This was a combined DSITI, The University of Queensland JRSRP, the University of NSW and Tern-Auscover revisit to the Injune Landscape Collaborative Project (ILCP) site that coincided with airborne capture of dual wavelength full waveform lidar, hyperspectral imagery and thermal imagery over the site by Airborne Research Australia (ARA), a program within the University of Adelaide. The field work had two main objectives:
  1. To calibrate and support the airborne imagery capture with a standard set of spectral, atmospheric and field measured biophysical parameters; and
  2. To remeasure several field plots first sampled in 2000 as part of a joint NASA/CSIRO/QNRM mission and were been subsequently measured in 2009 as part of our collaboration with the Japanese Aerospace Exploration Agency (JAXA) ALOS Kyoto and Carbon Initiative.
Over the week we travelled several hundred kilometers setting up calibration plots and field sites to cover a range of forest and woodland types.


The ILCP is recognised internationally as a key site (and one of only a few located in woodlands and open forests) that has facilitated the development of new algorithms for retrieving biophysical attributes and detecting change with long term remote sensing observations at multiple scales. These data will contribute to DSITI's fractional cover and wooded extent mapping programs, and will build on the existing data to better understand ecosystem response to change and allow the calibration and validation of new spaceborne sensors.

Day 1

We'd arrived in the night, after travelling via Morven to pick up a GPS base station from ARA who were preparing to capture Lidar and Hyperspectral data over the site. We set this up on a station in the middle of the site on Mt Owen Station and let it log for the week to act as a control point to geometrically correct the data.

We camped in the forestry hut on site. Dawn on the first day was about 1 degree so the first job was to chop some wood and get the fire going. After checking and packing the gear one group set off to start measuring a forest plot and a second group went to set up the hyperspectral calibration targets.


We set these three targets up at the end of the Mt Owen airstrip on day 1 and set about measuring their reflectance. There's a black, grey and white one. We also used a sun photometer to measure water vapour, areosol optical depth and ozone throughout the campain, fixed the position of the targets using DGPS and measured the temperature of the targets to help calibrate the thermal data sets.



Meanwhile, the second group was scanning the woodland site with the terrestrial laser scaner (TLS) and tagging and measuring the size and location of every tree. These trees had been measured in the past and so by remeasuring them we can start to see subtle changes in the site biomass, and link these measurements with the terrestrial laser scanner and airborne data.



We also ran a new experiment at this site, sampling our traditional star transects at a 50cm rather than 100cm interval. This is part of a scaling experiment designed to better sample the spatial variability of land cover classes and how they respond to changing climate, fire and grazing impacts. In this photo you can see the clumped nature of the bare and grassy tussock patches (and the cool sampling pole mount for the ODK enabled mobile phone to record data). As we better understand the clumping of the ground and canopy cover elements across landscape, canopy and leaf scales, we can better model how they respond to disturbance and change and better link remote sensing data captured across these multiple scales.

It also helps refine our ground cover model, which allows us to predict the amount of ground cover under the tree canopy.

This is a screen grab from my android mapping app over a portion of the site. My tracklog is in blue and the imagery is the standard Google earth image. It's a mixed open pasture and woodland environment with a long land management history.


This is the same region with the most recent Landsat fractional cover displayed. The tree covered areas (and riparian corridors) are green (high green cover) and there are some blue paddocks (dry non-green grasses) and red (bare) patches and roads. But from this we don't really know the grassland condition under the trees, or even in the mixed tree-grass paddocks. But if we model the tree cover and understand the scaling we can estimate the cover under the trees quite accurately.


The cover under trees (ground cover) image paints quite a different picture of the cover composition on the ground (it's using the same colour scale as the fractional cover image) - there is very little green ground cover but the forested areas still have high non-green cover due to the large amount of litter. You can also see that the river corridor is very bare in this area due to access by grazing animals, and that small patches of green forage still exist in places under the canopy, where they managed to miss the severe frosts that occurred over the site a month ago. This ground cover product is pretty useful for grazing land management and erosion modelling which is why we're spending some time improving and validating it.


Day 2


Day 2 started with some broken cabling which required some field repairs but we soon had the calibration site set up on a different station and the overflights by the hyperspectral and lidar instruments underway.



This "small world" panorama of the calibration site shows the black, white and grey targets set out under a beautiful cloudless day. We set the targets out on a clear, flat area and send the coordinates via satellite SMS to the plane who then capture imagery over them several times during the flight.



With the flights complete, I took off to help the others with the vegetation samples but got a flat a few kilometres down the road. Luckily I had the support of about 40 head of cattle to get me on my way.



Many of the tracks on this site are pretty rough and sandy making a 4WD essential to get around this remote area. It also meant long days travelling to and from the camp site to get the work done, and some time spent clearing debris from tracks to get through to the sites. But it's a beautiful landscape.


Day 3

Day 3 started with another spiked tyre en-route to the site. This used my last spare, so after replacing the tyre, we cleaned and plugged the hole, popped it back out onto the rim and re-inflated in case we needed to use it again. Luckily we didn't :)



This day we sampled a very dense sitewith heaps of stems in the 50m plot, so Richard made use of a log for a field chair while he took bearings and distances to all the measured trees to make a tree map.



Meanwhile the grassand litter biomass sampling team ran an impromptu training session in pasture harvesting so we could get more grassland biomass data to relate back to the terrestrial laser scanner (TLS) data.




These quadrats were sampled in precise locations across the site after the TLS scans so we can relate the grass height measured off the scans to the amount of biomass present on the site. this will be useful as we start to develop better grass biomass relationships based on optical and radar data in the future.


Day 4


And of course we took many TLS scans. On most of these field site we also set up several permanent marks (buried steel pegs in concrete collars) so we'll be able to precisely co-register any future scans to better measure very subtle changes across the site with a greater precision than ever before.


The scans will be used to link the field measurements to the airborne and satellite data sets, furthering our understanding of the ecological processes and changes in these dynamic woodland environments.


I'd like to thank everyone involved, it was a great week topped off by a hot shower and meal at the Courthouse in Mitchell (complete with Horse at the bar - thanks for the photo John!).



Despite the 438 new emails in my inbox when we regained mobile coverage, I'm really looking forward to seeing the airborne lidar and imagery (and coincident Landsat, Sentinel-1, ALOS-2, Terrasar-X and MODIS data) over the coming weeks.