Determining forest structural attributes using an inverted geometric-optical model in mixed eucalypt forests, Southeast Queensland, Australia

The Montreal Process indicators are intended to provide a common framework for assessing and reviewing progress toward sustainable forest management. The potential of a combined geometrical-optical/spectral mixture analysis model was assessed for mapping the Montreal Process age class and successional age indicators at a regional scale using Landsat Thematic data. The project location is an area of eucalyptus forest in Emu Creek State Forest, Southeast Queensland, Australia. A quantitative model relating the spectral reflectance of a forest to the illumination geometry, slope, and aspect of the terrain surface and the size, shape, and density, and canopy size. Inversion of this model necessitated the use of spectral mixture analysis to recover subpixel information on the fractional extent of ground scene elements (such as sunlit canopy, shaded canopy, sunlit background, and shaded background). Results obtained fron a sensitivity analysis allowed improved allocation of resources to maximize the predictive accuracy of the model. It was found that modeled estimates of crown cover projection, canopy size, and tree densities had significant agreement with field and air photo-interpreted estimates. However, the accuracy of the successional stage classification was limited. The results obtained highlight the potential for future integration of high and moderate spatial resolution-imaging sensors for monitoring forest structure and condition. (C) Elsevier Science Inc., 2000.

Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

A strategy to fill gaps in soil survey over large spatial extents: an example from the Murray-Darling basin of Australia

We re-mapped the soils of the Murray-Darling Basin (MDB) in 1995-1998 with a minimum of new fieldwork, making the most out of existing data. We collated existing digital soil maps and used inductive spatial modelling to predict soil types from those maps combined with environmental predictor variables. Lithology, Landsat Multi Spectral Scanner (Landsat MSS), the 9-s digital elevation model (DEM) of Australia and derived terrain attributes, all gridded to 250-m pixels, were the predictor variables. Because the basin-wide datasets were very large data mining software was used for modelling. Rule induction by data mining was also used to define the spatial domain of extrapolation for the extension of soil-landscape models from existing soil maps. Procedures to estimate the uncertainty associated with the predictions and quality of information for the new soil-landforms map of the MDB are described. (C) 2002 Elsevier Science B.V. All rights reserved.

ASRIS: the database

The Australian Soil Resources Information System (ASRIS) database compiles the best publicly available information available across Commonwealth, State, and Territory agencies into a national database of soil profile data, digital soil and land resources maps, and climate, terrain, and lithology datasets. These datasets are described in detail in this paper. Most datasets are thematic grids that cover the intensively used agricultural zones in Australia.

Predicting sheetwash and rill erosion over the Australian continent

Soil erosion is a major environmental issue in Australia. It reduces land productivity and has off-site effects of decreased water quality. Broad-scale spatially distributed soil erosion estimation is essential for prioritising erosion control programs and as a component of broader assessments of natural resource condition. This paper describes spatial modelling methods and results that predict sheetwash and rill erosion over the Australian continent using the revised universal soil loss equation (RUSLE) and spatial data layers for each of the contributing environmental factors. The RUSLE has been used before in this way but here we advance the quality of estimation. We use time series of remote sensing imagery and daily rainfall to incorporate the effects of seasonally varying cover and rainfall intensity, and use new digital maps of soil and terrain properties. The results are compared with a compilation of Australian erosion plot data, revealing an acceptable consistency between predictions and observations. The modelling results show that: (1) the northern part of Australia has greater erosion potential than the south; (2) erosion potential differs significantly between summer and winter; (3) the average erosion rate is 4.1 t/ha. year over the continent and about 2.9 x 10(9) tonnes of soil is moved annually which represents 3.9% of global soil erosion from 5% of world land area; and (4) the erosion rate has increased from 4 to 33 times on average for agricultural lands compared with most natural vegetated lands.

Observations of anti-winds in a deep alpine valley, Lake Tekapo, New Zealand

This paper presents observations of summertime anti-winds monitored under ideal conditions in the Lake Tekapo hydro-catchment situated in the central Southern Alps, New Zealand. Onset and cessation of anti-winds was observed to coincide with the change in phase of the surface limbs of thermally generated valley and mountain winds under settled anti-cyclonic conditions. Anti-winds were best developed in the early morning before surface heating and associated convective mixing of the valley atmosphere began to mask the boundaries between the surface based limb of the mountain-valley wind and the corresponding anti-wind. By mid-day, the anti-valley wind exceeded the height of the surrounding ridgeline and became embedded in the topographically channeled gradient wind. Observations presented here have both theoretical and applied implications with regard to the development of thermally generated wind systems in deep alpine valleys, and their role in the dispersion of air pollution.

Degradation of phenanthrene and pyrene in soil slurry reactors with immobilized bacteria Zoogloea sp.

The environmental fate of polycyclic aromatic hydrocarbons (PAHs) in soils is motivated by their wide distribution, high persistence, and potentially deleterious effect on human health. Polycyclic aromatic hydrocarbons constitute the largest group of environmental contaminants released in the environment. Therefore, the potential biodegradation of these compounds is of vital importance. A biocarrier suitable for the colonization by micro-organisms for the purpose of purifying soil contaminated by polycyclic aromatic hydrocarbons was developed. The optimized composition of the biocarrier was polyvinyl alcohol (PVA) 10%, sodium alginate (SA) 0.5%, and powdered activated carbon (PAC) 5%. There was no observable cytotoxicity of biocarriers on immobilized cells and a viable cell population of 1.86 x 10(10) g(-1) was maintained for immobilized bacterium. Biocarriers made from chemical methods had a higher biodegradation but lower mechanical strengths. Immobilized bacterium Zoogloea sp. had an ideal capability of biodegradation for phenanthrene and pyrene over a relative wide concentration range. The study results showed that the biodegradation of phenanthrene and pyrene reached 87.0 and 75.4%, respectively, by using the optimal immobilized method of Zoogloea sp. cultivated in a sterilized soil. Immobilized Zoogloea sp. was found to be effective for biodegrading the soil contaminated with phenanthrene and pyrene. Even in natural (unsterilized) soil, the biodegradation of phenanthrene and pyrene using immobilized Zoogloea sp. reached 85.0 and 67.1%, respectively, after 168 h of cultivation, more than twice that achieved if the cells were not immobilized on the biocarrier. Therefore, the immobilization technology enhanced the competitive ability of introduced micro-organisms and represents an effective method for the biotreatment of soil contaminated with phenanthrene and pyrene.