¶ Hyperspectral imaging
| Company | Airborne Logic |
| Country | Australia |
| Website | https://airbornelogic.com.au/ |
| Category | Planning & Inventory › Remote sensing & mapping |
¶ Overview
Hyperspectral imaging is a remote sensing technology that captures image data across a continuous and densely sampled range of the electromagnetic spectrum — typically spanning visible, near-infrared (NIR), and shortwave infrared (SWIR) wavelengths — enabling the identification and quantification of materials, biological states, and chemical properties that are invisible to conventional RGB or multispectral cameras. Unlike multispectral sensors that collect data in a small number of discrete broad spectral bands, hyperspectral sensors acquire hundreds of contiguous narrow bands, producing a three-dimensional data cube (two spatial dimensions and one spectral dimension) that can be analysed to identify specific spectral signatures associated with particular tree species, leaf chemistry, wood properties, disease states, or stress responses. In forestry applications, hyperspectral imaging deployed on aircraft or unmanned aerial vehicles (UAVs) is used for forest inventory, species classification, detection of pest and disease outbreaks (such as Phytophthora cinnamomi root rot or myrtle rust in Australian forests), assessment of bark beetle damage, and estimation of forest biophysical parameters including leaf area index, chlorophyll content, and water stress. Australian research institutions including the Australian National University, University of Tasmania, and CSIRO have applied airborne hyperspectral data to map native forest composition and condition across large areas of conservation and production forest. Hyperspectral imaging also has significant applications in timber processing facilities, where line-scan hyperspectral cameras on conveyor systems can rapidly assess log and board quality, detect knots, grain angle, moisture distribution, and surface defects, enabling automated sorting and grading decisions. The primary challenges associated with hyperspectral imaging include the large data volumes generated, the computational demands of processing hyperspectral cubes, the need for rigorous atmospheric correction in airborne applications, and the relatively high cost of hyperspectral sensor hardware compared to standard imaging alternatives.
¶ Assessment
A strong option that enhances inventory accuracy and reduces risks by detecting health issues and structural hazards early, while avoiding dangerous fieldwork.
¶ Details
| Field | Value |
|---|---|
| Company | Airborne Logic |
| Country | Australia |
| Type | Company |
| FWPA RD&E | 7.3 |