Spatial analysis of changing terrestrial ecosystems in the Windmill Islands and the sub-AntarcticEntry ID: AAS_3130
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Abstract: Metadata record for data from AAS (ASAC) project 3130.
High latitude terrestrial ecosystems are experiencing rapid change, which is most likely caused by climate change, human impacts, and invasive species. Up-to-date and accurate spatial data at a range of scales are of crucial importance for mapping changes in these fragile ecosystems. The aim of this study is to undertake spatial ... analyses on the changing terrestrial ecosystems of the Windmill Islands, Antarctica and sub-Antarctic Macquarie Island. The study aims to better understand the different processes that result in ecosystem change and with new state-of-the-art high-resolution spatial data we hope to contribute to improved management strategies.
Environmental threats globally can be categorised into four main types: local impact from human activity and habitat loss; impact from alien species and homogenisation of biota; impact from climate change and impact associated with harvesting and resource extraction. All four types of impacts occur to some degree in the Antarctic region (Hull and Bergstrom 2006, Bergstrom and Selkirk 2007). This project examines change associated with these impacts in Australian Antarctic and sub-Antarctic territories. In particular, we seek to isolate signals of impact from regional climate change from those of other human-induced change within Antarctic and sub-Antarctic terrestrial ecosystems.
This project will develop and apply spatial data collection and analysis techniques for detailed baseline mapping and change detection of vegetation communities on the Windmill Islands and Macquarie Island. We will then employ these cutting-edge techniques to quantify, detect, and understand the impact of changes. In detail, the objectives of this project are to:
Objective 1: Collate and collect spatial data in order to establish a baseline map of, and detect changes in vegetation communities on the Windmill Islands and Macquarie Island.
Objective 2: Create high-resolution digital elevation models (DEM) based on GPS data and airborne laser scanning (LiDAR) of the localities.
Objective 3: Explore ecological relationships between vegetation communities and biologically relevant landscape characteristics and human-induced disturbance using terrain analysis of digital elevation models in a Geographical Information System (GIS) in order to better understand the distribution of and changes in vegetation communities. This will include the development of hydrological terrain analyses to examine the impact of changing snow conditions around Casey on vegetation communities.
Objective 4: Develop and apply new multi-scale field sampling techniques based on field photogrammetry and GPS observations at different scales (from 20cm to 20m) to measure relative percent cover of plant species and vegetation communities. This objective is of key importance to bridge the range of scale levels from small field quadrats to satellite images that cover large portions of the landscape.
Objective 5: Combine detailed plot-scale data and field photographs with terrain information and high-resolution satellite imagery to identify and map changes in both plant communities and plant stress more efficiently.
This project will deliver valuable baseline and temporal data on the impact of environmental change in Australian Antarctic and sub-Antarctic territories. It will improve our understanding of Antarctic and sub-Antarctic landscape ecology and species adaptations. It will provide a predictive GIS model that can forecast the effects of human activities in Antarctica and provide new tools for spatial multi-scale geographic analysis.
Taken from the 2009-2010 Progress Report:
Progress against objectives:
Windmill Islands moss beds
In the first year of this project we found that the spatial scale of the moss beds (tens of m2) makes satellite imagery (even very high resolution imagery of 0.5 m) unsuitable for mapping their extent in sufficient detail. Due to logistical constraints aerial photography is impractical. Recent developments in the use of unmanned aerial vehicles (UAVs) for remote sensing applications provide exciting new opportunities for ultra-high resolution mapping and monitoring of the environment. This year, we developed a new UAV consisting of an electric remote controlled helicopter capable of carrying three different cameras: visible colour, near-infrared, and thermal infrared for cost-effective, efficient, and ultra-high resolution (less than 5 cm pixel size) mapping of terrestrial vegetation in the Windmill Islands, Antarctica. These three sensors allowed us to map different physical characteristics of the moss beds at resolutions of several centimetres.
We had a very successful season at Casey. We managed to collect spatial data for four different moss sites: ASPA135, Red Shed, Robinson Ridge, ASPA136. We collected the following datasets:
- Very accurate GPS locations for existing moss quadrat sites with a geodetic GPS receiver (cm accuracy).
- For ASPA135, Red Shed, and Robinson Ridge we collected very dense GPS transects and used these data to interpolate high resolution digital elevation models (DEMs).
- For all sites we collected geotagged photographs of all quadrats in addition to geotagged landscape scale photographs.
- For ASPA135, Red Shed, and Robinson Ridge we flew a total of 26 UAV flights collecting visible photography (2 cm pixel size), near-infrared photography, thermal imagery, and video footage for all sites.
- For the Robinson Ridge and Red Shed site we collected spectral signatures of the key moss species and other land cover types (water, rock types, lichen, snow, etc.). The handheld spectrometer was rented from Geoscience Australia.
- On request of Sandra Potter and Tom Maggs, we collected GPS data and UAV photography for the Casey quarry before and after blasting to determine the extent of the blasting zone and to acquire ultra-high resolution imagery of the quarry for management purposes.
This project has strong links with AAS project 3095. Phillippa Bricher (UTAS PhD student) and Jared Abdul-Rahman (UTAS volunteer and Honours student) have collected data for Phillippa's PhD project. Data collection for Phillippa's project consisted of geotagged photographs of vegetation plots with Polecam. Jared concentrated on photographing Azorella die-back. Phillippa's data will be used for vegetation classification of the island using satellite imagery and DEMs.
A new WorldView-2 high-resolution satellite image was acquired for the northern half of the island on 26 December 2009. This image will be extremely useful for vegetation classification and change detection.
As noted in objective 1 (above), we collected dense transects of GPS data for three moss bed sites in the Windmill Islands. We interpolated the GPS height values to obtain three very high resolution DEMs (less than 0.5 m). The AAD's LiDAR instrument was not available at Casey or Macquarie Island this season, however, we requested LiDAR data collection at Davis over known moss sites. The data was collected successfully, but it hasn't been processed yet. With this dataset we are hoping to assess the usefulness of LiDAR for mapping of micro-topography. In the meantime we have continued to develop our UAV (externally funded UTAS project). We have built a larger version that is capable of carrying a mini-LiDAR instrument. We hope to employ this UAV LiDAR at our study sites in the Windmill Islands during the 2010/2011 summer season. This novel system will allow us to capture the microtopography of the moss bed areas and will allows us to more accurately model the hydrological conditions (compared to GPS derived DEMs).
We have already modelled several environmental parameters for the high-resolution DEMs of the Windmill Islands (ASPA135, Robinson Ridge, and the Red Shed). The derivatives include a topographic wetness index, average annual solar radiation, and slope gradient. In combination with the UAV photographs and the close-up quadrat photographs we aim to establish a relationship between the condition of the moss and environmental factors.
Lucieer is currently on Study Leave at ITC in The Netherlands (March - April 2010) and the University of Calgary, Canada (April - May 2010). At these institutes Lucieer is working on a new texture-based classification technique to map healthy tussock slopes on Macquarie Island (as an indicator of island health). Preliminary highlight that this novel image classification technique is very successful at identifying tussock slopes in high resolution QuickBird imagery.
With the Polecam technique on Macquarie Island and with the UAV photographs in the Windmill Islands we have developed two very novel techniques for multi-scale sampling. These photographic sampling techniques will provide invaluable information for the next phase of the project.
We aim to further develop our UAV project and use the larger UAV with multiple sensor in future field campaigns. This will allow us to build a multi-temporal dataset of the study areas and detect changes over time. The experiments in this first field season have provided us with important insights for suitable data collection techniques and the collected data are incredibly valuable for addressing the objectives of this project.
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Data Set Citation
Dataset Release Date: 1999-10-07
This data set description is a member of a collection. The collection is described in
Start Date: 1998-02-28Stop Date: 1998-04-01
ATMOSPHERE > ATMOSPHERIC TEMPERATURE > AIR TEMPERATURE
ATMOSPHERE > ATMOSPHERIC WATER VAPOR > HUMIDITY
ATMOSPHERE > ATMOSPHERIC WINDS > SURFACE WINDS
ATMOSPHERE > ATMOSPHERIC RADIATION > SOLAR RADIATION
OCEANS > OCEAN TEMPERATURE > WATER TEMPERATURE
OCEANS > SALINITY/DENSITY > SALINITY
ATMOSPHERE > ATMOSPHERIC PRESSURE
Quality See the Marine Science Support Data Quality and Programmer's Reports at the Related URL section.
Please see the Marine Science Support Data Quality Report via the Related URL section.
Where data for a particular sensor do not exist for a particular time, the last known value is used unless the sensor has been disabled or has encountered an error. For example, some sensors only record data every minute, but the resolution for the underway dataset is 10 seconds, so the same value will be used 6 times a minute. No averages are taken for sensors that capture data at a rate other than every 10 seconds. Instead, each record will be a snapshot of each sensor at that time.
Access Constraints Data stored on DLT tapes. Available online via the Australain Antarctic Division Data Centre web page.
Use Constraints This data set conforms to the PICCCBY Attribution License
Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=199798060 when using these data.
Data Set Progress
Role: TECHNICAL CONTACT
Role: DIF AUTHOR
Phone: +61 3 6232 3106
Email: jono.reeve at aad.gov.au
203 Channel Highway Australian Antarctic Division
Province or State: Tasmania
Postal Code: 7050
Extended Metadata Properties
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Creation and Review Dates
DIF Creation Date: 1999-10-07
Last DIF Revision Date: 2013-05-16