climate model data in Trentino-South Tyrol (Eastern Italian Alps)

Autor: Alice Crespi, Daniel Frisinghelli, Tatiana Klisho, Marcello Petitta, Alexander Jacob, Massimiliano Pittore

Statistical downscaling is a very popular technique to increase the spatial resolution of existing global and regional climate model simulations and to provide reliable climate data at local scale. The availability of tailored information is particul

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ac65d4b056bfdd96601396818b80546c
https://doi.org/10.5194/egusphere-egu22-10120

A Methodology for Heterogeneous Sensor Data Organization and Near Real-Time Data Sharing by Adopting OGC SWE Standards

Autor: Andrea Vianello, Daniel Frisinghelli, Roberto Monsorno, Mattia Rossi, Armin Costa, Bartolomeo Ventura

Publikováno v: ISPRS International Journal of Geo-Information
Volume 8
Issue 4
ISPRS International Journal of Geo-Information, Vol 8, Iss 4, p 167 (2019)

Finding a solution to collect, analyze, and share, in near real-time, data acquired by heterogeneous sensors, such as traffic, air pollution, soil moisture, or weather data, represents a great challenge. This paper describes the solution developed at

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75b7dd5b59425b541c7b4dd1dd925128