Citation: Valavi R, Levick SR, Lehmann EA, Liu N, Giljohann KM, Williams KJ, Collings S, Johnson S, Botha EJ, Munroe SEM, Van Niel TG, Newnham G, Paget M, Malley C, Carlile P, Gunawardana D, Lyon P, Richards AE, Tetreault Campbell S and Ferrier S (2025) HCAS 3.3 (1988-2024) base model estimate of habitat condition (90m grid), National Connectivity Index 2.0 (NCI) and annual time series for continental Australia. Data collection 65549. CSIRO, Canberra, Australia. DOI: https://data.csiro.au/collection/csiro:65549.The data collection utilises Geoscience Australia’s archive of Landsat Earth observation imagery over 37 years from 1988 to 2024, and comprises for continental Australia:• the 90 m gridded (Australian Albers projection, EPSG 3577, Geographic Datum of Australia 1994) HCAS v3.3 base model (1988-2024) estimation of habitat condition for terrestrial biodiversity• Annual epochs of habitat condition derived from 3-, 5- and 10-year rolling averages of remotely sensed ecosystem characteristics (condition variables) from 1990, 1992 and 1997 to 2024, respectively• model-based uncertainty quantification as 95% confidence interval limit estimates of Habitat Condition for the long-term epoch (1988-2024) and selected short-term epochs, applying the method developed by Lehmann et al. (2025)• classification of long- and short-term epochs of Habitat Condition into six modification levels based on experts’ best estimate of condition (Giljohann et al., 2024) for each category of the Vegetation Assets, States and Transitions (VAST) narrative framework (Thackway and Lesslie, 2006; 2008)• National Connectivity Index (NCI) v2.0 (Giljohann et al., 2022) for the long-term epochs and short-term epochs using the corresponding HCAS v3.3 epoch• long- and short-term epochs of Connectivity-adjusted Condition (NCIC) derived from the geometric mean of corresponding NCI and HCAS epochs• several other datasets to support use and interpretation of the long- and short-term epochs of HCAS and NCI products, and related derivatives, including reference sites and the input remotely sensed ecosystem characteristics (i.e. Condition Variables). HCAS v3.3 (production version 3) was derived using 'ClassicHCAS' software version 0.2.0 and 'HCAS-workflow' software version 1.2.1. The NCI and NCIC are developed by DCCEEW and included in the data collection along with other derivative products, for end user convenience. The NCI has been updated using HCAS v3.3 epochs. Raster datasets (*.tif) are Cloud Optimised GeoTIFFs at 90 m grid resolution, GDA 1994 (Australian Albers, EPSG:3577). HCAS v3.3 Habitat Condition indices vary continuously from a theoretical minimum of 0.0 (ecosystem integrity removed) to a maximum of 1.0 (ecosystem integrity in reference condition). NCI also ranges continuously from 0.0 (unconnected removed habitat) to a maximum of 1.0 (fully connected intact habitat), as does the NCIC: from 0.0 (landscape ecosystem integrity functionally extinguished) to a maximum of 1.0 (landscape ecosystem integrity functionally intact and in reference condition). Both the HCAS and NCIC represent the contribution that a given site (grid cell) makes to effective area of ecosystem integrity remaining within a spatial reporting unit, as a proportion of the contribution made by a site in reference condition. Data extent is defined by any data pixel intersecting a coastline polygon as defined by the land fraction dataset (Liu 2024). The data and no-data extent of each grid layer encompasses the area within the Australian Continental Exclusive Economic Zone (EEZ) (Alcock et al., 2020), excluding territories of Cocos, Christmas, Norfolk, Macquarie, Heard, and McDonald Islands, as well as Antarctica (Liu and Newnham, 2024). Data are described in "Habitat Condition Assessment System (HCAS) version 3.3: A guide to the 90-metre data collection. Technical report EP2025-2979" (available from CSIRO's publication repository, see related links).

Citation: Valavi R, Lehmann EA, Liu N, Levick S, Giljohann KM, Williams KJ, Johnson S, Botha EJ, Munroe SEM, Collings S, Searle R, Van Niel TG, Newnham G, Paget M, Joehnk K, Hosack GR, Harwood TD, Malley C, Gunawardana D, Sivanandam P, Richards AE, Tetreault Campbell S and Ferrier S (2025) HCAS 3.1 (1988-2022) base model estimate of habitat condition (90m grid) and National Connectivity Index (NCI) 2.0, annual epochs of HCAS from 1990 to 2022 for continental Australia with uncertainty. Updated data collection 63571. CSIRO, Canberra, Australia. DOI: https://data.csiro.au/collection/csiro:63571. This updated HCAS v3.1 data collection derives in part from Geoscience Australia’s archive of Landsat Earth observation Collection 3 Analysis Ready Data (Commonwealth of Australia, 2021) Derivative Products version 3.1.0 (Geoscience Australia, 2022) and version 3.0.0 (Lymburner, 2022) between 1988 and 2022, and comprises for continental Australia:• the 90 m gridded (Australian Albers projection, EPSG 3577, Geographic Datum of Australia 1994) Habitat Condition Assessment System version 3.1 (1988-2022) base model (HCAS v3.1) estimation of habitat condition for terrestrial biodiversity• 33 annual short-term epochs of HCAS from 1990 to 2022, formed using 3-year antecedent rolling averages of remotely sensed variables. • model-based uncertainty quantification as 95% confidence interval limits for the estimates of habitat condition for the long-term epoch (1988-2022) and selected short-term epochs (Lehmann et al., 2025)• a classification of long- and short-term epochs of habitat condition into six modification levels based on experts’ best estimate of condition for each category of the Vegetation Assets, States and Transitions (VAST) narrative framework (Thackway and Lesslie, 2006; 2008)• updated National Connectivity Index (NCI) v2.0 (Giljohann et al., 2022) for the long-term epoch using the HCAS v3.1 base model • long-term epoch of connectivity-adjusted condition (NCIC) derived from the geometric mean of the corresponding NCI and HCAS outputs (1988-2022)• several other datasets to support use and interpretation of the long- and short-term epochs of HCAS habitat condition products and derivatives, including reference sites and remote sensing inputs. The HCAS v3.1 short-term epochs derive from the base model. The NCI and NCIC are developed by DCCEEW and published in this HCAS data collection, for the convenience of end users. The majority are raster datasets in GeoTIFF format (*.tif) at 90 m grid resolution, Geographic Datum of Australia (GDA) 1994 (Australian Albers, EPSG:3577). All GeoTIFFs are provided as Cloud Optimised GeoTIFFs (COGs). In most cases, a corresponding *.png map image is also provided for quick views. Example summary tables by IBRA bioregions are also provided. The HCAS v3.1 base model and epoch habitat condition data varies continuously from a theoretical minimum of 0.0 (ecosystem integrity removed) to a maximum of 1.0 (ecosystem integrity in reference condition). The index represents the contribution that a given site (grid cell) makes to the effective area of ecosystem integrity remaining within any given spatial reporting unit, expressed as a proportion of the contribution made by a site in reference condition. Data extent is defined by any data pixel that intersected a coastline polygon as defined by the land fraction dataset (Liu 2024). The data and no-data extent of each grid layer encompasses the area within the Australian Continental Exclusive Economic Zone (EEZ) (Alcock et al., 2020), excluding territories of Cocos, Christmas, Norfolk, Macquarie, Heard, and McDonald Islands, as well as Antarctica (Liu and Newnham, 2024). Data are described in "Habitat Condition Assessment System (HCAS) version 3.1: A guide to the 90-metre data collection with uncertainty. Technical report EP2025-1549" (published in 2025, available from CSIRO's publication repository, see related links).

Please cite as follows: Valavi R, Williams KJ, Liu N, Levick S, Giljohann KM, Johnson S, Botha EJ, Munroe SEM, Lehmann EA, Collings S, Searle R, Van Niel TG, Newnham G, Paget M, Joehnk K, Hosack GR, Harwood TD, Malley C, Gunawardana D, Sivanandam P, Richards AE, Tetreault Campbell S and Ferrier S (2024) HCAS 3.1 (1988-2022) base model estimate of habitat condition (90 m grid), National Connectivity Index (NCI) 2.0, and 3-year average annually rolling epochs of habitat condition from 1990 to 2022 for continental Australia. Data collection 63571. CSIRO, Canberra, Australia. DOI: https://data.csiro.au/collection/csiro:63571. This data collection derives from Geoscience Australia’s archive of Landsat Earth observation imagery between 1988 and 2022, and comprises for continental Australia:• the 90 m gridded (Australian Albers projection, EPSG 3577, Geographic Datum of Australia 1994) Habitat Condition Assessment System (HCAS) version 3.1 (1988-2022) base model (HCAS v3.1) estimation of habitat condition for terrestrial biodiversity• updated National Connectivity Index (NCI) v2.0 (Giljohann et al., 2022) using the HCAS v3.1 base model, and • 3-year antecedent average rolling short-term epochs of HCAS from 1990 to 2022 and one experimental 5-year epoch ending 2022 for continental Australia• long-term epoch of connectivity-adjusted condition (NCIC) derived from the geometric mean of the corresponding NCI and HCAS. The HCAS v3.1 short-term epochs derive from the base model. The NCI long-term epoch uses the corresponding long-term HCAS v3.1 epoch as an input (production version 2). The NCI is developed by DCCEEW and included as one of the derivative products. The core collection in the HCAS v3.1 product suite comprises 34 datasets of habitat condition (the base model long-term epoch and 33 short-term epochs), and other input, derived and supporting datasets to inform use and interpretation, including the long-term epoch (1988-2022) of the NCI v2.0 and the derived connectivity-adjusted condition, NCIC. The majority are raster datasets in GeoTIFF format (*.tif) at 90 m grid resolution, Geographic Datum of Australia (GDA) 1994 (Australian Albers, EPSG:3577). All GeoTIFFs are provided as Cloud Optimised GeoTIFFs (COGs). In most cases, a corresponding *.png map image is also provided for quick views. Example summary tables by IBRA bioregions are also provided. The HCAS v3.1 base model and epoch datasets are habitat condition indices that vary continuously from a theoretical minimum of 0.0 (ecosystem integrity removed) to a maximum of 1.0 (ecosystem integrity in reference condition). The index represents the contribution that a given site (grid cell) makes to the effective area of ecosystem integrity remaining within any given spatial reporting unit, expressed as a proportion of the contribution made by a site in reference condition. The data extent of the curated collection is defined by any data pixel that intersected a coastline polygon, as defined by the land fraction dataset developed by Liu (2024). The data and no-data extent of each grid layer encompasses the area within the Australian Continental Exclusive Economic Zone (EEZ) (Alcock et al., 2020), excluding territories of Cocos, Christmas, Norfolk, Macquarie, Heard, and McDonald Islands, as well as Antarctica. This HCAS v3.1 product suite builds on the earlier HCAS v3.0 and substantially improves on, and extends, the former HCAS series 2 outputs. HCAS v3.1 uses 14 remotely sensed ecosystem characteristics derived from the Digital Earth Australia Surface Reflectance NBART Landsat Analysis Ready Data Collection 3 derivative products (Commonwealth of Australia, 2021). Data descriptions are summarised in the accompanying "Habitat Condition Assessment System (HCAS) version 3.1: A guide to the 90-metre data collection. Publication EP2024-5394" documentation, which can be downloaded separately from CSIRO's publication repository (see related links).

Please cite as follows: Valavi R, Williams KJ, Liu N, Levick S, Giljohann KM, Johnson S, Botha EJ, Munroe SEM, Lehmann EA, Collings S, Searle R, Van Niel TG, Newnham G, Paget M, Joehnk K, Hosack GR, Harwood TD, Malley C, Gunawardana D, Sivanandam P, Carlile P, Richards AE, Tetreault Campbell S, Schmidt RK and Ferrier S (2024) HCAS 3.0 (1988-2022) base model estimate of habitat condition (250m grid), National Connectivity Index (NCI) 2.0, 3-year average annually rolling epochs of HCAS and NCI from 1990 to 2022, trends and other derivatives for continental Australia. Data Collection 62484. CSIRO, Canberra, Australia. Landing page: https://data.csiro.au/collection/csiro:62484. This data collection comprises, for continental Australia, the 250m gridded Habitat Condition Assessment System (HCAS) version 3.0 (1988-2022) base model (HCAS v3.0) estimation of habitat condition for terrestrial biodiversity, updated National Connectivity Index (NCI) v2.0 using the HCAS v3.0 base model, 3-year antecedent average rolling short-term epochs of HCAS, NCI, connectivity-adjusted condition (NCIC) and Ecosystem Site Condition (ESC) from 1990 to 2022, trends and other derivatives for continental Australia. The HCAS v3.0 short-term epochs are derived from the base model, and the NCI, NCIC and ESC short-term epochs use the corresponding HCAS v3.0 epochs as an input (production version 3-2). Several other datasets support use and interpretation of the base model, epochs and trends. Spatial raster datasets are provided in GeoTIFF format (*.tif) at 250m grid resolution, Geographic Datum of Australia (GDA) 1994 (Australian Albers, EPSG:3577). The original data, in a grid of 0.0025 degrees of latitude and longitude (EPSG:4283, GDA 1994), was projected to Australian Albers. Continuous data were bilinearly resampled resulting in some smoothing across pixels. Therefore, the unprojected data (EPSG:4283) are also provided as an option available to users. All GeoTIFFs are provided as Cloud Optimised GeoTIFFs (COGs). COGs are regular GeoTIFF files with an internal organisation to enable HTTP GET range requests to ask for just the needed parts of a file. In most cases, a corresponding *.png map image is also provided for quick views. The HCAS v3.0 base model and epoch datasets are Habitat Condition indices that vary continuously from a theoretical minimum of 0.0 (ecosystem integrity removed) to a maximum of 1.0 (ecosystem integrity in reference condition). The same definition applies to Ecosystem Site Condition (ESC). The NCI also ranges continuously from 0.0 (unconnected removed habitat) to a maximum of 1.0 (fully connected intact habitat), as does the NCIC: from 0.0 (ecosystem integrity functionally extinguished) to a maximum of 1.0 (ecosystem integrity functionally connected and in reference condition). The data extent of the curated projected collection is defined by any data pixel that intersected a coastline polygon using the land fraction dataset developed by Liu (2024) and the extent of National Land use data (ABARES, 2024b). The data and no-data extent of each grid layer encompasses the area within the Australian Continental Exclusive Economic Zone (EEZ), excluding territories of Cocos, Christmas, Norfolk, Macquarie, Heard, and McDonald Islands, as well as Antarctica (Liu and Newnham, 2024). This HCAS v3.0 product suite substantially improves on and extends the former HCAS series 2 outputs. HCAS v3.0 uses 14 remotely sensed ecosystem characteristics derived from the Digital Earth Australia Surface Reflectance NBART Landsat Analysis Ready Data Collection 3 derivative products (Commonwealth of Australia, 2021). HCAS v3.1 supersedes HCAS v3.0. Data descriptions are summarised in the accompanying "Habitat Condition Assessment System version 3.0: A guide to the 250-metre data collection" documentation, which can be downloaded separately from CSIRO's publication repository (see related links).

Data from multibeam echosounder surveys taken as part of the Ningaloo Outlook project are classified into various seafloor cover types according to their hardness, rugosity and depth. The classifications are validated with towed video ground truth where it is available. Three AOIs are classified, two that were explicitly part of the Ningaloo Outlook Deep Reefs project and a third transect that was acquired incidentally while RV Investigator was transiting between locations. Due to the nature of the acquired data, two different approaches were taken for the classification, the first approach used multibeam backscatter angular response curves along with rugosity as input to a maximum likelihood classifier. The second approach used flattened multibeam backscatter (i.e. with the angular effects removed), along with rugosity as inputs to a Random Forest Classifier. Estimates of the accuracy of the classifiers are produced, where possible, along with area statistics for the different substratum observed in the classified maps. The maps are GeoTIFFs with text based classification keys. [Note:] 120m Transect only

Data from multibeam echosounder surveys taken as part of the Ningaloo Outlook project are classified into various seafloor cover types according to their hardness, rugosity and depth. The classifications are validated with towed video ground truth where it is available. Three AOIs are classified, two that were explicitly part of the Ningaloo Outlook Deep Reefs project and a third transect that was acquired incidentally while RV Investigator was transiting between locations. Due to the nature of the acquired data, two different approaches were taken for the classification, the first approach used multibeam backscatter angular response curves along with rugosity as input to a maximum likelihood classifier. The second approach used flattened multibeam backscatter (i.e. with the angular effects removed), along with rugosity as inputs to a Random Forest Classifier. Estimates of the accuracy of the classifiers are produced, where possible, along with area statistics for the different substratum observed in the classified maps. The maps are GeoTIFFs with text based classification keys. [Note:] Area 5 only

Data from multibeam echosounder surveys taken as part of the Ningaloo Outlook project are classified into various seafloor cover types according to their hardness, rugosity and depth. The classifications are validated with towed video ground truth where it is available. Three AOIs are classified, two that were explicitly part of the Ningaloo Outlook Deep Reefs project and a third transect that was acquired incidentally while RV Investigator was transiting between locations. Due to the nature of the acquired data, two different approaches were taken for the classification, the first approach used multibeam backscatter angular response curves along with rugosity as input to a maximum likelihood classifier. The second approach used flattened multibeam backscatter (i.e. with the angular effects removed), along with rugosity as inputs to a Random Forest Classifier. Estimates of the accuracy of the classifiers are produced, where possible, along with area statistics for the different substratum observed in the classified maps. The maps are GeoTIFFs with text based classification keys. [Note:] Area 3a only

The digital 3-dimenional (3D) mineral mapping suite of Queensland comprises ~20 “standardized” products at the spectral resolution of the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor and generated from publicly-available satellite, airborne, field and drill core spectral data spanning the visible near infrared (VNIR; 0.4 to 1.0 µm), shortwave infrared (SWIR; 1.0 to 2.5 µm) and thermal infrared (TIR; 7.5 to 12.0 µm) wavelength regions, including: 1. Satellite ASTER maps at both 30 m and 90 m pixel resolution with complete coverage of the state of Queensland, i.e. 1.853 million km²; 2. Airborne HyMap maps at ~5 m pixel resolution with a coverage of ~25,000 km2 from areas across north Queensland; 3. Field point samples (~300) from the National Geochemical Survey of Australia (NGSA) collected from a depth of 0-10 cm of flood overbank sediments; 4. Drill-core profiles (~20) of the National Virtual Core Library (NVCL) selected from the area around the Georgetown seismic line (07GA-IG2). Key to the processing of the remote sensing data-sets (ASTER and HyMap) was the implementation of unmixing methods to remove the effects dry and green vegetation. This unmixing was not applied to the Australian ASTER geoscience maps released in 2012 (called here Version 1 or V1) resulting in extensive areas with little/no mineral information because of the need to apply masks. The vegetation unmixing methods used in the Version 2 (V2) processing of the ASTER and HyMap imagery has resulted in very few areas without coherent mineral information. The resultant V2 “mineral group” products were designed to measure mineral information potentially useful for mapping: (i) primary rock composition; (ii) superimposed alteration effects; and (iii) regolith cover. These V2 products may assist in mapping soil properties and groundwater conditions. However their relatively low spectral resolution (based on ASTER’s 14 VNIR-SWIR-TIR bands) means that they do not provide the high level of mineralogical detail available from hyperspectral systems (>100 spectral bands), like HyMap and the HyLogger. Nevertheless, the relatively low spectral resolution of ASTER means that all other sensor data can be spectrally resampled to that resolution. Furthermore, the ASTER global data archive, which now spans entire Earth’s land surface <80degrees latitude, means that it can be used as global base-map for integrating all other spectral data.

The digital 3-dimenional (3D) mineral mapping suite of Queensland comprises ~20 “standardized” products at the spectral resolution of the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor and generated from publicly-available satellite, airborne, field and drill core spectral data spanning the visible near infrared (VNIR; 0.4 to 1.0 µm), shortwave infrared (SWIR; 1.0 to 2.5 µm) and thermal infrared (TIR; 7.5 to 12.0 µm) wavelength regions, including: 1.Satellite ASTER maps at both 30 m and 90 m pixel resolution with complete coverage of the state of Queensland, i.e. 1.853 million km²; 2.Airborne HyMap maps at ~5 m pixel resolution with a coverage of ~25,000 km2 from areas across north Queensland;3.Field point samples (~300) from the National Geochemical Survey of Australia (NGSA) collected from a depth of 0-10 cm of flood overbank sediments;4.Drill-core profiles (~20) of the National Virtual Core Library (NVCL) selected from the area around the Georgetown seismic line (07GA-IG2).Key to the processing of the remote sensing data-sets (ASTER and HyMap) was the implementation of unmixing methods to remove the effects dry and green vegetation. This unmixing was not applied to the Australian ASTER geoscience maps released in 2012 (called here Version 1 or V1) resulting in extensive areas with little/no mineral information because of the need to apply masks. The vegetation unmixing methods used in the Version 2 (V2) processing of the ASTER and HyMap imagery has resulted in very few areas without coherent mineral information. The resultant V2 “mineral group” products were designed to measure mineral information potentially useful for mapping: (i) primary rock composition; (ii) superimposed alteration effects; and (iii) regolith cover. These V2 products may assist in mapping soil properties and groundwater conditions. However their relatively low spectral resolution (based on ASTER’s 14 VNIR-SWIR-TIR bands) means that they do not provide the high level of mineralogical detail available from hyperspectral systems (>100 spectral bands), like HyMap and the HyLogger. Nevertheless, the relatively low spectral resolution of ASTER means that all other sensor data can be spectrally resampled to that resolution. Furthermore, the ASTER global data archive, which now spans entire Earth’s land surface <80degrees latitude, means that it can be used as global base-map for integrating all other spectral data.

The digital 3-dimenional (3D) mineral mapping suite of Queensland comprises ~20 “standardized” products at the spectral resolution of the ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) sensor and generated from publicly-available satellite, airborne, field and drill core spectral data spanning the visible near infrared (VNIR; 0.4 to 1.0 µm), shortwave infrared (SWIR; 1.0 to 2.5 µm) and thermal infrared (TIR; 7.5 to 12.0 µm) wavelength regions, including: 1.Satellite ASTER maps at both 30 m and 90 m pixel resolution with complete coverage of the state of Queensland, i.e. 1.853 million km²; 2.Airborne HyMap maps at ~5 m pixel resolution with a coverage of ~25,000 km2 from areas across north Queensland;3.Field point samples (~300) from the National Geochemical Survey of Australia (NGSA) collected from a depth of 0-10 cm of flood overbank sediments;4.Drill-core profiles (~20) of the National Virtual Core Library (NVCL) selected from the area around the Georgetown seismic line (07GA-IG2).Key to the processing of the remote sensing data-sets (ASTER and HyMap) was the implementation of unmixing methods to remove the effects dry and green vegetation. This unmixing was not applied to the Australian ASTER geoscience maps released in 2012 (called here Version 1 or V1) resulting in extensive areas with little/no mineral information because of the need to apply masks. The vegetation unmixing methods used in the Version 2 (V2) processing of the ASTER and HyMap imagery has resulted in very few areas without coherent mineral information. The resultant V2 “mineral group” products were designed to measure mineral information potentially useful for mapping: (i) primary rock composition; (ii) superimposed alteration effects; and (iii) regolith cover. These V2 products may assist in mapping soil properties and groundwater conditions. However their relatively low spectral resolution (based on ASTER’s 14 VNIR-SWIR-TIR bands) means that they do not provide the high level of mineralogical detail available from hyperspectral systems (>100 spectral bands), like HyMap and the HyLogger. Nevertheless, the relatively low spectral resolution of ASTER means that all other sensor data can be spectrally resampled to that resolution. Furthermore, the ASTER global data archive, which now spans entire Earth’s land surface <80degrees latitude, means that it can be used as global base-map for integrating all other spectral data.