Interview by the Appalachian State University

Discussing Virtual Forest Tours in Podcast

Prof. Jan-Peter Mund and HNEE graduate Torben Foehrder were guest in the “The Versatilist” podcast of The Immersive Learning Research Network. The podcast covers the latest news in immersive learning across the disciplines. The podcast’s host Patrick O’Shea, spoke with Torben Foehrder and Jan-Peter Mund about their work on “Advantages of 360 Virtual Forest Tours to Supplement Academic Forestry Education.” In 2021, both had published a paper in 2021 describing virtual forest tours and their use in higher education. Patrick O’Shea, Associate Professor at Instructional Technology, Appalachian State University (North Carolina, USA), had discovered the paper and invited both to his podcast.  Listen:

Photo by Robinson Recalde on Unsplash

Photo by Jeremy Bishop on Unsplash
Remote Sensing and Urban Green

Vegetation Cover and Land Surface Temperature

January, 12, 2022. Gulam Mohiuddin – scientific staff, FIT student and IT4Forest enthusiast studied the relationship between the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) in  Phnom Penh City. Understanding the Land Surface Temperature and NDVI can enable urban planners to address urban heat island scenarios.

Mohiuddin presented his research at the digital ICRSUPM 2023: 17. International Conference on Remote Sensing for Urban Planning and Management hosted in Singapore. The analysis was conducted in the frame of the Build4people project- funded by the German Federal Ministry of Education and Research. His publication “Statistical Relation between Vegetation Cover and Land Surface Temperature in Phnom Penh City” is ready for download.

Nature Conservation Digital 2

Digitalisation at the intersection of conservation and commerce

November 9, 2021. When robots destroy weeds with lasers, sensors measure the reaction of trees to climate change, or when fish shoals are digitally recorded – can this serve commercial purposes or will nature conservation benefit? This question was at heart of the 2nd Dialogue Event of the Federal Agency for Nature Conservation (BfN) on opportunities and risks of digitalisation in the intersection of nature conservation and commercial use . In his intervention Prof. Dr. Jan-Peter Mund highlighted the three megatrends at the crossroads of nature conservation: Digitisation, globilisation and climate change.

Innovation - quantum technologies - artificial intelligence

Photonics – enabling technologies for forest monitoring

04.Oct 2021. Prof. Jan-Peter Mund presented at the Photonics Days Berlin Brandenburg. Over 500 participants had registered for the virtual event to discuss the latest tech developments, that emerge with innovation in quantum technologies, integrated photonics and the integration of artificial intelligence.

Prof. Mund presented on monitoring forest diseases and threats with UAV imagery and artifical intelligence. He elaborated on key applications including multi-sensor application for detecting and monitoring forest fires, multispectral application for detecting and monitoring forest diseases and  RGB Sensors producing large scale image mosaics and AI training data and prediction. Vehicle velocity and multiple sensor payloads, near-real-time calibration of sensors, GSD scalability, near-real-time observation, fast and flexible deployment, large AI training sample production and the adaptation of AI – methods and algorithms – are advantages of working with UAV and AI.

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Research Results

Progress prediction of forest storm damage

Nicole Albert – HNEE manager of the WINMOL project attended the FOWITA – the Forest Science Conference. From 13 to 15 Septembner 2021 FOWITA brought together the forest sciences in their entire disciplinary breadth and offered an overview of forest science research in German-speaking countries. Nicole presented progress made in the prediction of forest storm damage.  Discover her presentation.

Point clouds, wearable laser scanning and algorithms for forestry

Performance test of tree segmentation algorithms

Ramazan Bülbül, Stefan Reder and Jan-Peter Mund compared three raster-based and two point-cloud-based algorithms, that were developed for the segmentation of LiDAR point clouds with the aim of individual trees detection and segmentation in data products captured with a WLS using SLAM technology.

The performance test showed  the limits of raster-based segmentation approaches for WLS point clouds, especially in stands with high density. The same shortcomings were observed for the point-cloud-based region growth algorithm which is mainly depended on visible treetops. The ASM3D, developed for LiDAR point clouds, showed  the best performance and was able to detect most trees (>85%) up to 850 trees/ha and is only falling off slightly afterwards (1250 trees/ha; 75% detection rate).

The proof-of-concept study was conducted as part of the WINMOL-Project ( funded by the Fachagentur Nachwachsende Rohstoffe (FNR) and the Federal Ministry of Food and Agriculture, Germany (BMEL) (FNR funding number: 2220NR024A). The research was presented at the SilviLaser 2021 conference in Vienna and the full paper can be downloaded.

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