Dr. Arun Pratihast is a Senior Data scientist at Wageningen Environmental Research, team Earth Informatics, Wageningen, The Netherlands with a passion for the effective application of data and technology for forest, biodiversity, and agriculture monitoring. He focuses on citizen Science, geoinformation technologies, mobile application development, open and big data flow, data standardisation, software engineering and how these can lead to user-friendly applications and quality decision making. He is also actively engaged in the training and capacity building activities of World Bank, SilvaCarbon Global Forest Observation Initiative in many countries around the world. He has also received Google Earth Engine Award 2015.
Arun has a PhD from Wageningen University entitled "Interactive community-based tropical forest monitoring using emerging technologies”. This PhD project was funded by Centers for Natural Resources and Development (CNRD), DAAD Fellowship Programme and was in collaboration with Institute for Technology & Resources Management in the Tropics & Subtropics (ITT), Cologne University of Applied Sciences, Cologne, Germany and the Laboratory of Geoinformation Science and Remote Sensing , Wageningen University, Wageningen, The Netherlands. Prior to coming to Wageningen, he completed his MSc. at ITC, University of Twente, Enschede, The Netherlands and his undergraduate degree in Computer Engineering from, Tribhuvan University, Nepal. A full list of publications can be found via his GoogleScholar or ResearchGate profile.
“Community-based Tropical Forest Monitoring Using Emerging Technologies”
The unprecedented destruction of tropical forest cover has serious negative consequences on the regulation of the world’s climate cycle, biodiversity and other environmental variables. With rising global temperatures, improved forest monitoring, especially at the landscape scale has become increasingly important. Because forest changes manifest at a variety of spatial and temporal scales, effective monitoring will likely require an integrated approach, where detailed community-based in-situ observations are combined with remote sensing satellites. With these considerations in mind, this presentation will describe an integrated community based tropical forest monitoring system which combines emerging technologies, remote sensing and community-based observation in support of REDD+ monitoring, reporting and verification implementation.