QUT Research Data Respository Dataset and Resources

The Digital Elevation Model (DEM) 5 Metre Grid of Australia derived from LiDAR model represents a National 5 metre (bare earth) DEM which has been derived from some 236 individual LiDAR surveys between 2001 and 2015 covering an area in excess of 245,000 square kilometres. These surveys cover Australia's populated coastal zone; floodplain surveys within the Murray Darling Basin, and individual surveys of major and minor population centres. All available 1 metre resolution LiDAR-derived DEMs have been compiled and resampled to 5 metre resolution datasets for each survey area, and then merged into a single dataset for each State. These State datasets have also been merged into a 1 second resolution national dataset.

The acquisition of the individual LiDAR surveys and derivation of the 5m product has been part of a long-term collaboration between Geoscience Australia, the Cooperative Research Centre for Spatial Information (CRCSI), the Departments of Climate Change and Environment, State and Territory jurisdictions, Local Government and the Murray Darling Basin Authority under the auspices of the National Elevation Data Framework and Coastal and Urban DEM Program, with additional data supplied by the Australian Department of Defence. The source datasets have been captured to standards that are generally consistent with the Australian ICSM LiDAR Acquisition Specifications with require a fundamental vertical accuracy of at least 0.30m (95% confidence) and horizontal accuracy of at least 0.80m (95% confidence).

LiDAR_Point_Clouds, Classified. AHD have been preocessed to conform to the Australian Height Datum and converted from files collected as swaths in to tiles of data. The file formats is LAS.

LAS is an industry format created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water

Lineage: Fugro Spatial Solutions (FSS) were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu National Park. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

Images of DOT bathymetric composite surfaces (LIDAR, multibeam and Laser) with colour ramp and hill shading applied. This polygon feature class represents the extents of the composite surface surveys created from all multibeam, laser and lidar surveys loaded into the Bathymetric Information System managed by Coastal Information Branch, DoT, Fremantle. This feature class also contains URLs to the Composite Surface 32 bit tif files stored on Amazon S3 for public download. The images are 5m and are as follows.

RPS Group were awarded a contract by CO2CRC (Geoscience Australia) to carry out a Aerial LiDAR survey over the Nirranda South region of the Victorian Coast. The data will be used for the CO2CRC Otway project which will demonstrate that carbon capture and storage is a technically and environmentally safe way to reduce Australia's greenhouse gas emissions.

This dataset is a collection of drone lidar data from plots across Australia (AusPlots, SuperSites, Cal/Val sites to be established in the future). The aim of these drone surveys is to capture vegetation structure. The standardised data collection and data processing protocols developed in 2022 are based on the DJI Matrice 300 (M300) RTK drone platform. Lidar sensor DJI Zenmuse L1 is used with DJI Matrice 300 (M300) RTK platform to capture RGB colourised 3D point clouds. The data is georeferenced using the onboard GNSS in M300 and the D-RTK 2 base station. DJI Terra software was used to generate 3D point clouds from the raw lidar data. The protocols include flight planning and data collection guidelines for a 100 x 100 m TERN plot, and the processing workflow used on DJI Terra. Mission-specific metadata for each plot is provided in the imagery/metadata folder (please refer to the imagery collection). The Drone Data Collection and Lidar Processing protocols can be found at https://www.tern.org.au/field-survey-apps-and-protocols/ .

LiDAR_Point_Clouds, Classified. ELL have been preocessed to from swaths in to tiles of data. Points are located by Elevation, Latitude and Longitude. The file formats is LAS.

LAS is an industry format created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water

Lineage: LIDAR Survey of the floodplains within Kakadu National Park conducted by Fugro Spatial Solutions for Geoscience Australia Fugro Spatial Solutions were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

Bathymetric (depth) information were sourced from the NSW statewide marine lidar bathymetry data collected in 2018 and multibeam echosounder surveys conducted by the NSW Department of Planning and Environment since 2005. Data were mosaicked in ArcGIS 10.8, with the marine lidar data superseding the multibeam data where overlaps occurred. This dataset will be updated as new surveys are conducted. \r \r Please refer to the ‘NSW Marine LiDAR Topo-Bathy 2018 Geotif’ (https://datasets.seed.nsw.gov.au/dataset/marine-lidar-topo-bathy-2018) and ‘HABMAP Multi-beam Survey Coverage Areas’ (https://datasets.seed.nsw.gov.au/dataset/habmap-multi-beam-survey-coverage-areasd74ae) records on SEED for further information on the data sources.

Model key points are statistically thinned data points that represent the main changes in a sampled surface. The Key Points are classified with code 8 in the LiDAR point classification scheme. Advantages in their use are significant reductions in data volume and reductions in data noise. There are disadvantages in using this data as has been a loss small features which may be potentially significant for certain applications. eg hydrology Lineage: Fugro Spatial Solutions (FSS) were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu National Park. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

This dataset is a footprint of the current available LiDAR data over for the State of Queensland compiled from numerous LiDAR projects captured on or after the year 2008.

LiDAR_Point_Clouds, UNClassified. ELL Files swaths of flight collected data. Points are located by Elevation, Latitude and Longitude. The file formats is LAS.

LAS is an industry format created and maintained by the American Society for Photogrammetry and Remote Sensing (ASPRS). LAS is a published standard file format for the interchange of lidar data. It maintains specific information related to lidar data. It is a way for vendors and clients to interchange data and maintain all information specific to that data. Each LAS file contains metadata of the lidar survey in a header block followed by individual records for each laser pulse recorded. The header portion of each LAS file holds attribute information on the lidar survey itself: data extents, flight date, flight time, number of point records, number of points by return, any applied data offset, and any applied scale factor. The following lidar point attributes are maintained for each laser pulse of a LAS file: x,y,z location information, GPS time stamp, intensity, return number, number of returns, point classification values, scan angle, additional RGB values, scan direction, edge of flight line, user data, point source ID and waveform information. Each and every lidar point in a LAS file can have a classification code set for it. Classifying lidar data allows you to organize mass points into specific data classes while still maintaining them as a whole data collection in LAS files. Typically, these classification codes represent the type of object that has reflected the laser pulse. Point classification is usually completed by data vendors using semi-automated techniques on the point cloud to assign the feature type associated with each point. Lidar points can be classified into a number of categories including bare earth or ground, top of canopy, and water. The different classes are defined using numeric integer codes in the LAS files. The following table contains the LAS classification codes as defined in the LAS 1.1 standard: Class code Classification type 0 Never classified 1 Unassigned 2 Ground 3 Low vegetation 4 Medium vegetation 5 High vegetation 6 Building 7 Noise 8 Model key 9 Water

Lineage: LIDAR Survey of the floodplains within Kakadu National Park conducted by Fugro Spatial Solutions for Geoscience Australia Fugro Spatial Solutions were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

In 2011 AAM was commissioned by the Commonwealth to fly an airborne laser scanning survey (LiDAR) of Christmas Island. The survey was carried out using a fixed wing aircraft between the 24th and 26th of August 2011. All data was captured within approximately 2 hours of low tide. During this period tides ranged from 0.5m to 1.2m. AAM classified the raw LiDAR points into the following classes using a single algorithm across the project area: 0 Unclassified - Created, never classified 1 Default - Unclassified 2 Ground - Bare ground 3 Low vegetation - 0 – 0.3m (essentially sensor 'noise') 4 Medium vegetation - 0.3 – 2m 5 High vegetation - 2m > 6 Buildings, structures - Buildings, houses, sheds, silos etc. 7 Low / high points - Spurious high/low point returns (unusable) 8 Model key points - Reserved for ‘model key points’ only 9 Water - Any point in water 10 Bridge - Any bridge or overpass 11 not used - Reserved for future definition 12 Overlap points - Flight line overlap points The raw LiDAR points in the .las format were provided to Geoscience Australia along with 1km ESRI grid tiles generated by interpolation from the points. The tiles were then joined to create a DEM (TIFF) that covers the full extent of Christmas Island. Each cell, 1m x 1m, in the grid contains the height in metres of the ground surface. As a guide, the DEM data is vertically accurate to 15cm and horizontally accurate to 30cm. Manual checking and editing was carried out by AAM to improve accuracy. Positional accuracy has been checked by Geoscience Australia and was found to match the ground surface well. The DEM data is complete for the full extent of Christmas Island. Disclaimer

Cocos Island - DEM - 2011 In 2011 AAM was commissioned by the Commonwealth to fly an airborne laser scanning survey of Cocos (Keeling) Islands. The survey was carried out using a fixed wing aircraft between the 8th and 16th of August 2011 and covers the whole of the Cocos (Keeling) Islands. All data was captured within approximately 2 hours of low tide. During this period tides ranged from 0.4m to 1.3m. AAM classified the raw LiDAR points into ground and non-ground points using a single algorithm across the project area. The raw LiDAR points in the .las format were provided to Geoscience Australia along with 1km by 1km ESRI grid tiles generated by interpolation from the points. The tiles were then joined to create a DEM (TIFF) that covers the full extent of the Cocos (Keeling) Islands. Each cell, 1m x 1m, in the grid contains the height in metres of the ground surface. As a guide, the DEM data is vertically accurate to 15cm and horizontally accurate to 30cm. A control survey was carried out by Whelans. Manual checking and editing was carried out by AAM to improve accuracy. Positional accuracy has been checked by Geoscience Australia and was found to match the ground surface well. The DEM grid file was generated in GDA94 and has been converted to UTM WGS 84 zone 47s to fit the rest of the Cocos GIS data. Vertical data was collected in the Cocos Keeling Island Height Datum (CKIHD). Disclaimer

These gully mapping datasets were developed using an algorithm that exploits the topographic signature of gullies to map them across multiple scales. It uses high-resolution (~1 m) airborne LiDAR topography data to map gullies and areas susceptible to gully erosion. The LiDAR datasets used were collected as part of the Reef Trust Gully and Stream Bank Erosion Control Program and cover ~7 000 square kilometres of Great Barrier Reef catchments. For each catchment with suitable data two independent datasets (existing gullies and areas at risk of gullying) are available. These two independent datasets enable comparison between current and future potential gully erosion that may help to prioritise gully remediation works. The data format is GeoTIFF, compatible with most GIS software. Lineage: The input topography data was captured as part of the Reef Trust 3D Terrain Mapping Services project. The data are available on the Elvis - Elevation and Depth - Foundation Spatial Data data portal (including metadata for the LiDAR products used).

Processing of the data was done using the algorithm described in Walker et al. 2020 (https://doi.org/10.1016/j.geomorph.2020.107115).

Companies in the Surveying and Mapping Services industry have struggled with volatile downstream demand over the past few years. Demand for surveying services fluctuates in response to construction activity, as surveyors are a necessity for construction projects. Although demand for surveying services has risen in areas like heavy and civil engineering construction, as well as exploration, these gains haven’t been enough to counterbalance a drop in demand from residential building construction. Slow growth in the number of surveyors has constrained the market’s size, as more experienced surveyors are retiring while fewer young people are interested in pursuing surveying as a career. Overall, revenue is expected to have contracted at an annualised 3.9% over the five years through 2024-25 to $4.0 billion, including an anticipated plummet of 7.1% in 2024-25. Technological advancements in surveying and mapping services have influenced the industry’s performance. Cost-effective drone surveying technology with fast processing speeds has allowed some companies to provide value-added products that appeal to time-sensitive clients. However, some downstream clients with large capital resources have bypassed third-party surveying service providers, even though they can offer specialised services, and developed in-house surveying capabilities for cost efficiency, limiting surveyors’ pricing ability. Some large-scale surveyors have capitalised on a flurry of high-profile projects to build stronger reputations and expand their market share. Over the coming years, a recovery in key downstream sectors, including residential housing construction, as interest rates ease will improve the industry’s performance. As softening interest rates improve downstream conditions, surveyors working in construction markets will be in a better position to capitalise on improved downstream conditions. Investment in apartment and townhouse construction will also rally, driven by government efforts to solve housing supply shortages over the coming years. Industry revenue is projected to climb at an annualised 2.2% over the five years through 2029-30 to $4.1 billion.

Canopy Height Model (CHM) 2 metre ESRI Grid Float format as 4944 tiles

Lineage: LIDAR Survey of the floodplains within Kakadu National Park conducted by Fugro Spatial Solutions for Geoscience Australia Fugro Spatial Solutions were awarded a contract by Geoscience Australia to carry out an Aerial LiDAR Survey over the Kakadu. The data will be used to examine the potential impacts of climate change and sea level rise on the West Alligator, South Alligator, East Alligator River systems and other minor areas. The project area was flight planned using parameters as specified. A FSS aircraft and aircrew were mobilised to site and the project area was captured using a Leica ALS60 system positioned using a DGPS base-station at Darwin airport. The Darwin base-station was positioned by DGPS observations from local control stations. A ground control survey was carried out by FSS surveyors to determine ground positions and heights for control and check points throughout the area. All data was returned to FSS office in Perth and processed. The deliverable datasets were generated and supplied to Geoscience Australia with this metadata information.

NEDF Metadata Acquisition Start Date: Saturday, 22 October 2011 Acquisition End Date: Wednesday, 16 November 2011 Sensor: LiDAR Device Name: Leica ALS60 (S/N: 6145) Flying Height (AGL): 1409 INS/IMU Used: uIRS-56024477 Number of Runs: 468 Number of Cross Runs: 28 Swath Width: 997 Flight Direction: Non-Cardinal Swath (side) Overlap: 20 Horizontal Datum: GDA94 Vertical Datum: AHD71 Map Projection: MGA53 Description of Aerotriangulation Process Used: Not Applicable Description of Rectification Process Used: Not Applicable Spatial Accuracy Horizontal: 0.8 Spatial Accuracy Vertical: 0.3 Average Point Spacing (per/sqm): 2 Laser Return Types: 4 pulses (1st 2nd 3rd 4th and intensity) Data Thinning: None Laser Footprint Size: 0.32 Calibration certification (Manufacturer/Cert. Company): Leica Limitations of the Data: To project specification Surface Type: Various Product Type: Other Classification Type: C0 Grid Resolution: 2 Distribution Format: Other Processing/Derivation Lineage: Capture, Geodetic Validation WMS: Not Applicable?

LiDAR (Light Detection And Ranging) is an increasingly popular remote sensing technology that uses light in the form of a pulsed laser (typically from an aircraft) to measure 'ranges', thereby being able to accurately calculate distances and elevations in a 3D environment. Landgate commissioned a LiDAR capture over the 'built up' areas of the Perth metropolitan area between the summer of 2021 and autumn of 2022. This supplements previous captures undertaken in recent years in the more remote regions - usually in support of state and local government initiatives. As the State's custodian of elevation data, Landgate makes its Capture WA funded LiDAR acquisitions available for use by state & local governments and industry. Additional information is available on the Landgate website. © Western Australian Land Information Authority (Landgate). Use of Landgate data is subject to Personal Use License terms and conditions unless otherwise authorised under approved License terms and conditions.

In June 2017, AAM completed field and aerial surveys over ~8,000 sqkm to generate orthoimagery and high definition level 1 classified LiDAR data to GA’s specifications. Under GA Deed CMC G3298A Contract D2017-43573 - Kimberley East. LiDAR and Imagery was captured over the site in separate flights between the 9th and 17th June 2017, a small gap was captured 9th July, the LiDAR and imagery have been controlled by 30 new control points This data supplied in this delivery is the Level 1 Classified las v1.4 dataset in 2km tiles. The height datum is Ellipsoidal.

This compilation data release is a selection of remotely sensed imagery used in the Exploring for the Future (EFTF) East Kimberley Groundwater Project. Datasets include: • Mosaic 5 m digital elevation model (DEM) with shaded relief • Normalised Difference Vegetation Index (NDVI) percentiles • Tasselled Cap exceedance summaries • Normalised Difference Moisture Index (NDMI) • Normalised Difference Wetness Index (NDWI)

The 5m spatial resolution digital elevation model with associated shaded relief image were derived from the East Kimberley 2017 LiDAR survey (Geoscience Australia, 2019b).

The Normalised Difference Vegetation Index (NDVI) percentiles include 20th, 50th, and 80th for dry seasons (April to October) 1987 to 2018 and were derived from the Landsat 5,7 and 8 data stored in Digital Earth Australia (see Geoscience Australia, 2019a). Tasselled Cap Exceedance Summary include brightness, greenness and wetness as a composite image and were also derived from the Landsat data. These surface reflectance products can be used to highlight vegetation characteristics such as wetness and greenness, and land cover.

The Normalised Difference Moisture Index (NDMI) and Normalised Difference Water Index (NDWI) were derived from the Sentinel-2 satellite imagery. These datasets have been classified and visually enhanced to detect vegetation moisture stress or water-logging and show distribution of moisture. For example, positive NDWI values indicate waterlogged areas while waterbodies typically correspond with values greater than 0.2. Waterlogged areas also correspond to NDMI values of 0.2 to 0.4.

Geoscience Australia, 2019a. Earth Observation Archive. Geoscience Australia, Canberra. http://dx.doi.org/10.4225/25/57D9DCA3910CD

Geoscience Australia, 2019b. Kimberley East - LiDAR data. Geoscience Australia, Canberra. C7FDA017-80B2-4F98-8147-4D3E4DF595A2 https://pid.geoscience.gov.au/dataset/ga/129985