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Добірка наукової літератури з теми "Remote sensing South Australia Adelaide"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 19 лютого 2022

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Статті в журналах з теми "Remote sensing South Australia Adelaide"

1

Bailey, Adam, Rosalind King, Simon Holford, Joshua Sage, Guillaume Backe, and Martin Hand. "Remote sensing of subsurface fractures in the Otway Basin, South Australia." Journal of Geophysical Research: Solid Earth 119, no. 8 (August 2014): 6591–612. http://dx.doi.org/10.1002/2013jb010843.

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2

GIESBRECHT, J. "AN EMPIRICAL STUDY OF THE PROBABILITY DENSITY FUNCTION OF HF NOISE (PART II)." Fluctuation and Noise Letters 08, no. 03n04 (December 2008): L305—L314. http://dx.doi.org/10.1142/s0219477508005008.

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The impetus for investigating the probability density function of high-frequency (HF) noise arises from the requirement for a better noise model for automatic modulation recognition techniques. Many current modulation recognition methods still assume Gaussian noise models for the transmission medium. For HF communications this can be an incorrect assumption. Whereas a previous investigation [1] focuses on the noise density function in an urban area of Adelaide Australia, this work studies the noise density function in a remote country location east of Adelaide near Swan Reach, South Australia. Here, the definition of HF noise is primarily of natural origins – it is therefore impulsive – and excludes man-made noise sources. A new method for measuring HF noise is introduced that is used over a 153 kHz bandwidth at various frequencies across the HF band. The method excises man-made signals and calculates the noise PDF from the residue. Indeed, the suitability of the Bi-Kappa distribution at modeling HF noise is found to be even more compelling than suggested by the results of the earlier investigation.

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3

Hewson, R., D. Robson, A. Carlton, P. Gilmore, and Louis-Noel Moresi. "Geological application of ASTER remote sensing within sparsely outcropping terrain, Central New South Wales, Australia." Cogent Geoscience 3, no. 1 (January 1, 2017): 1319259. http://dx.doi.org/10.1080/23312041.2017.1319259.

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4

Power, Hannah E., Michael A. Kinsela, Caio E. Stringari, Murray J. Kendall, and David J. Hanslow. "WAVE OVERWASH ON A ROCK PLATFORM: REMOTE SENSING AND PRESSURE SENSOR OBSERVATIONS." Coastal Engineering Proceedings, no. 36 (December 30, 2018): 29. http://dx.doi.org/10.9753/icce.v36.waves.29.

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Open ocean rocky shore platforms are typically exposed to high wave energy and are often the location of recreational activities from sightseeing and walking to fishing (Kennedy et al. 2017). The exposure of these environments, combined with the use for recreation, results in a high level of risk for those who use the rock platform. In Australia, for example, 19% of coastal fatalities occur on rock coasts, most commonly when individuals fall from microtidal semi-horizontal platforms into the ocean (SLSA, 2014a,b). Managing the hazards and resultant risk on rocky shore platforms requires a different approach to that taken for sandy beaches as the sites are typically remote. Here we explore the wave overwash hazards on a remote but high visitation rocky shore platform 40 km south of Sydney, Australia.

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5

Van Niel, Thomas G., and Tim R. McVicar. "Determining temporal windows for crop discrimination with remote sensing: a case study in south-eastern Australia." Computers and Electronics in Agriculture 45, no. 1-3 (December 2004): 91–108. http://dx.doi.org/10.1016/j.compag.2004.06.003.

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6

Aravena, Ricardo A., Mitchell B. Lyons, Adam Roff, and David A. Keith. "A Colourimetric Approach to Ecological Remote Sensing: Case Study for the Rainforests of South-Eastern Australia." Remote Sensing 13, no. 13 (June 29, 2021): 2544. http://dx.doi.org/10.3390/rs13132544.

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To facilitate the simplification, visualisation and communicability of satellite imagery classifications, this study applied visual analytics to validate a colourimetric approach via the direct and scalable measurement of hue angle from enhanced false colour band ratio RGB composites. A holistic visual analysis of the landscape was formalised by creating and applying an ontological image interpretation key from an ecological-colourimetric deduction for rainforests within the variegated landscapes of south-eastern Australia. A workflow based on simple one-class, one-index density slicing was developed to implement this deductive approach to mapping using freely available Sentinel-2 imagery and the super computing power from Google Earth Engine for general public use. A comprehensive accuracy assessment based on existing field observations showed that the hue from a new false colour blend combining two band ratio RGBs provided the best overall results, producing a 15 m classification with an overall average accuracy of 79%. Additionally, a new index based on a band ratio subtraction performed better than any existing vegetation index typically used for tropical evergreen forests with comparable results to the false colour blend. The results emphasise the importance of the SWIR1 band in discriminating rainforests from other vegetation types. While traditional vegetation indices focus on productivity, colourimetric measurement offers versatile multivariate indicators that can encapsulate properties such as greenness, wetness and brightness as physiognomic indicators. The results confirmed the potential for the large-scale, high-resolution mapping of broadly defined vegetation types.

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7

Hwang, Charnsmorn, Chih-Hua Chang, Michael Burch, Milena Fernandes, and Tim Kildea. "Effects of Epiphytes and Depth on Seagrass Spectral Profiles: Case Study of Gulf St. Vincent, South Australia." International Journal of Environmental Research and Public Health 16, no. 15 (July 29, 2019): 2701. http://dx.doi.org/10.3390/ijerph16152701.

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Seagrasses are a crucial indicator species of coastal marine ecosystems that provide substratum, shelter, and food for epiphytic algae, invertebrates, and fishes. More accurate mapping of seagrasses is essential for their survival as a long-lasting natural resource. Before reflectance spectra could properly be used as remote sensing endmembers, factors that may obscure the detection of reflectance signals must be assessed. The objectives in this study are to determine the influence of (1) epiphytes, (2) water depth, and (3) seagrass genus on the detection of reflectance spectral signals. The results show that epiphytes significantly dampen bottom-type reflectance throughout most of the visible light spectrum, excluding 670–679 nm; the depth does influence reflectance, with the detection of deeper seagrasses being easier, and as the depth increases, only Heterozostera increase in the exact “red edge” wavelength at which there is a rapid change in the near-infrared (NIR) spectrum. These findings helped improve the detection of seagrass endmembers during remote sensing, thereby helping protect the natural resource of seagrasses.

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8

Hunter, John. "Grasslands on Coastal Headlands in New South Wales, south eastern Australia." Vegetation Classification and Survey 1 (June 16, 2020): 111–22. http://dx.doi.org/10.3897/vcs/2020/48228.

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Aims: To use unsupervised techniques to produce a hierarchical classification of grasslands on coastal headlands of New South Wales in eastern Australia. Methods: A dataset of 520 vegetation plots scored on cover and placed across grasslands on coastal headlands (ca. 2000 km of coastline). Vegetation assemblages were identified with the aid of a clustering method based on group averaging and tested using similarity profile analysis (SIMPROF) using Bray-Curtis similarity. A hierarchical schema was developed based on EcoVeg hierarchy and was circumscribed using positive and negative diagnostic taxa via similarity percentage analysis (SIMPER) and importance based on summed cover scores and frequency. Mapping the occurrences grasslands was initially constructed using remote sensing which was verified and modified with on ground observations. Results: One group Themeda – Pultenaea – Zoysia – Cynodon grasslands and heathy grasslands was defined to include all coastal headland grassland vegetation of the New South Wales, and within this, three alliances and ten associations. Only one of the circumscribed associations is represented within the current state classification schema. In total 107 ha were mapped of which 68 ha occurred within secure conservation tenure. Conclusions: A number of unique and rare grassland assemblages on coastal headlands have to date gone undescribed. The most common alliance constitutes approximately 87% of extant grassland occurrences but is currently the only type listed as endangered and afforded protection. Although Poa spp. are listed as a threat to Themeda dominated assemblages on headlands data from this study suggest that this is unlikely to be the case. Taxonomic reference: PlantNET (http://plantnet/10rbgsyd.nsw.gov.au/; accessed June 2019). Abbreviations: BC Act = Biodiversity Conservation Act; NMDS = non-metric multidimensional scaling; NSW = New South Wales; PCT = Plant Community Type; SIMPER = similarity percentage analysis; SIMPROF = Similarity profile analysis.

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9

Ahmed, Alaa, Abdullah Alrajhi, and Abdulaziz S. Alquwaizany. "Identification of Groundwater Potential Recharge Zones in Flinders Ranges, South Australia Using Remote Sensing, GIS, and MIF Techniques." Water 13, no. 18 (September 17, 2021): 2571. http://dx.doi.org/10.3390/w13182571.

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In Australia, water resource management is a major environmental, biological, and socio-economic issue, and will be an essential component of future development. The Hawker Area of the central Flinders Ranges, South Australia suffers from a lack of reliable data to help with water resource management and decision making. The present study aimed to delineate and assess groundwater recharge potential (GWRP) zones using an integration between the remote sensing (RS), geographic information system (GIS), and multi-influencing factors (MIF) approaches in the Hawker Area of the Flinders Ranges, South Australia. Many thematic layers such as lithology, drainage density, slope, and lineament density were established in a GIS environment for the purpose of identifying groundwater recharge potential zones. A knowledge base ranking from 1 to 5 was assigned to each individual thematic layer and its categories, depending on each layer’s importance to groundwater recharge potential zones. All of the thematic layers were integrated to create a combined groundwater potential map of the study area using weighting analysis in ArcGIS software. The groundwater potential zones were categorized into three classes, good, moderate, and low. The resulting zones were verified using available water data and showed a relative consistency with the interpretations. The findings of this study indicated that the most effective groundwater potential recharge zones are located where the lineament density is high, the drainage density is low, and the slope is gentle. The least effective areas for groundwater recharge are underlain by shale and siltstone. The results indicated that there were interrelationships between the groundwater recharge potential factors and the general hydrology characteristics scores of the catchment. MIF analysis using GIS mapping techniques proved to be a very useful tool in the evaluation of hydrogeological systems and could enable decision makers to evaluate, better manage, and protect a hydrogeological system using a single platform.

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10

Gibson, Rebecca, Tim Danaher, Warwick Hehir, and Luke Collins. "A remote sensing approach to mapping fire severity in south-eastern Australia using sentinel 2 and random forest." Remote Sensing of Environment 240 (April 2020): 111702. http://dx.doi.org/10.1016/j.rse.2020.111702.

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Більше джерел

Дисертації з теми "Remote sensing South Australia Adelaide"

1

Arkun, Sedat. "Hyperspectral remote sensing and the urban environment : a study of automated urban feature extraction using a CASI image of high spatial and spectral resolution." Title page, contents, research aims and abstract only, 1999. http://web4.library.adelaide.edu.au/theses/09ARM/09arma721.pdf.

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Coppa, Isabel Patricia Maria, and Isabel coppa@csw com au. "The use of remote sensing data for broad acre grain crop monitoring in Southeast Australia." RMIT University. Mathematical and Geospatial Sciences, 2006. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070201.095831.

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In 2025, there will be almost 8 billion people to feed as the worlds population rapidly increases. To meet domestic and export demands, Australian grain productivity needs to approximately triple in the next 20 years, and this production needs to occur in an environmentally sustainable manner. The advent of Hi-tech Precision Farming in Australia has shown promise in recent time to optimize the use of resources. Most

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3

Lau, Ian Christopher. "Regolith-landform and mineralogical mapping of the White Dam Prospect, eastern Olary Domain, South Australia, using integrated remote sensing and spectral techniques." Title page, abstract and table of contents only, 2004. http://hdl.handle.net/2440/37972.

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The research contained within this thesis was directed at examining the spectral properties of regolith-dominated terrains using airborne and proximal hyperspectral instruments. The focus of the investigation was to identify the mineralogy of the regolith and determine if surficial materials were indicative of the underlying bedrock in the regolithdominated terrain of the eastern Olary Domain, South Australia. The research area was constrained to a 250 km2 area around the Cu-Au mineralisation of the White Dam Prosect. Integrated remote sensing, using airborne hyperspectral datasets (HyMap), Landsat imagery and gamma-ray spectroscopy data, was performed to map regolith-landforms and extract information on surficial materials. Detailed calibration of the HyMap dataset, using a modified model-based/empirical line calibration technique, was required prior to information extraction. The White Dam area was able to be divided into: alluvial regolith-dominated; in situ regolith-dominated; and bedrock-dominated terrains, based on mineralogical interpretations of the regolith, using the remotely sensed hyperspectral data. Alluvial regions were characterised by large abundances of vegetation and soils with a hematite-rich mineralogy. Highly weathered areas of in situ material were discriminated by the presence of goethite and kaolinite of various crystallinities, whereas the bedrock-dominated regions displayed white mica-/muscovite-rich mineralogy. Areas flanking bedrock exposures commonly consisted of shallow muscovite-rich soils containing regolith carbonate accumulations. Traditional mineral mapping processes were performed on the HyMap data and were able to extract endmembers of regolith and other surficial materials. The Mixture Tuned Matched Filter un-mixing process was successful at classifying regolith materials and minerals. Spectral indices performed on masked data were effective at identifying the key regolith mineralogical features of the HyMap imagery and proved less time consuming than un-mixing processes. Processed HyMap imagery was able to identify weathering halos, highlighted in mineralogical changes, around bedrock exposures. Proximal spectral measurements and XRD analyses of samples collected from the White Dam Prospect were used to create detailed mineralogical dispersion maps of the surface and costean sections. Regolith materials of the logged sections were found to correlate with the spectrally-derived mineral dispersion profiles. The HyLogger drill core scanning instrument was used to examine the mineralogy of the fresh bedrock, which contrasted with the weathering-derived near-surface regolith materials. The overall outcomes of the thesis showed that hyperspectral techniques were useful for charactering the mineralogy of surficial materials and mapping regolith-landforms.
Thesis (Ph.D.)--School of Earth & Environmental Sciences, 2004.

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4

Lau, Ian Christopher. "Lithological, structural and lineament analysis of the Southern Mount Lofty Ranges, South Australia, using remote sensing and geographical information system techniques /." Title page, contents and abstract only, 2000. http://web4.library.adelaide.edu.au/theses/09SB/09sbl3662.pdf.

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5

Mahoney, Sean Douglas. "Remote sensing techniques for geological and regolith mapping, interpretations in basement rock and thinly covered terrains adjacent to the Tarcoola mine site, north-western South Australia /." Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09SB/09sbm2165.pdf.

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6

McCloy, K. R. (Keith R. ). "Development and evaluation of a remote sensing algorithm suitable for mapping environments containing significant spatial variability : with particular reference to pastures." 1987. http://web4.library.adelaide.edu.au/theses/09PH/09phm127.pdf.

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7

McCloy, Keith R. "Development and evaluation of a remote sensing algorithm suitable for mapping environments containing significant spatial variability : with particular reference to pastures / by Keith R. McCloy." 1987. http://hdl.handle.net/2440/18902.

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Includes bibliographical references (leaves 176-179)
xiii, 202 leaves : ill. (some col.) ; 30 cm.
Title page, contents and abstract only. The complete thesis in print form is available from the University Library.
Thesis (Ph.D.)--University of Adelaide, 1989

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Книги з теми "Remote sensing South Australia Adelaide"

1

International Geoscience and Remote Sensing Symposium (2001 Sydney, Australia). IGARSS 2001: Proceedings : IEEE 2001 International Geoscience and Remote Sensing Symposium : Scanning the present and resolving the future : 9-13 July, 2001, University of New South Wales, Sydney, Australia. Piscataway, New Jersey: IEEE, 2001.

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Частини книг з теми "Remote sensing South Australia Adelaide"

1

Hewson, Robert, and Thomas Cudahy. "Issues Affecting Geological Mapping with ASTER Data: A Case Study of the Mt Fitton Area, South Australia." In Land Remote Sensing and Global Environmental Change, 273–300. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6749-7_13.

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2

Fraser, David. "Mapping Areas Susceptible to Soil Salinity in the Irrigation Region of Southern New South Wales, Australia." In Remote Sensing of Soil Salinization. CRC Press, 2008. http://dx.doi.org/10.1201/9781420065039.pt2.

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Тези доповідей конференцій з теми "Remote sensing South Australia Adelaide"

1

Zhu, Qinggaozi, Xihua Yang, and Qiang Yu. "Climate change impact on bushfire risk in New South Wales, Australia." In IGARSS 2015 - 2015 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2015. http://dx.doi.org/10.1109/igarss.2015.7326042.

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2

Shi, Xianzhong, Mehrooz Aspandiar, and Ian C. Lau. "Assessment of acid sulfate soil using hyperspectral data in South Yunderup, Western Australia." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723790.

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3

Bierman, Paul, Megan Lewis, Jason Tanner, and Bertram Ostendorf. "Understanding Phytoplankton Variability Throughout Spencer Gulf, South Australia, via Satellite Derived Chlorophyll-A." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779869.

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4

Mengen, Carl, Fabrice Marre, and Tishampati Dhar. "Accuracy assessment of the first high-resolution IFSAR campaign over the coorong region of South Australia." In 2009 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5417445.

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5

Abuzar, M., D. Whitfield, A. McAllister, G. Lamb, K. Sheffield, and M. O'Connell. "Satellite remote sensing of crop water use in an irrigation area of south-east Australia." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6723525.

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6

Rudiger, Christoph, Alessandra Monerris, David McJannet, Luigi Renzullo, Mariette Vreugdenhil, and Wolfgang Wagner. "Comparison of Different High-Resolution Soil Moisture Products Across an Agricultural Landscape in South-Eastern Australia." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518208.

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7

Benger, Simon N. "Remote sensing of invasive tubeworm reefs in the Coorong and Lower Lakes of South Australia." In 2010 3rd International Congress on Image and Signal Processing (CISP). IEEE, 2010. http://dx.doi.org/10.1109/cisp.2010.5647966.

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8

Rahman, Shahriar, Hsing-Chung Chang, Christina Magill, Kerrie Tomkins, and Warwick Hehir. "Spatio-Temporal Assessment of Fire Severity and Vegetation Recovery Utilising Sentinel-2 Imagery in New South Wales, Australia." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8899242.

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9

Ge, Linlin, Xiaojing Li, and Alex Hay-Man Ng. "UAV for mining applications: A case study at an open-cut mine and a longwall mine in New South Wales, Australia." In IGARSS 2016 - 2016 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2016. http://dx.doi.org/10.1109/igarss.2016.7730412.

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10

Hewson, R. D., G. R. Taylor, and L. B. Whitbourn. "Application of TIR Imagery and Spectroscopy for the Extraction of Soil Textural Information at Fowlers Gap, Western New South Wales, Australia." In IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779095.

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