Ian C. Lau

Comparison of PLSR modelling and indicative mineral mapping of airborne hyperspectral imagery for acid sulphate soil assessment

Acid sulphate soils (ASS) are widely distributed around the world and can be harmful to the environment due to their potential release of severe acidity, which in turn can mobilize harmful quantities of both major and trace metals. The effective mapping and assessment of ASS and the resulting spread of their harmful effects are important in the management of these widespread soils. Secondary iron and sulphate-bearing minerals form within and on surfaces of AAS during oxidative evolution. These secondary minerals are indicative of the existence of different pH conditions on the surface of the soil. Many of these indicator secondary minerals associated with acidic soil conditions can be identified by hyperspectral sensing due to their diagnostic spectral reflectance features. Accordingly, hyperspectral sensing was used in a coastal area bearing AAS to identify and map secondary minerals using spectral absorption features. This information was used to establish the spatial extent and severity of soil acidity by utilizing the relationship between the presence of indicative minerals and pH values. Additionally, an intrinsic relationship between pH values and reflectance spectral features was also modelled by the partial least square regression (PLSR) method using ASS samples collected from the test site and applied to HyMap imagery to successfully deduce an acidity map. Both resultant maps of acidic conditions were compared and it was found that nearly 94% of the pixels in the two pH maps deduced from these different methods were highly similar. This suggested that the soil pH distribution attained was accurately mapped by the HyMap imagery and the PLSR model established was robust at predicting soil acidity affected by ASS in the study area.

Assessment of Acid Sulphate Soil both on surface and in subsurface using hyperspectral data

Acid sulphate soils (ASS) are widely spread around the world and are potentially harmful to the environment due to their strong acidity producing ability and their capability to release trace metals. Secondary iron-bearing minerals produced by ASS, have diagnostic spectral features in the visible-near infrared to short-wave infrared spectral range and can be good indicators to the severity of the effects of ASS. Therefore, it is possible to detect ASS using hyperspectral sensing by mapping these indicative iron-bearing minerals. Iron oxides, hydroxides, hydroxysulphates, as well as noniron-bearing minerals, were mapped using airborne Hyperspectral Mapper data. Subsequently, a soil pH map of the surface was deduced according to the relationship between the indicative mineral species and measured pH values. Furthermore, this study investigated the presence of ASS in the subsurface by the proximal hyperspectral sensing HyLogger system, together with soil coring and soil property measurements. This allowed the acquisition of mineralogy, pH, and other soil properties at different subsurface depths. Thus, comprehensive understanding and estimation of ASS, both on the surface and in the subsurface, were attained.

Estimating soil salinity using hyperspectral data in the Western Australian wheat belt

With the aim of early detection of soil salinity, this study developed a method to quantitatively estimate soil salinity in arid and semi-arid environments using SWIR reflectance spectroscopy. Focusing on the soil spectral characteristics occurring around 2000 nm, we determined, using subset analysis, that the spectral wavelength ranges which provide the greatest diagnostic information relating to soil salinity occur at 1996 and 2025 nm. An index was created using the normalized difference between reflectance values at these two wavelengths. Using this index a robust estimation equation (R2=0.91) was established with laboratory measurements of soil salinity. The derived estimation equation can provide quantitative estimates of soil salinity at an early stages across a variety of soil types. Our proposed method would significantly contribute to soil restoration by providing a means to take countermeasures before the situation of soil salinity gets worse and irreversible.

Compositional characterisation of the pinnacles vicarious calibration site

Earth Observation (EO) satellite data are the single most important and richest source of environmental information for Australia. It is expected that future imaging spectroscopy satellites will be important for Australia for accessing critical information for managing natural and non-renewable resources, such as dry plant matter and mineralogy, which are currently difficult to access. Research and development has been undertaken by CSIRO to find an appropriate site to set up a vicarious calibration site aligned with Radiometric Calibration Network (RadCalNet) principles in response to a national need for calibration and validation of EO sensors. This paper reports specifically on the spatial and temporal compositional characteristics of the Pinnacles site using ASTER and Hyperion data.

An investigation into the use of the thermal wavelengths of the aster satellite borne sensor for dry vegetation identification

Since the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) was launched in 1999 the sensor has acquired an extensive coverage of the Earths surface. The ASTER archive has great potential for a variety of regional and continental scale studies. ASTER is particularly useful for geological applications with a number of mineralogical groups being able to be identified. Although a number of mineral groups can be identified using ASTER it is not capable of detecting, using bands in the VNIR/SWIR regions, dry vegetation. For geological mapping in semi arid environments where dry vegetation cover is significant (such as much of inland and northern Australia) this can confound, if left uncorrected, the interpretation of mineral information products derived from ASTER. Ideally a method of detecting, unmixing or filtering the dry vegetation component from the mineral information products is required. In an attempt to address this issue this paper looks at the thermal wavelength regions covered by ASTER to assess whether dry vegetation can be identified using these wavelength ranges.

Mapping of soil salinity using an airborne hyperspectral sensor in Western Australia

The goal of this study was the quantitative mapping of soil salinity from soil reflectance spectroscopy using airborne and/or spaceborne optical data. Generally, the reflectance spectra of agricultural lands contain a mixture of information of soil and vegetation. In addition, the spectra observed at the sensor are affected by the atmosphere and the aspect of topography. In this study, we corrected for atmospheric effects using the Second order derivative algorithm (SODA) method, which canceled the effect of the differences due to topography, and removed the effect of vegetation, to obtain pure soil spectra and estimate the degree of soil salinity. The soil salinity estimation map was found to correspond well to the electrical conductivity (EC) values that were used for validation. These validation results show that this method is effective for the estimation of soil salinity regardless of soil color and topography.

Assessment of acid sulfate soil using hyperspectral data in South Yunderup, Western Australia

Acid sulphate soils (ASS) are harmful to the environment, but it is detectable because they contain secondary iron bearing minerals which have diagnostic spectral features in reflectance spectral ranges, and these iron bearing minerals have indicative nature to reflect the pH conditions when they form, thus make ASS assessable via hyperspectral sensing. The extent and severity of ASS were mapped on the airborne remotely sensed imagery HyMap based on the mapping of indicative iron bearing minerals and the utilizing the relationship between these minerals and soil pHs. While, the distribution of ASS in subsurface was estimated by proximal hyperspectral instrument Hylogger™ and soil coring. Therefore, a comprehensive assessment of ASS both on the surface and in the subsurface was acquired and could be useful to further predict and monitor the ASS evolution.