Section (b.2) Data Sources

Data is retrieved through two primary sources: Remote Sensing (Satellite Observations) and Ground Data. These diverse datasets are then integrated into our Modelling processes to create ecosystem models.

Remote Sensing

Remote sensing involves gathering information about ecosystems from a distance using advanced technologies. Key remote sensing methods we utilize include:

• Lidar: Uses laser pulses to generate 3D models of landscapes, allowing precise measurement of vegetation height, canopy structure, and terrain.

• Radar: Penetrates cloud cover and dense vegetation to provide data on surface roughness, biomass, and soil moisture.

• Thermal: Captures temperature variations in ecosystems, essential for understanding heat stress in plants, water bodies, and animal activity.

• Optical: Collects images using visible and infra-red light, making it possible to monitor vegetation health, land cover changes, and other environmental features.

Ground Data

Ground data collection is optional and serves to validate and enhance the remote sensing data by providing detailed, site-specific insights. Key methods include:

• Field Sampling: Direct collection of data such as soil composition, plant health, and other ecological metrics to provide ground-level accuracy for models.

• Bioacoustics: Uses audio recordings of animal calls and natural sounds to monitor biodiversity and wildlife presence.

• eDNA: Environmental DNA sampling involves extracting genetic material from soil, water, or air to detect the presence of species in an area without direct observation.

• Camera Trapping: Motion-sensitive cameras capture images of wildlife, providing critical data on species presence, behavior, and population trends.