Development of multistage procedures for quantifying the biomass, structure and community composition of Australian woodlands using polarimetric radar and optical data R.M. Lucas, P. Tickle† , C. Witte†† A.K.Milne ††† Institute of Geography and Earth Sciences, The University of Wales, Aberystwyth, Penglais Campus, Aberystwyth, Ceredigion, SY23 3DB, United Kingdom. †† Bureau of Rural Sciences and Cooperative Research Centre for Greenhouse Accounting, PO Box E11, Kingston, ACT, 2604 Australia. (Tel: 61 2 6272 4689; email:
[email protected]) †† Forest Ecosystem Assessment and Planning, Queensland Department of Natural Resources, Resource Sciences Centre, 80 Meiers Road, Indooroopilly, Queensland, 4068, Australia. (Tel: 61 738969832; Email:
[email protected]) ††† School of Geography, The University of New South Wales, Kensington, NSW, 2052, Australia. (Tel: 61 2 93854386; Fax: 61 2 931357878; Email:
[email protected]) Abstract-Focusing on woodlands in Queensland, Australia, this paper outlines a multi-stage approach to quantifying and scaling-up field-based measurements of vegetation structure, biomass and community composition to the landscape. The approach utilises remotely sensed data from a range of instruments (including SAR, hyperspectral and lidar) operating at different spatial and spectral resolutions. The research is anticipated to benefit calculation of greenhouse gas emissions, conservation of biodiversity, and sustainable utilisation of woodlands in Australia. INTRODUCTION
As a signatory to international agreements, that include the United Nations Framework Convention on Climate Change (UNFCCC), the Kyoto Protocol and the Montreal Process, Australia is increasingly obliged to provide spatial and temporal information on ecosystem structure, species/community composition and biomass (carbon content). Such information is necessary for providing regional assessments of biological diversity and forest condition, calculating greenhouse gas emissions associated with land use change and forestry, and supporting sustainable utilisation of ecosystems. In Australia, the urgency to acquire such information has increased, particularly following recent awareness of increased woodland clearance in several States, particularly Queensland. Despite these requirements, mechanisms for spatially quantifying the structural diversity, biomass and community composition of woodlands have not been forthcoming for a number of reasons. In particular, many organizations have historically relied upon field-based observations and inventory data to support the interpretation of stereo aerial photography and Landsat sensor data. However, increasingly, field-based measurements are proving inappropriate or insufficient for quantifying key biophysical properties of vegetation, particularly biomass. Furthermore, in using data from optical sensors, only two-dimensional observations of vegetation are provided and the three-dimensional
structure can only be inferred. The potential of SAR for quantifying the biomass and three-dimensional structure of woodlands, particularly when used in conjunction with optical data, has nevertheless been recognised. However, demonstrating the integration of SAR and optical data for these purposes has been limited by the lack of simultaneous observations across the electromagnetic spectrum, the scarcity of site and species-specific allometric equations for biomass estimation, and the inability to extrapolate field-based measurements beyond the basic area of the plot. To address these issues, the University of New South Wales, the Queensland Department of Natural Resources, the Bureau of Resource Sciences, the Queensland University of Technology and the Queensland Tropical Beef Centre established a project aimed at advancing fieldbased and remote sensing techniques for scaling-up plotbased estimates of the biomass, structural diversity and community composition of woodlands in Queensland. The project, funded through the Australian Research Council (ARC SPIRT) scheme, was designed to support the calculation of national carbon budgets, sustainable utilization of forests, and conservation of biodiversity through sound scientific underpinning. Furthermore, the research is intended as a first stage in a process aimed at understanding and modelling the dynamics of woodlands in Australia. Support for the project was increased subsequently through contributions from the Australian Greenhouse Office and the CRC for Carbon Accounting. STUDY AREA
The study focused on a 40 x 60 km area of woodland near Injune, which is located in the Southern Brigalow Belt (SBB), a biogeographic region of southeast and central Queensland (Fig. 1). More than 50 % of clearing in Queensland has occurred in the SBB and has been attributed largely to the establishment of cattle pasture, the expansion of the wheat farming and, more recently, the formation of cotton fields. Partial clearance of vegetation
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has also been commonplace in the pastoral areas and woody thickening is also widespread. Due to the complex nature of land use and management practices, the landscape consists of a mosaic of cleared fields and forest and woodland communities in various stages of degradation and/or regeneration. Within the Injune study area, the gently undulating country supports white cypress pine (Callitris glaucophylla) stands on the sandy hills. The more alluvial clays in the valleys are dominated by poplar box (E. populnea), silver-leaved ironbark (E. melanaphloia) and brigalow (A. harpophylla) communities.
Fig. 1: The Injune study area and sampling design FIELD AND REMOTE SENSING DATA ACQUISITION
For the study area, a systematic sampling scheme based on 150 150 x 500 m primary sampling units arranged across a 4km grid was established (Fig. 1.) For each PSU, the following remotely sensed data were acquired: • 1:4000 stereo colour aerial photographs (June, 2000); for purposes of tree crown mapping, species and community identification, tree height estimation (using standard photogrammetric techniques), and land cover mapping. • Laser scanner data (1 m resolution, footprint of 25 cm, August, 2000); for deriving tree height and vertical canopy profiles, crown dimensions, and ground surface digital elevation models. • Hyperspectral CASI (August, 2000) data (1 m spatial resolution; 14 wavebands) and HyMap (September, 2000) data (2.5 m spatial resolution, 120 wavebands, for a subsection of the sampling units); for establishing crown dimensions, differentiating tree species on the basis of their visible, near infrared and mid infrared reflectance and retrieving foliage parameters including projected foliage cover, leaf area and foliar chemistry.
Using the stereo colour aerial photographs, the main vegetation types were delineated by a trained photogrammetrst/botanist and described in terms of their height, cover and disturbance. The field data collected in late July/early August from 12 of the 150 sample units included: • Within 36 50 x 50 m secondary sampling units (SSUs; up to 4 per subunit), the locations of all trees > 5 cm diameter (at 130 cm) and their diameter (at 30 and 130 cm), height and crown dimensions. Each tree was identified to species. • Within 10 x 10 m subplots, an assessment of understorey (< 5 cm) vegetation type and structure. • Digital photographs of at least every 10th tree. • Foliage projected cover observations acquired at 1 m intervals along three 50 m transect lines and canopy photographs taken at 5 m intervals along the same transect lines. • Soil moisture measurements. • Reflectance measurements of vegetation and nonvegetation surfaces acquired with an ASD Fieldspec Spectroradiometer. Destructive harvesting of the major tree species (Callitris glaucophylla, Eucalpytus crebra, Eucalpytus populnea, Acacia harpophylla) across the diameter range was undertaken to estimate the biomass of the above ground and, in the case of C. glaucophylla, the below ground components. These components included leaves and both branches and trunks divided into discrete size classes (e.g., 1-4 cm, 4-10 cm, 10-20 cm etc.) Additional harvesting for total above ground biomass estimation was undertaken for several other key species, including Angophora leiocarpa. For the majority of trees harvested, leaves were extracted from different heights and aspects within the canopy and their spectral reflectance measured using the Fieldspec radiometer, thus providing comparative reflectance curves for species discrimination purposes. On the 3rd September, the NASA JPL DC-10 acquired four strips (10 x 80 km) of polarimetric SAR (POLSAR), one strip of topographic SAR (TOPSAR) and four strips of hyperspectral MASTER (TERRA-1 MODIS ASTER simulator) data over the 40 x 60 km study area. Landsat ETM+ data and also ASTER data were acquired over the study area over the same time period. ASTER data continues to be collected on a regular basis. PROCESSING STAGES
The extensive datasets that have been acquired are currently maintained within a site-specific GIS database and the processing and integration of these data is
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ongoing. The analysis of the data is focusing on the following key areas: • Calculation of total and component biomass for each SSU based using data on height, diameter and crown dimensions as input to site and species-specific allometric equations [1]. • Establishment of empirical relationships between attributes of the woodlands (e.g., height, crown area) that can be quantified using fine spatial resolution remotely sensed data [2,3] and key structural and biomass elements (e.g., crown volume, above ground and component biomass) • On this basis, spatial extrapolation of component structure and biomass beyond each SSU and across each PSU using a combination of stereo aerial photography and laser scanner, CASI and HyMap data. The resulting spatial estimates for each PSU are being used to understand and interpret the POLSAR, TOPSAR and MASTER data acquired for the study area. This is being achieved through the following processes. • Establishment of empirical relationships between component biomass and structure (as mapped for 150 PSUs) and both SAR and optical (MASTER) data. • Simulation of the SAR backscatter using composite backscatter models or radiative transfer equation models (e.g., MIMICS). The primary purpose of the modelling is to understand and interpret the interactions of microwaves of different length and polarisation with the structural and biomass components of the woodlands. Such theoretical work provides a physical base for the application of the image data and is expected to indicate the optimal SAR parameters (wavelength, polarisation, incidence angle) for quantifying the biomass and structural diversity of woodlands. The spatial datasets on biomass, structure and floristic composition together with information on the ground surface (generated from aerial photographs and laser scanner data) will be used as input to the models that generate estimates of C, L and P band backscatter at different polarisations. The actual and predicted backscatter will be compared thereby providing a better understanding of the interaction of microwaves with the woodland components. Through this research, the project seeks to understand the interactions between active microwaves and component biomass/structural attributes, thereby gaining an understanding of the optimal SAR frequencies and polarisations for their estimation. The additional benefits of integrating estimates of, for example, leaf area or foliage projected cover, as estimated using data from optical sensors (e.g. MASTER, ASTER) are also being established. The project is anticipated to generate, for the
Injune study area, fine spatial resolution maps of component biomass, structural diversity and also woodland community composition, using a combination of SAR and optical data, together with statements of accuracy. Algorithms, that use SAR and optical data as input, will be developed to facilitate routine mapping of biomass, structure and community composition. FUTURE PROSPECTS
Following the launch of ENVISAT Advanced SAR (ASAR) in June 2001and the ALOS Phase Array L-band Synthetic Aperture Radar (PALSAR) in June 2003, spaceborne observations using polarimetric C- and L-band will be realised. Combined with the current and future suite of spaceborne optical sensors, this unique configuration potentially provides an opportunity for many countries to enhance their capacity for quantifying and mapping vegetation biomass, structure and community composition. The research undertaken during the ARC SPIRT project, using airborne equivalents of these spaceborne sensors, will provide the capacity to rapidly understand and utilise these new datasets and is anticipated to provide sufficient evidence to facilitate Statewide or even continental assessment of vegetation biophysical properties. In this capacity, the project will support Australia’s obligations to international agreements, enhance national understanding of woodland ecosystem dynamics and response to change and facilitate calculation of greenhouse gas emissions and carbon accounting, support regional assessments of biological diversity, and encourage sustainable utilisation of ecosystems ACKNOWLEDGMENTS
The authors would like to acknowledge the support provided by the Australian Research Council (ARC) under their SPIRT program, staff of the UNSW, QDNR, BRS, QUT, QDPI TBC, the CRC GA and Agriculture Fisheries and Forestry Australia and QDPI TBC. Integrated Spectronics, Rotor Resources, NASA and BALL AIMS are thanked for acquiring the data. REFERENCES [1] N.L.R. Cronin, R.M. Lucas, C. Witte and A.K. Milne, “Synthetic Aperture Radar for Above Ground Biomass Estimation in Australia’s woodlands”, Proceedings IGARSS Conference, Sydney, Australia, 2001. [2] P.K. Tickle, C. Witte, A. Lee, R.M. Lucas, K. Jones, and J. Austin, “The use of airborne scanning lidar and large-scale aerial photography within a strategic forest inventory and monitoring framework”, Proceedings IGARSS Conference, Sydney, Australia, 2001. [3]M.Paterson, L. Chisholm, and R.M. Lucas, “Differentiation of selected Australian woodland species using CASI data”, Proceeedings IGARSS Conference, Sydney, Australia, 2001.
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