ORCID Profile
0000-0003-2599-1392
Current Organisation
University of Queensland
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Agriculture land and farm management | Agricultural spatial analysis and modelling | Crop and pasture improvement (incl. selection and breeding) |
Publisher: Elsevier BV
Date: 03-2018
Publisher: Trans Tech Publications, Ltd.
Date: 04-2015
DOI: 10.4028/WWW.SCIENTIFIC.NET/AMR.1096.572
Abstract: Abstract This paper presents the effect of random inclusion of palm fibers on strength characteristics of Shanghai cohesive soil. Locally available cohesive soil (CL) is used as medium and palm fibers with three lengths (l = 6, 12 and 18 mm) are used as reinforcement. Soil is compacted with standard Proctor’s maximum density with low percentage of reinforcement (0–1% by weight of oven-dried soil). Direct shear tests, unconfined compression tests and CBR tests were conducted on un-reinforced as well as reinforced soil to investigate the strength characteristics of fiber-reinforced soil. The test results reveal that the inclusion of randomly distributed palm fibers in soil increases peak and residual shear strength, unconfined compressive strength and CBR value of soil. It is noticed that the optimum fiber content for achieving maximum strength is 0.6–0.8% of the weight of oven-dried soil for fiber length 12 mm.
Publisher: Elsevier BV
Date: 2021
Publisher: Wiley
Date: 11-2018
Publisher: Wiley
Date: 05-11-2022
DOI: 10.1111/SUM.12666
Abstract: The soil in the sugarcane growing area of far north Queensland is often sodic (exchangeable sodium percentage—ESP 6%). Gypsum therefore needs to be applied to reduce potential for land degradation. To accurately map ESP, a digital soil map (DSM) approach can be used. In this paper, we compare and contrast various aspects of DSM for mapping topsoil (0–0.3 m) ESP, including a suitable model (i.e. linear mixed model (LMM), Cubist and regression kriging (Cubist‐RK)), usefulness of digital data (in combination or alone) and how many calibration data (i.e. n = 20, 30,…120) are required. We compare these with ordinary kriging (OK) of soil data and using prediction agreement (i.e. Lin's concordance—Lin's) and accuracy (root mean squared error—RMSE). We compare all of these results with a DSM derived from numerical clustering (fuzzy K‐mean—FKM) of digital data to identify management zones ( k = 2, 3, 4 and 5) and a conventional Soil Order map ( k = 5 Orders). We do this by calculating mean squared prediction error (MSPE). Prediction of topsoil ESP by OK using 120 s les gave moderate agreement (Lin's = 0.72) with accuracy satisfactory given RMSE (3.69) was less than half standard deviation of measured ESP (½ SD = 3.75). Moreover, a minimum number of 100 s les would be required for OK. However, when digital data were used to value add to soil data in models, the results were equivocal, given Cubist (Lin's = 0.74) and Cubist‐RK (0.79) outperformed OK, while LMM (0.65) was inferior to OK. In addition, a smaller s le size (i.e. 70 and 60, respectively) was enough for Cubist and Cubist‐RK to permit the development of accurate predictions of ESP given the RMSE was less than ½ SD of measured ESP. Prediction of ESP (considering 120 s les) using only the γ‐ray data (Lin's = 0.77) was superior to EC a (0.72), however, using both in combination was best (0.79). The MSPE ( n = 120) indicated creating DSM from clustering of digital data was best for k = 4 zones (MSPE = 27.60) however, Cubist‐RK (13.40), Cubist (14.75), OK (15.56) and LMM (15.76) were able to provide better prediction of ESP. Nevertheless, all DSM generated smaller MSPE than a conventional Soil Order map (32.33). We recommend using Cubist‐RK and both digital data, is the optimal approach to develop a DSM for application of gypsum to enable implementation of Six‐Easy‐Steps soil management guidelines for Proserpine.
Publisher: Frontiers Media SA
Date: 10-05-2022
DOI: 10.3389/FEART.2022.902444
Abstract: With the rapid development of the economy and society in recent years, the ecological environment has deteriorated significantly. The governments at all levels, departments, and relevant scholars have begun to pay attention to urban ecological construction and research on urban disaster prevention and mitigation. The concept of resilience has gained widespread attention in this context. However, at present, urban ecological resilience research is still in its infancy, and there are many qualitative but few quantitative studies in terms of assessment methods. This study explores the complex dynamic evolution mechanism of urban ecosystem resilience based on the three resilience characteristics and selects Nanchang, an important ecological barrier in the middle and lower reaches of the Yangtze River and a model area for integrated management of the Great Lakes basin, as an assessment target. This study establishes a quantitative measurement and evaluation framework for urban ecological resilience in three dimensions (resistance, adaptation, and vitality) and conducts a comprehensive evaluation of urban ecosystem resilience. The results show that the trend of land-use change from 1990 to 2020 is mainly characterized by the continuous decrease in arable land and ecological land (forestland, grassland, and water) and the continuous increase in construction land, among which the land-use dynamic attitude of construction land is the largest, reaching 5.33% from 1990 to 2005. During the study period, the overall ecosystem resilience of Nanchang showed a gradual decline and was always at a moderate-to-low level, with a long-term distribution pattern of “low in the middle and high in the surrounding areas” and clear spatial heterogeneity. This study helps clarify the security status of the regional ecosystem and provides a reference for exploring the complex dynamic evolution mechanism of ecological resilience.
Publisher: Elsevier BV
Date: 2021
Publisher: Elsevier BV
Date: 07-2019
Publisher: Elsevier BV
Date: 11-2015
Publisher: Springer Science and Business Media LLC
Date: 07-11-2021
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 02-2022
Publisher: Informa UK Limited
Date: 2017
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 09-2022
Publisher: Elsevier BV
Date: 06-2021
Publisher: MDPI AG
Date: 12-09-2019
DOI: 10.3390/S19183936
Abstract: Most cultivated upland areas of northeast Thailand are characterized by sandy and infertile soils, which are difficult to improve agriculturally. Information about the clay (%) and cation exchange capacity (CEC—cmol(+)/kg) are required. Because it is expensive to analyse these soil properties, electromagnetic (EM) induction instruments are increasingly being used. This is because the measured apparent soil electrical conductivity (ECa—mS/m), can often be correlated directly with measured topsoil (0–0.3 m), subsurface (0.3–0.6 m) and subsoil (0.6–0.9 m) clay and CEC. In this study, we explore the potential to use this approach and considering a linear regression (LR) between EM38 acquired ECa in horizontal (ECah) and vertical (ECav) modes of operation and the soil properties at each of these depths. We compare this approach with a universal LR relationship developed between calculated true electrical conductivity (σ—mS/m) and laboratory measured clay and CEC at various depths. We estimate σ by inverting ECah and ECav data, using a quasi-3D inversion algorithm (EM4Soil). The best LR between ECa and soil properties was between ECah and subsoil clay (R2 = 0.43) and subsoil CEC (R2 = 0.56). We concluded these LR were unsatisfactory to predict clay or CEC at any of the three depths, however. In comparison, we found that a universal LR could be established between σ with clay (R2 = 0.65) and CEC (R2 = 0.68). The LR model validation was tested using a leave-one-out-cross-validation. The results indicated that the universal LR between σ and clay at any depth was precise (RMSE = 2.17), unbiased (ME = 0.27) with good concordance (Lin’s = 0.78). Similarly, satisfactory results were obtained by the LR between σ and CEC (Lin’s = 0.80). We conclude that in a field where a direct LR relationship between clay or CEC and ECa cannot be established, can still potentially be mapped by developing a LR between estimates of σ with clay or CEC if they all vary with depth.
Publisher: Elsevier BV
Date: 07-2017
Publisher: Elsevier BV
Date: 10-2019
Publisher: Informa UK Limited
Date: 21-07-2016
Publisher: Elsevier BV
Date: 10-2021
Publisher: Elsevier BV
Date: 11-2022
Publisher: Springer Science and Business Media LLC
Date: 20-09-2022
Publisher: Elsevier BV
Date: 10-2015
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 07-2019
Publisher: Elsevier BV
Date: 12-2018
Publisher: Springer International Publishing
Date: 31-07-2020
Publisher: Frontiers Media SA
Date: 22-06-2022
Abstract: While there have been various studies on global vegetation dynamics, limited studies have been conducted to understand vegetation changes in arid areas. Vegetation distribution patterns can be affected by multiple factors, so understanding their interactions can help improve the capability of predicting future vegetation dynamics. This study, therefore, analyzed the dynamic vegetation changes in Alxa League, China, using the Normalized Difference Vegetation Index (NDVI) dataset (2000–2019), with the consideration of land cover types, digital elevation model, air temperature, precipitation, soil moisture, total evaporation, and air quality. The results show that the NDVI in Alxa League is small. Before 2012, the NDVI value fluctuated, while after 2012, the NDVI value dropped sharply and then slowly recovered after 2015. High NDVI values were found in areas with high and frequent human activities (city centers). The NDVI in the northwest region showed a slight degradation trend, and the southeast showed a slight improvement trend. According to the land cover type analysis, the NDVI value was the largest when the land cover type was tree cover, and the NDVI value was the smallest when the land cover type was bare/sparse vegetation. Alxa League was dominated by a bare/sparse vegetation distribution. The terrain analysis indicates that when the height was between 1800 and 3492 m, the NDVI value was the highest, and high NDVI values were mainly distributed in the area with a slope & 25°. When the slope was flat, the NDVI value was the smallest. Considering climate factors, the NDVI was negatively correlated with air temperature, precipitation, soil moisture, and total evaporation in space, and only precipitation and soil moisture were positively correlated in time. Moreover, the population size has a strong positive correlation with the NDVI in this area. The monthly variation of the NDVI and absorbable particulate matter (PM 10 ) was negatively correlated, i.e., strongly negatively correlated in spring, summer, and autumn, but only weakly positively correlated in winter. The seasonal variation of the NDVI was as follows: summer & autumn & spring & winter, and the seasonal variation of PM 10 was spring & winter & summer & autumn. The interannual variation of the NDVI and PM 10 was positively correlated. This suggests that the absorbable particulate matter (PM 10 ) may be an essential factor for the normalized vegetation index to underestimate the dynamic changes of vegetation in arid regions. This study provides a theoretical basis for the dynamic changes of vegetation in the dry Alxa League.
Publisher: Elsevier BV
Date: 10-2019
Publisher: Wiley
Date: 20-07-2020
DOI: 10.1002/LDR.3684
Publisher: Elsevier BV
Date: 10-2016
DOI: 10.1016/J.SCITOTENV.2016.06.056
Abstract: To improve soil texture and structure, techniques associated with physical, biological or chemical aspects are generally adopted, among which diatomite is an important soil conditioner. However, few studies have been conducted to investigate the physical, hydraulic and tillage performance of diatomite-improved soils. Consistency limits and compaction properties were investigated in this study, and several performance indicators were compared, such as the liquid limit, plastic limit and compactability, of silt, silt loam and silty-clay loam soils to which diatomite was added at volumetric ratios of 0%, 10%, 20%, and 30%. The results showed that diatomite significantly (p<0.05) improved the consistency limits, with the most preferred effects in the silt soil. The liquid limits were increased by 53.9%, 27.3%, and 14.7%, in the silt, silt loam and silty-clay loam soils, respectively, when the volumetric ratio was 30%. While diatomite lowered the maximum dry bulk density (MBD) of the classified soils, the optimum moisture content (OMC) was increased overall. The trend was consistent with the proportion of diatomite, and MBD decreased by 8.7%, 10.3%, and 13.2% in the silt, silt loam and silty-clay loam soils when 30% diatomite was mixed, whereas OMC increased by 28.7%, 22.4%, and 25.3%, respectively. Additionally, aggregate stability was negatively correlated with MBD but positively correlated with OMC. Diatomite exerts positive effects on soil mechanical strength, suggesting that soils from sludge farms are more tillable with a larger stabilized and workable matrix.
Publisher: Elsevier BV
Date: 03-2021
Start Date: 11-2023
End Date: 11-2026
Amount: $457,906.00
Funder: Australian Research Council
View Funded Activity