Research Challenges

The UAV Workshop at Fowlers Gaps seeks to address a number of research challenges, which can be met by acquiring and analysing data from a range of UAV platforms and sensors.   For each challenge, ground data will be collected concurrently and you will have the opportunity to fly all or several in rotation.   To register your interest in undertaking a particular challenge, please complete the following table.

Registrations of interests in challenges.

The following provides an overview of these challenges:

A:  Vegetation Structure

Can fractional cover and foliage projective cover be derived from UAV data?

Background:  Many agencies have adopted the star transect technique for measuring ground cover, originally developed by the Queensland Government. The method requires three 100 m tape measures to be laid out in a star pattern, and for point intercept observations of cover to be recorded at 1 m intervals. Several metrics can be derived from the resulting 300 observations, with two of the most important being fractional cover and foliage projective cover (FPC). Fractional cover is the proportion of photosynthetic vegetation, non-photosynthetic vegetation and bare ground, while FPC is the proportion of the plot covered by the vertical projection of the canopy foliage. Both metrics have been modelled from Landsat data Australia wide, using many historical field observations as training. The collection of star transects is slow, and projects wishing to use the Landsat models often cannot collect sufficient data for a thorough validation.

The challenge:  To collect UAV data of the semi-arid landscape at Fowlers Gap, to derive a relationship with ground-based estimates of FPC, and to use this to generate spatial estimates of FPC from the UAV data that can scaled-up using satellite-based observation.

Ground data:  FPC Star Transects laid out at least 20 sites representing the range of FPC found at Fowlers Gap (Leaders:  Adrian Fisher and Kasper Johansen, Joint Remote Sensing Research Program (JRSRP),  UNSW and UQ). Ausplots Point intercept data – calculated to FPC and fractional cover – by the Ausplots Team

 

B:  Vegetation Species Composition

Background:  The floristic composition of vegetation communities typically requires ground-based surveys that are intensive to complete and are often insufficient to represent distributions across the landscape.   UAV-mounted sensors are able to collect spectral information but also measures of the three-dimensional structure of vegetation, each of which can be used (either singularly or in combination) to characterise, discriminate and map vegetation types to species or genus.

The challenge:  To use multi-spectral or hyper-spectral UAV data and UAV-derived point clouds to differentiate and map the distribution of dominant vegetation species or genera.

Ground data:  Auscover plots (1 ha) with measures of plant species distributions and vegetation structure. (Leader: AusCover TERN – Ben Sparrow) Composition and structure collected as per: https://www.researchgate.net/publication/266262164_AusPlots_Rangelands_Survey_Protocols_Manual_v_129

 

C:  Stock Surveys

Background:  In pastoral areas, knowledge of the density and spatial distribution of stock (cattle, sheep, horses, camels) is essential to determine numbers, movement and pasture use (e.g., to avoid degradation).  Determining the density of native and feral herbivores, which can make up to half of the herbivore grazing pressure, is also important for sustainable management of pasture. Ground based methods for counting large herbivore density are time consuming and, due to the movement of animals, often inaccurate.

The challenge:  To demonstrate the use of UAV optical, thermal and three-dimensional data for identifying individual animals within a paddock.

Ground data:  Counts and locations of feral goats in Sandstone paddock. This paddock is enclosed by a goat proof fence and the number of goats within the paddock is known.  (Leader:  NSW DPI – Steven McLeod).

 

D:  Kangaroo Surveys

Background:  Large mammals are common throughout Australia’s landscapes but quantifying their numbers and patterns of movement at different times of the year and in response to environmental factors (e.g., drought, water supply) has only been undertaken using ground-based and aircraft surveys.   A better understanding of the use of resources by these fauna and their population dynamics would improve the management and conservation of these fauna.

The challenge:  To detect individual kangaroos (and sheep) within two adjacent paddocks and provide a count of individuals and maps of their distribution, at different times of day and also on different days.

Ground data:  Counts and locations of kangaroos and stock (sharing the paddock) will be recorded using walked surveys after flights have been completed (Leader:  NSW DPI – Steven McLeod)

 

E:  Small to medium sized mammal surveys

Banckground: Small to medium sized mammals are commonplace throughout the semi-arid regions of Australia, with these ranging from mouse sized (dunnarts and planigales) to larger native species such as the bilby, which are closer in size to rabbits, and introduced species (cats, foxes, rabbits, dingos).   Knowledge of their abundance, distribution and behaviour and how these change over time is fundamental for conserving native species or controlling pest species.  However, the distribution of many mammals can only be quantified through ground surveys or through inference from vegetation and ground cover.  Direct measurement over large areas has proved problematic, not least because these mammals are often nocturnal.

The challenges:  a) To provide indirect measurements of vegetation structure and ground cover that can be used to infer the distribution and abundance of small mammals of different species and b) to directly map individuals through the use of thermal (nighttime) imagery.

Ground data:  Small to medium size mammal trapping and knowledge of distributions and habitat preferences (Leader:  UNSW – Keith Leggett). Ausplots protocols available here: http://www.ausplots.org/ecosystem-surveillance/

 

F:   Bird and Vegetation Characteristics

Background: Knowledge of the distribution and behaviour of bird species is often obtained from field surveys but there has been wide use of distribution models based on environmental variables including plant species composition, vegetation cover, productivity, height and density and the amount of bare ground.  However, much of this information has historically been obtained from airborne or spaceborne imagery, such as multi-/hyper-spectral data, lidar or radar, with relatively coarse spatial resolution.  UAVs offer a unique opportunity to capture the characteristics of vegetation which can be used directly to identify ‘favoured’ habitats or as input to species distribution models at fine spatial resolution.   At Fowlers Gap, a number of bird species occur including Chestnut-crowned Babblers, Zebra Finches and Apostlebirds but their populations and breeding times and successes are varying in response to climate.

The challenge:  To map vegetation characteristics (e.g., species composition, productivity) from UAV data that can be used to discern the distribution of selected bird species and to use as input to species distribution models.

Ground data:  Historical and real time data on the distribution of selected bird species and their association with vegetation communities; vegetation plots (Leader: Macquarie University – Simon Griffith)

 

G:  Geological Surveys

Background: For over 60 years, remote sensing data has been used to describe and differentiate different geologies across the World, with Australia being a well-studied continent.  This capability has increased with the advancement of hyperspectral, radar and lidar imaging although the majority have been acquired from spaceborne and airborne sensors.   However, few studies have evaluated the use of UAV data for describing geological formations.

The challenge:  To provide maps of geological formations at Fowlers Gap that represent a significant improvement on those that are existing using hyperspectral, lidar or other imagery.

Ground data:  Existing geological maps and ground based confirmation (Leaders:  UNSW –  Keith Leggett/Adrian Fisher)

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