<p>This data set consists of .tif files of true colour orthomosaics for expansive areas of mangroves in Kakadu National Park in Australia's Northern Territory.</p> <p>The orthomosaics were generated from 68 stereo pairs of true colour aerial photographs acquired in 1991 in the lower reaches of the East Alligator, West Alligator, South Alligator and Wildman Rivers and Field Island, Kakadu National Park, Northern Australia (Mitchell et al., 2007). The photographs were taken at a flying height of 13,000 ft (3,960 m) using a Wild CR10, a standard photogrammetric camera with a frame size of 230 x 230 mm. The focal length was 152 mm. The photographs were scanned by Airesearch (Darwin) with a photogrammetric scanner to generate digital images with a pixel resolution between 12 and 15 mm. The orthomosaics have a spatial resolution of 1 m, cover an area of approximately 742 km² and a coastal distance of 86 km. </p> <p>These orthomosaics were co-registered using ground control points identified from 1:100,000 digital topographic maps with a Universal Transverse Mercator (UTM), and subsequently co-registered to LiDAR data acquired over the same region in 2011.</p>

<p>This data set consists of a shapefile/kml of mangrove extent and dominant species for Kakadu National Park mangroves generated from true colour aerial photographs acquired in 1991.</p> <p>From true color 1991 orthomosaics of Field Island and the Wildman, West, and South Alligator Rivers, mangroves were mapped by first applying a fine scale spectral difference segmentation within eCognition to all three visible bands (blue, green, and red). A maximum likelihood (ML) algorithm within the environment for visualizing images (ENVI) software was then used to classify all segments using training areas associated with mangroves, but also water, mudflats, sandflats, and coastal woodlands. These were identified through visual interpretation of the imagery. Segmentation was necessary as 1) the diversity of structures and shadows within and between tree crowns limited the application of pixel-based classification procedures and 2) the color balance between the different photographs comprising the orthomosaics varied. All segments were examined individually and methodically to determine whether they should be reallocated to a non-mangrove class (e.g., mudflats) or confirmed as mangroves. Open woodlands dominated by Eucalyptus species could also be visually identified within the aerial photography (AP) orthoimages, although their discrimination was assisted by only considering areas where the underlying LiDAR DTM (Digital Terrain Model) exceeded 10 m, assuming this excludes tidally inundated sections.</p>

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Tumbarumba Wet Eucalypt site in the Bago State Forest, New South Wales, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Cumblerland Plain Woodland SuperSite in Western Sydney, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Robson Creek Tropical Rainforest SuperSite within Danbulla National Park, North Queensland, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Calperum Mallee SuperSite on Calperum Station near Renmark, South Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardised and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Alice Mulga SuperSite on Pine Hill Cattle Station in the Northern Territory, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Wombat Stringybark Eucalypt SuperSite in the Wombat State Forest, near Ballarat, Victoria, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Fletcherview Tropical Rangeland SuperSite, located 50km west of Townsville, Queensland, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.

This terrestrial LiDAR dataset captures detailed vegetation structural information at the Warra Tall Eucalypt SuperSite in southern Tasmania, Australia. The purpose of this data is to enhance understanding of vegetation dynamics and ecosystem function in the region. The dataset is part of a broader collection of Terrestrial LiDAR data acquired from all TERN SuperSites, aimed at achieving a standardized and highly detailed capture of 3D vegetation structure across Australia.