Bridging hole between distant sensing and tree modelling with knowledge science

Announced at the moment, a bunch of worldwide scientists from New Zealand and Singapore is collaborating on a three-year challenge, funded by MBIE, to make use of knowledge science and distant sensing to routinely mannequin and analyse tree species and their interactions with setting.

  • University of Canterbury Computer Science and Software Engineering Professor Richard Green

Announced at the moment, a bunch of worldwide scientists from New Zealand and Singapore is collaborating on a three-year challenge, funded by MBIE, to make use of knowledge science and distant sensing to routinely mannequin and analyse tree species and their interactions with setting.

Singapore, the ‘City in a Garden’, embodies the ‘green city’ idea with over 7 million city timber masking 700 km2. New Zealand, with 24% of its 270,000km2 land coated in forest, additionally actively helps and promotes city re-greening in lots of its cities.

Sustaining and enhancing biodiversity and wholesome residing environments are priorities for Singapore and New Zealand that require cautious administration of timber in city areas and forests. Reliable data, fashions, and evaluation of timber and their interplay with the encompassing setting are important to tell administration choices. However, these are presently restricted by the standard of obtainable knowledge, instruments, and methods.

Leveraging their joint experience in knowledge science, distant sensing, and 3D modelling, the researchers suggest a proof-of-concept built-in methodology.

According to key researcher and Co-PI, University of Canterbury Computer Science and Software Engineering Professor Richard Green, they’ll develop novel data-science strategies for extracting tree species data from petabytes of multiresolution remote-sensing knowledge to mannequin tree species and their interactions with the setting, and subsequently analyse their socio-economic impacts.

“This will include tree segmentation from remote sensing, with the objective to extract individual tree point cloud and tree information from both high- and low-resolution remote sensing data,” Professor Green says.

“We will also automate tree species recognition and species profiling based on learning from both high- and low-resolution remote sensing data. Among other things, this will give us automatic inference of species profiles​ and enable tree species classification.”

This work will kind the premise for future analysis collaborations to allow additional modelling, simulation, and evaluation. In the long run, our work will empower and inform decision-makers on timber and environmental issues for the higher good thing about each New Zealand and Singapore.

Under the Government-wide New Zealand-Singapore Enhanced Partnership, the Ministry of Business, Innovation & Employment (MBIE) has established a jointly-funded Data Science Research Programme with the Singapore Data Science Consortium (SDSC), on behalf of the National Research Foundation of Singapore. The profitable initiatives will assist result in the creation of recent and world-leading data and contribute to the overarching goal of accelerating the event of information science and future meals capabilities in each Singapore and New Zealand.

Eight initiatives have been chosen for New Zealand’s 2 joint analysis programmes with Singapore on Data Science and Future Foods. MBIE’s funding dedication for these initiatives totals virtually $23 million (excluding GST) over three years, and represents New Zealand’s largest ever single funding in a bilateral science programme.

Project crew:

  • Dr Jan Schindler (NZ Science Leader/PI) | Manaaki Whenua – Landcare Research, New Zealand)
  • Professor Richard Green (Co-PI) | University of Canterbury, New Zealand
  • Dr Alan Tan (Co-PI) | Scion, New Zealand
  • Dr Kourosh Neshatian (Key Individual) | University of Canterbury, New Zealand
  • Dr Oliver Batchelor (Key Individual) | University of Canterbury, New Zealand
  • Professor Mengjie Zhang (Key Individual) | Victoria University of Wellington, New Zealand
  • Dr Like Gobeawan (Singapore Principal Investigator (PI)) | Institute of High Performance Computing, A*STAR, Singapore
  • Associate Professor Lee Bu Sung (Key Researcher) | Nanyang Technological University, Singapore

/Public Release. The materials on this public launch comes from the originating group and could also be of a point-in-time nature, edited for readability, type and size. View in full here.

LEAVE A REPLY

Please enter your comment!
Please enter your name here