Winners of the Geospatial EDU Contest for HxGN LIVE 2017

This year, we were glad to bring back the Hexagon Geospatial EDU Contest for HxGN LIVE 2017!  In 2015, we started this contest with the goal of engaging some of the brightest geospatial minds and working with them to discover how they are employing our software in their research. We wanted them to highlight how they are using our technology to expand our understanding of the dynamic world around us and the geospatial and push the boundaries of geospatial analysis. This year, we opened the contest to the whole world. We had a resounding response, receiving 22 submissions from 7 countries across the globe.

This exciting opportunity offers students and professors who are utilizing Hexagon Geospatial technology in their research a chance to win a free registration to HxGN LIVE in Las Vegas, as well as money towards travel. Additionally, the winner will have the chance to present their research to a wide variety of thought leaders and influencers in a special breakout session during the conference, and the opportunity to network with those leaders in multiple events at the conference. The winners will present their research at the HxGN LIVE conference in Las Vegas June 13 – 16 and receive an award for their winning research.

The Winning Project is…

Vincenzo Giannico (PhD Student) and his Advisor Prof. Raffaele Lafortezza from the University of Bari, Italy, in cooperation with Michigan State University, for their research in biomass estimation in urban areas from LiDAR. This group of researchers developed an innovative methodology for the biomass estimation in urban areas from LiDAR (laser scanner) data and the results were published in the Remote Sensing (April 2016) magazine. The study was made over an urban forest plantation located in the metropolitan area of Milan, Northern Italy: Parco Nord Milano. The analysis processes were conducted using Hexagon Geospatial software. The methodology developed includes two main steps: data production and modeling. LiDAR classification, orthorectification of multispectral imagery, DTM extraction, and quality control were some of the functionalities used in ERDAS IMAGINE. Statistics from the results of ERDAS IMAGINE were used in conjunction with statistical analysis open source software to derive the results. Through the development of ad hoc mathematical models, it was possible to estimate the amount of biomass present in the study area. This study has great potential for future applications in the estimation of carbon sinks in urban areas.

Honorable Mentions

The Hexagon Geospatial EDU Research Contest was a call for students, researchers, and professors from all over the world to submit their research and win free admission to HxGN LIVE, a session to present their research, and $1500 toward travel expenses. We received many interesting submissions and in addition to the winning research, we would like to acknowledge two honorable mentions for their innovation in the use of Hexagon Geospatial technology.

Ariel Blanco from the University of the Philippines used various types of imagery, GIS layers, and production statistics field observations with the ERDAS IMAGINE Spatial Modeler to find more accurate and reliable methodologies to monitor and estimate sugarcane production.

Igor Sereda from Lomonosov Moscow State University for his project utilizing ERDAS IMAGINE and the Spatial Modeler with Sentinel-2 multispectral and UAV-mounted hyperspectral sensors to identify best practices for Precision Agriculture projects in Russia.

Congratulations to the Hexagon Geospatial EDU Contest winner and honorable mentions. Please join us at HxGN LIVE to learn about the research conducted by Raffaele and Vincenzo. Together, academia and Hexagon Geospatial solutions continue to study, visualize, and model our dynamically changing Earth.

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    Hexagon's Geospatial division creates solutions that visualize location intelligence. From the desktop to the browser to the edge, we bridge the divide between the geospatial and the operational worlds.
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