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1. Overview
The Eyes on Australian Forests project aims to provide a robust tool for the ingestion, visualisation and analysis of multispectral space-based imagery. It facilitates the extraction of valuable vegetation health metrics from publicly available APIs, enabling standardised products and information metrics such as the Normalised Difference Vegetation Index (NDVI), Normalised Difference Moisture Index (NDMI) and Normalised Burn Ratio (NBR). By ingesting data from multiple satellite sources, this tool reduces spatial and temporal gaps in forest imagery coverage nationwide and allows for cross-calibration between sensors.
The repository provides tools for analysing imagery, underpinned by spatial datasets delineating the forests of Australia and differentiating between natural bushland, plantation and commercial forestry, and other forest types. The information derived from the Earth Observation datasets would enable many avenues of forest wellbeing to be explored, such as: the spatial variation of forest health; the quantitative impacts of forest management practices; and identification of regions where stress due to climate induced rainfall reduction or human-impact induced groundwater level change has impacted water availability.
The project initially focuses on incorporating data from:
- Landsat 8-9 (Digital Earth Australia)
- Sentinel-2 (Digital Earth Australia)
- VIIRS (AppEEARS)
Future phases will explore additional sources such as ASTER, EnMAP, MODIS, PROBA-V, and ECOSTRESS aboard the International Space Station. The choice of Landsat, Sentinel 2 and VIIRS is based on their higher temporal and spatial resolution, enabling more detailed analysis.
Please note the following regarding satellite data providers:
Digital Earth Australia (DEA) offers satellite data access via the NCI THREDDS server and AWS S3 bucket without requiring authentication. However, it's important to be aware that DEA's data access policies may change in the future, potentially transitioning to a requestor pays model. Users should stay informed about any updates or changes to DEA's data access policies and terms of use.
AppEEARS provides satellite data access through NASA Earth Data login credentials. Data retrieval is facilitated through a task-queue system. Users are required to have a NASA Earth Data account to access AppEEARS data. Please note that data access processes and policies may vary, and users should review AppEEARS' terms of use for more information.
The Normalised Difference Vegetation Index (NDVI) is a widely used vegetation index that measures the amount and vigor of green vegetation in an area. It is calculated from the ratio of the difference between near-infrared (NIR) and red light to the sum of these wavelengths.
Relevance: NDVI is a key indicator of vegetation health and productivity. High NDVI values typically indicate dense, healthy vegetation, while low values may indicate sparse vegetation or areas affected by stressors such as drought, disease, or human activities. NDVI is used in agriculture, forestry, ecology, and environmental monitoring to assess vegetation dynamics, detect changes over time, and monitor the impact of environmental factors on vegetation health.
The Normalised Difference Moisture Index (NDMI) is a vegetation index that measures the moisture content or water availability of vegetation. It is calculated from the ratio of the difference between near-infrared (NIR) and shortwave infrared (SWIR) wavelengths to their sum.
Relevance: NDMI is particularly useful for assessing vegetation moisture content and detecting areas prone to drought stress or water scarcity. High NDMI values indicate moist or water-rich vegetation, while low values suggest dry or water-stressed vegetation. NDMI is used in agriculture, hydrology, and ecology to monitor drought conditions, assess water stress in crops and forests, and evaluate land surface moisture dynamics.
The Normalised Burn Ratio (NBR) is a vegetation index used to detect and assess the severity of fire-affected areas. It is calculated from the ratio of the difference between near-infrared (NIR) and shortwave infrared (SWIR) wavelengths to their sum.
Relevance: NBR is valuable for mapping and quantifying the extent and severity of fire-affected areas in landscapes. Positive NBR values typically indicate unburned or healthy vegetation, while negative values suggest burned or fire-affected areas. The magnitude of NBR values correlates with the severity of fire damage, with higher negative values indicating more severe burning. NBR is used in fire management, ecology, and land management to assess fire impacts, plan recovery efforts, and monitor vegetation regeneration after wildfires.