Alex Held

Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Comparison of PROSPECT and HPLC estimates of leaf chlorophyll contents in a grapevine stress study

This letter describes how PROSPECT, updated with a 1 nm chlorophyll absorbance database, was used to infer total chlorophyll content from the measured reflectance spectra of grapevine leaves. Modelled and measured reflectance spectra agreed on average to within 13% over the range 400–1600 nm. However, discrepancies between modelled and measured reflectances of up to 40% were observed in the spectral region dominated by chlorophyll content. In terms of estimating total chlorophyll content, PROSPECT gave estimates that were on average within 10 µg cm−2 of those obtained using high performance liquid chromatography.

NEW TECHNOLOGIES FOR TRANSPORT ROUTE SELECTION

Abstract Planning a new road or railway can be an expensive and time-consuming process. There are numerous environmental issues that need to be addressed, and the problem is exacerbated where the alignment is also influenced by the location of services, existing roads and buildings, and the financial, social and political costs of land resumption. A comprehensive approach to the problem is available through the recent convergence of: geospatial imaging, softcopy photogrammetry, regional significance analysis and alignment optimisation. The first technology is concerned with obtaining low cost data containing far more information than was available in the past. The second two are concerned with extracting from that data, information essential to the planning process. The final technology is about automating the way alignments are generated to produce low cost, high quality routes. The convergence of these enabling technologies can have a major impact on the way that various jobs are performed – or whether they are done at all. Separately, they can have a major influence on a large number of disciplines, but taken in combination they can change the paradigm of alignment planning completely. By taking tasks that were previously difficult, time-consuming and expensive, and making them easy, fast and cheap, they can change completely the way alignments are planned.

Predicting eucalypt biochemistry from HYPERION and HYMAP imagery

Hyperspectral remote sensing methods are advancing rapidly and offer the promise of estimating canopy pigment, bio-chemistry and water content dynamics, which can in turn be linked to carbon assimilation, forest growth and photosynthetic capacity models. The recent EO-1 HYPERION mission and associated field campaigns with ground based spectra and HYMAP airborne 5m hyperspectral imagery has allowed foliage bio-physical and bio-chemistry variables of eucalypt vegetation to be analyzed in conjunction with remotely sensed spectra. The paper will report on the prediction of eucalypt leaf bio-chemistry from ground based, airborne and satellite spectra and detail the approaches used to extrapolate these results from individual leaves to regional scales to allow estimates of the carbon cycle to be made across the landscape using combinations of inverse modeling and remote sensing. The paper details results from eucalypt forest near Tumbarumba (Bago-Maragle State Forest), Australia which has a number of eucalypt species, ranging in productivity and age.

Summary of current and future terrestrial civilian hyperspectral spaceborne systems

This paper provides an overview of current and future civilian hyperspectral spaceborne systems for terrestrial applications. For this purpose, a brief history of hyperspectral mission initiatives is given together with the spectral and spatial characteristic of current systems in orbit today. Future sensor systems are divided into missions, which are under development and in a planning stage. The latter category provides a good cross section of sensor systems to come, but is probably not a complete list of hyperspectral instruments considered by the various space agencies.

The bio-geophysical approach to remote sensing of vegetation in coupled human-environment systems : Societal benefits and global context

Hyperspectral remote sensing has promised a new era in quantitative measurement of key properties of terrestrial systems. The high information content, mechanistic relationships between reflectance spectra and canopy, leaf and molecular properties, and combination of computing power, algorithm maturity and highly quantitative methodology provides the basis for delivery of key information into new international research and observation frameworks seeking to provide societal benefits. This paper describes current capacity of global biophysical remote sensing and defines products that could be delivered by a new sensor. New products could be particularly useful in description of ecosystem services.

Integrating JERS-1 Imaging Radar and Elevation Models for Mapping Tropical Vegetation Communities in Far North Queensland, Australia

The Wet Tropics World Heritage Area in Far North Queens- land, Australia consists predominantly of tropical rainforest and wet sclerophyll forest in areas of variable relief. Previous maps of vegetation communities in the area were produced by a labor-intensive combination of field survey and air-photo interpretation. Thus,. the aim of this work was to develop a new vegetation mapping method based on imaging radar that incorporates topographical corrections, which could be repeated frequently, and which would reduce the need for detailed field assessments and associated costs. The method employed G topographic correction and mapping procedure that was developed to enable vegetation structural classes to be mapped from satellite imaging radar. Eight JERS-1 scenes covering the Wet Tropics area for 1996 were acquired from NASDA under the auspices of the Global Rainforest Mapping Project. JERS scenes were geometrically corrected for topographic distortion using an 80 m DEM and a combination of polynomial warping and radar viewing geometry modeling. An image mosaic was created to cover the Wet Tropics region, and a new technique for image smoothing was applied to the JERS texture bonds and DEM before a Maximum Likelihood classification was applied to identify major land-cover and vegetation communities. Despite these efforts, dominant vegetation community classes could only be classified to low levels of accuracy (57.5 percent) which were partly explained by the significantly larger pixel size of the DEM in comparison to the JERS image (12.5 m). In addition, the spatial and floristic detail contained in the classes of the original validation maps were much finer than the JERS classification product was able to distinguish. In comparison to field and aerial photo-based approaches for mapping the vegetation of the Wet Tropics, appropriately corrected SAR data provides a more regional scale, all-weather mapping technique for broader vegetation classes. Further work is required to establish an appropriate combination of imaging radar with elevation data and other environmental surrogates to accurately map vegetation communities across the entire Wet Tropics.

Preliminary assessment of the performance of Hyperion in coastal waters. Cal/Val activities in Moreton Bay, Queensland, Australia

Moreton Bay is the Australian EO1-Hyperion coastal site used for Cal/Val activities. Moreton Bay shows spatial gradients in optical depth, bathymetry, and substrate composition. The turbid and humic river inputs, as well as the open ocean flushing, determine the water quality of the bay. Lyngbya toxic algae blooms have become a serious environmental and health concern. The field campaigns, carried out to coincide with Hyperion overpasses, focussed on the retrieval of inherent optical properties, apparent optical properties, substrate reflectance spectra and water quality parameters. Spectra from a 12 January 2001 Hyperion image show very close agreement to in situ upwelling radiance spectra.

Hyperspectral imaging for benthic species recognition in shallow coastal waters

Airborne hyperspectral data was collected in April 1999 over 16 square kilometres of coastal waters adjacent to the South Australian Bolivar Wastewater Treatment Plant (near Adelaide). Concurrent in situ measurements of benthic reflectances were collected. A subsequent field-work mission to validate the 1999 image analysis was completed in February 2000. The aim was to map substrate type accurately, differentiating species and canopy density, if possible. The analysis approach was based on the coupling of radiative transfer models using in situ atmospheric measurements and inwater measurements to remove atmospheric and water column effects from the image data. After removal of atmospheric effects, the spectral variation is a function of the water columns constituents and spatial related effects along the image. Water samples were collected at the time of the flights and analysed for the retrieval of inherent optical properties (IOPs). The SpecTool software was used to derive benthic reflectance models based on the IOPs. The atmospheric and in-water radiative transfer corrections applied to the imagery enabled delivery of environmental baseline data of the substrate and a basis for accurate multitemporal data analysis.

ICESat/GLAS Canopy Height Sensitivity Inferred from Airborne Lidar

Variations in laser properties and data acquisition times introduced inconsistencies in Geoscience Laser Altimeter System (GLAS) data. The effect of data inconsistencies, on two GLAS height retrieval methods, from three study sites, are investigated and validated against airborne laser scanning (ALS) percentile heights, from three data sources: all/first return point clouds, and raster canopy height models. GLAS/ALS controls were established as a basis against which the influence of laser number, transmission energy, and seasonality were assessed through comparison statistics. The favored GLAS height method best compared with ALS 95th percentile heights from an all return point cloud. Optimal GLAS data (R2 = 0.69, RMSE = 8.10 m) were noted when GLAS acquired data during summertime from high energy, laser three transmissions. As GLAS data can be used in global biomass assessments, there is a need to understand and quantify the influence of these data inconsistencies on canopy height estimates. (Less)