Supplier log in
Feasibility of Biomass Carbon Modelling
Details
|
Tender Closed
|
|
| RFx ID : | 29168977 |
| Tender Name : | Feasibility of Biomass Carbon Modelling |
| Reference # : |
C - C0036655
|
| Open Date : | Thursday, 11 April 2024 4:30 PM (Pacific/Auckland UTC+12:00) |
| Close Date : | Friday, 10 May 2024 2:00 PM (Pacific/Auckland UTC+12:00) |
| Department/Business Unit : | Te Uru Rakau - Forestry NZ |
| Tender Type : | Request for Proposals (RFP) |
| Tender Coverage : | Sole Agency [?] |
| Categories : |
|
| Regions: |
|
| Exemption Reason : | None |
| Required Pre-qualifications : | None |
| Contact : |
Michiel Cumming |
| Alternate Physical Delivery Address : | |
| Alternate Physical Fax Number : | |
| Agency Address : | NEW ZEALAND |
A key focus for the Maximising Forest Carbon (MFC) Programme is looking to explore the potential use of remote sensing technology to measure forest carbon, with the objective to identify and introduce improved methods for measuring forest carbon at local and national scales that are more cost effective for the forest owner and regulator.
An initial piece of research reviewed existing technology that could be utilised for forest carbon accounting, and a primary finding was both the extensive use of remote sensing technology (LiDAR in particular) in forest management and inventory, and its potential use for carbon accounting. Following the results and recommendations of a recent pilot study, LiDAR remote sensing was shown to be a promising tool for generating carbon estimates using a ‘whole-of-forest’ methodology, but further research is needed to explore remote sensing capture for biomass data and understand the requirements for data processing and volumetric modelling this approach would require.
This opportunity is a feasibility study to understand the requirements needed to take classified point-cloud (.las) data through to volumetric modelling to produce a biomass-based carbon estimate. MPI wishes to gain an understanding of the capabilities of existing data and, building on earlier work delivered, utilise collected LiDAR point clouds to determine the feasibility of single model for data processing and biomass-based carbon estimates.
No Winner This tender closed with no responses
