Max Planck Gesellschaft

Olee Hoi Ying Lam

Research scientist at the Functional Biogeography research group
room: C1.024
phone: +49 3641 57 6298
email: hlam(at)bgc-jena.mpg.de

Research Interests | Projects | Background | Publications | Conferences and Workshops


Research Interests

I am particularly interested in topics with remote sensing which can provide non-invasive observations in the agricultural and conservation domains. As a recent computer science graduate, I am also interested in data analysis and imaging techniques for early-detection and decision support systems, as well as workflow development for environmental monitoring and precision agricultural applications.

At the MPI-BGC, I am currently developing my skills and knowledge in plant physiology and biochemistry so that I could further contribute and explore different methodologies in the area of nature conservation and sustainable use of natural resources.

  • remote sensing
  • machine learning and deep learning
  • site-specific management
  • early-detection and decision support system
  • nature conservation and precision agriculture

Projects

Current Project

  • Contributing to the development of an R package for the TRY database

Previous Projects

  • Development of an open-source workflow for weed species identification using airborne imagery in the Dutch-German cooperation project SPECTORS (funded by INTERREG V-A Deutschland-Nederland)

Background:

currently

Research scientist at the research group Functional Biogeography at the Max Planck Institute for Biogeochemistry, Jena, Germany

2017 - 2020

Reseach assistant at the Dutch-German cooperation project SPECTORS (funded by INTERREG V-A Deutschland-Nederland) at the Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany

2020

Master's thesis "An open source workflow for weed mapping in native grassland using unmanned aerial vehicle: using Rumex obtusifolius as a case study" in the Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany

2016 - 2020

Studies in Information Engineering and Computer Science at the Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany

2016

Bachelor's thesis "Radar signal distortion caused by directional vibration of a 24 GHz FMCW system" at the IMST GmbH, Kamp-Lintfort, Germany

2015 - 2016

Student Intern at the IMST GmbH, Kamp-Lintfort, Germany

2015

Research assistant at the Rhine-Waal University of Applied Sciences, Kamp-Lintfort, Germany

2013 - 2014

Student worker at the German Aerospace Center, Oberpfaffenhofen, Germany

2012 - 2016

Studies in Communication and Information Engineering at the Rhine-Waal University of Applied Science, Kamp-Lintfort, Germany

2008 - 2012

Studies in Law and Business at the Hong Kong Shue Yan University, Hong Kong


Publications

Lam, O. H. Y., Dogotari, M., Prüm, M., Vithlani, H. N., Roers, C., Melville, B., Zimmer, F., & Becker, R. (2020). An open source workflow for weed mapping in native grassland using unmanned aerial vehicle: using Rumex obtusifolius as a case study. European Journal of Remote Sensing. doi: 10.1080/22797254.2020.1793687.

Vithlani, H. N., Dogotari, M., Lam, O. H. Y., Prüm, M., Melville, B., Zimmer, F., & Becker, R. (2020). Scale Drone Mapping on K8S: Auto-scale Drone Imagery Processing on Kubernetes-orchestrated On-premise Cloud-computing Platform. 6th International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM). doi: 10.5220/0009816003180325.

Lam, O. H. Y., Dogotari, M., Prüm, M., Vithlani, H. N., Roers, C., Melville, B., Becker, R., & Zimmer, F. (2019). Mapping invasive Rumex obtusifolius in grassland using unmanned aerial vehicle [Abstract]. Proceedings, 30(1), pp. 34. doi: 10.3390/proceedings2019030034.

Prüm, M., Dogotari, M., Melville, B., Lam, O. H. Y., & Becker, R. (2019). A Hyperspectral Imaging System for UAV Based Agricultural Remote Sensing in the VIS-SWIR Range [Abstract]. 10th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS).

Dogotari, M., Prüm, M., Lam, O. H. Y., Vithlani, H. N., Vu, V. H., Melville, B., & Becker, R. (2019). Development of a UAV-Borne LiDAR System for Surveying Applications [Abstract]. Proceedings, 30(1), pp. 75. doi: 10.3390/proceedings2019030075.

Vithlani, H. N., Dogotari, M., Melville, B., Prüm, M., Lam, O. H. Y., Becker, R., & Zimmer, F. (2019). Applicability of Remote Sensing Workflow in Kubernetes-Managed On-premise Cluster Environment [Abstract]. Proceedings, 30(1), pp. 38. doi: 10.3390/proceedings2019030038.

Lam, O. H. Y., Dogotari, M., Prüm, M., Vithlani, H. N., Roers, C., Melville, B., Becker, R., & Zimmer, F. (2019). Mapping of Rumex obtusifolius in Native Grassland using Unmanned Aerial Vehicle: From Object-based Image Analysis to Deep Learning [Abstract]. 39th Annual EARSeL Symposium (EARSeL). [Online] Available at: http://symposium.earsel.org/39th-symposium-Salzburg/wp-content/uploads/2019/07/EARSeL-2019-Book-of-Abstracts-Print.pdf

Lam, O. H. Y., Melville, B., Dogotari, M., Prüm, M., Roers, C., Becker, R., & Zimmer, F. (2018). Detection of invasive weed species in grasslands using UAV RGB-imagery [Abstract]. 3rd Unmanned Aircraft Systems for Remote Sensing (UAS4RS).

Kabiito, B., Melville, B., Lam, O. H. Y., Dogotari, M., & Becker, R. (2018). Remote Sensing for Localized Food Tree Mapping in Central Uganda: A Basis for Biodiversity Conservation [Abstract]. 3rd Unmanned Aircraft Systems for Remote Sensing (UAS4RS).

Lam, O. H. Y., Kulke, R., Hagelen, M., & Mollenbeck, G. (2016). Classification of moving targets using mirco-Doppler radar. 2016 17th International Radar Symposium (IRS). doi: 10.1109/irs.2016.7497317.


Conferences and Workshops

2019

THE Port Humanitarian Hackathon 2019 at CERN
Participant in Team Pier47

  • Setup platform for media outrearch, including Beacon and WiFi access point using Raspberry Pi
  • Researched in existing food databases
  • Provided insights in image recognition

2019

TERRAenVISION 2019 Conference at Barcelona
Oral Presentation – Abstract (Presented by co-author: R. Becker)

  • Topic: Mapping invasive Rumex obtusifolius in grassland using unmanned aerial vehicle

2019

39th Annual EARSeL Symposium at Salzburg
Oral Presentation – Abstract

  • Topic: Mapping of Rumex obtusifolius in Native Grassland using Unmanned Aerial Vehicle: From Object-based Image Analysis to Deep Learning

2018

UAS4RS 2018 Conference at Melbourne
Poster Presentation – Abstract

  • Topic: Detection of invasive weed species in grasslands using UAV RGB-imagery

2016

17th International Radar Symposium at Krakow
Oral Presentation – Paper (Presented by co-author: R. Kulke)

  • Topic: Classification of moving targets using mirco-Doppler radar
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