Dissertations / Theses on the topic 'Remote sensing South Australia'
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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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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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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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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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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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Siddiqi, Muhammad Junaid. "Remote sensing and GIS techniques for monitoring and predicting land degradation and impacts of engineering solutions in an area." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/2427.
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Salinity, waterlogging and drought are major causes of land degradation and serious threats to sustainable agricultural productivity in the south-west agricultural region of Western Australia (WA). The spectral signatures of pasture plants under drought, waterlogging and nutrient deficiency were examined in a greenhouse study using both a field and an analytical laboratory spectrometer (400 to 2,500 nm wavelength). Drought stress group (RWC, 39.9%) has the highest reflectance of 48.2%, waterlogging group (RWC, 49.7%) with a magnitude of 43.1% reflectance and control group (RWC, 61.5%) has the lowest of 41.9%. The highest separability based on magnitude among control, waterlogging and drought stress groups is located at reflection band at 1,666 nm, 1,818 nm and 2,216 nm and at 1,450 nm absorption bands. Remote sensing and GIS techniques were used to predict risks of soil salinity and waterlogging in the study area. Time-sequenced Landsat TM satellite data and groundwater data were analysed to delineate areas where major changes in soil salinity, waterlogging have taken place before and after engineering interventions of deep drains.The rainfall data analysis of all cities in the south-west of Western Australia indicate that annual rainfall has been decreasing since 1969 for some cities in the region and rainfall is decreasing in some cities since 1975. The winter season rainfall shows a downward trend and summer season rainfall shows an upward trend linked to an increase in the frequency of summer storm events in the south-west, in the Wheatbelt and in the east of Western Australia. The annual rainfall and summer season rainfalls have been increasing in the north of Western Australia and both annual rainfall and summer season rainfalls show an increasing trend. Climate change was studied for northern, eastern, Wheatbelt and south-west of WA and its impacts of on surface runoff, groundwater recharge, and land degradation were studied.Deep open drains were monitored in the two major drainage districts of Narembeen and Dumbleyung in Wheatbelt of Western Australia. The efficacy of drains in mitigating the problems of waterlogging and salinity in the area was studied. Information on monitoring of drains in six coastal districts in Western Australia, from Australia and other countries was collated and a coastal drainage best management practices ‘BMP Toolbox’ has been developed.
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Dufbäck, Emma. "Nitrogen Uptake by Vegetation in the Wakkerstroom Wetland, South Africa." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-389981.
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The lack of proper wastewater treatment inhibits the social and economic development in many communities. The South African town Wakkerstroom is an example where wastewater is first treated before it is released. Due to the lack of technical expertise and funding to manage the sewage disposal system, a large part of the wastewater goes directly, without any treatment, into a stream feeding the Wakkerstroom wetland. The wetland purifies the wastewater and provides clean water downstream, thus is indispensable for its detoxification capacity. One relatively cheap method to determine the absorption capacity of a wetland with respect to nitrogen loading is to investigate the nitrogen uptake by the wetland vegetation. In this study, the nitrogen uptake of the vegetation in the Wakkerstroom wetland during the growing seasons between the years 2000-2018 was investigated by using harvested biomass and its nitrogen content as a proxy. The interannual variability of Net Primary Production (NPP) was calculated using a Light Use Efficiency (LUE) model for the period 2000-2018. The NPP derived with LUE-modelling was compared to NPP based on an end-of season harvest of biomass in March 2019. The nitrogen content and carbon and nitrogen (C:N) ratio were determined in the harvested biomass by carbon and nitrogen content analysis. The annual nitrogen uptake of the growing seasons between the years 2000-2018 was subsequently determined by multiplying the calculated NPP by the fraction of nitrogen found in the harvested material. The NPPtot based on harvested biomass (NPPharvest) towards the end of the growing season 2018/2019 was estimated to be 2.01 kg‧m-2‧season-1. The NPPtot calculated from LUE modelling (NPPLUE) varied between 0.49-1.64 kg‧m-2 for the growing seasons between 2000-2018. NPPharvest was between 1.2-4 times higher compared to NPPLUE, probably due to overestimation of NPPharvest because of biomass sampling of more than one-year production, or underestimation of NPPLUE due to a low maximum radiation conversion efficiency factor, εmax. The community mean nitrogen (N) content found in the biomass harvested aboveground was 1.29 % for the Phragmites community and 1.00 % for the Typha community. The nitrogen uptake of the vegetation was estimated to vary between 6.10-20.5 g N∙m-2 per growing season between the years 2000-2018.Bristen på adekvata reningstekniker för att behandla avloppsvatten hämmar den sociala och ekonomiska utvecklingen i många samhällen. Den sydafrikanska staden Wakkerstroom är ett exempel där avloppsvatten först renas innan det släpps ut. På grund av brisen på teknisk kompetens och finansiering att hantera reningsverket som avlägsnar avloppsvatten så läcker en stor del av det orenade avloppsvattnet ut i en våtmark i Wakkerstroom via en närliggande å. Våtmarken är av regional betydelse för sin reningskapacitet då den renar avloppsvattnet och förser användare nedströms med rent vatten. En viktig aspekt för att bestämma en våtmarks reningskapacitet med avseende på kväve (N) är att undersöka växternas kväveupptag i våtmarken. Kväveupptaget hos växterna i våtmarken i Wakkerstroom under växtsäsongerna mellan år 2000–2018 undersöktes genom att använda skördad biomassa och dess kväveinnehåll som proxy. Den årliga variabiliteten hos nettoprimärproduktionen (NPP) beräknades genom att använda en LUE (Light Use Efficiency)-modell för perioden 2000-2018. NPP framtaget med LUE-modellering jämfördes med NPP baserat på biomassa skördad i slutet av växtsäsongen i mars 2019. Kväveinnehållet och kol-kväve (C:N) kvoten bestämdes hos den skördade biomassan genom en kol- och kväveanalys. Det årliga kväveupptaget under växtsäsongerna mellan 2000–2018 togs därefter fram genom att multiplicera beräknad NPP med kvävefraktionen erhållen från den skördade biomassan. NPPtot framtaget med biomassa skördad i slutet av växtsäsongen 2018/2019 (NPPbiomassa) uppskattades vara 2,01 kg‧m-2‧säsong-1. NPPtot beräknat med LUE-modellering (NPPLUE) varierade mellan 0,49–1,64 kg‧m-2 under växtsäsongerna mellan år 2000–2018. NPPbiomassa var 1,2–4 gånger högre i jämförelse med NPPLUE, vilket troligtvis berodde på att NPPbiomassa överskattades på grund av att mer än en årsproduktion av biomassa skördades, eller för att NPPLUE underskattades på grund av ett för lågt värde på den maximala effektivitetsfaktorn εmax valdes. Medelvärdet för kväveinnehållet erhållen i biomassan skördad ovanför vattennivån var 1,29 % för Phragmites-samhället och 1,00 % för Typha-samhället. Kväveupptaget hos växterna varierade mellan 6,10–20,5 g N∙m-2 per växtsäsong mellan år 2000–2018.
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Gabell, Andrew R. "High-resolution remote sensing applied to mineral exploration in Australia /." Title page, and contents only, 1986. http://web4.library.adelaide.edu.au/theses/09PH/09phg1123.pdf.
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Quibell, G. E. "Remote sensing of algae in inland southern African waters." Thesis, Rhodes University, 1992. http://hdl.handle.net/10962/d1005440.
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Routine monitoring of algae in inland waters in southern Africa is a critical element in assessing the efficacy of eutrophication management options. Several authors have indicated that single point samples are not necessarily representative of conditions throughout the water body and some have suggested remote sensing as a means of overcoming this problem. Remote sensing of algae normally involves deriving the empirical relationship between radiance detected at a sensor, and contact sensed chlorophyll concentrations. Quantification of, or compensation for, contributions to the upwelling radiance other than that light reflected by the algae is critical for this approach. In southern Africa these contributions arise primarily from atmospheric effects and from scattering by sediments in the water. A review of the atmospheric correction models suggested that a cosine sun angle correction followed by dark pixel subtraction is the most feasible method to compensate for the former effects. Studies of the changes in upwelling radiance induced by addition of sediment to algal cultures indicated that subtraction of reflectance at ≈665nm from that at ≈700nm, may provide a means of compensating for the scattering by sediments. The disadvantage of this approach is that few sensor systems have narrow spectral bands centred at these wavelengths. Investigations of the nature of the reflectance from 5 algal species indicated that all had similar reflectance spectra, but the blue-green genera had a smaller peak at ≈650nm. Chlorophyll absorption at ≈665nm was evident by lower reflectance at this point, but the alga Microcystis sp. did not conform to the conceptual model of reflectance, in that reflectance at 665nm was higher at increased cell density. Spectra of natural waters confirmed the results obtained in the laboratory. Reflectance at ≈700nm showed the largest changes with increasing chlorophyll concentration and also had the highest correlations to chlorophyll concentrations. However, due to the strong absorption of these wavelengths by water, this reflectance peak only occurred when sufficient cells were found in the upper layers of water. Use of these wavelengths in remote sensing models should therefore be restricted to highly eutrophied waters. Although the reflectance spectra of different algae were similar, the amount of light scattered by each species (measured as turbidity) differed for any given chlorophyll concentration. This appeared to be due to the colonial nature of the cells and means that empirical models will be unique to the species on which they were developed. Comparisons of multispectral photography (MSP) and LANDSAT MSS imagery indicated the MSP data had higher correlations with chlorophyll concentrations than did the MSS data. Chlorophyll simulations from a test set of data using ordinary multiple regression showed that the MSP imagery had mean errors of 7.3M9/I, while that for the MSS imagery was 7.4M9/I. Similar tests using the canonical procedure produced larger mean errors of 9M9/I and 12M9/I for the MSP and MSS data respectively. This was due to the fact that the canonical procedure is not suitable for the spectral band widths of these sensors. In spite of similar simulation accuracies, the MSS imagery produced very patchy synoptic views. This was due to the lower variance (radiometric resolution) in the LANDSAT MSS data. This appears to be the most important criterion for accurate chlorophyll mapping in inland waters. Development of a single multidate algorithm for southern Africa is not yet feasible, and routine monitoring of chlorophyll using these techniques is impractical. However acceptable chlorophyll maps are possible if the model is recalibrated for each occasion and the sensor used has a high radiometric resolution.
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Marinelli, Marco Antonio. "An ocean colour remote sensing study of the phytoplankton cycle off Western Australia." Thesis, Curtin University, 2002. http://hdl.handle.net/20.500.11937/1782.
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The concentration of phytoplankton in waters off the Western Australian coastline contrast with the coastal waters west of southern Africa and South America. The lack of favourable upwelling conditions results in the majority of the southeastern Indian Ocean surface waters being nutrient poor. Which is reflected in their low productivity. Several areas either on or in close proximity to the coastline are notably more productive. The associated forcing terms generating phytoplankton favourable conditions differ between areas. as do the seasons in which they occur. Measurements of chlorophyll a concentration. the major photosynthetic pigment contained in phytoplankton, may be directly related to oceanic bioproductivity. Using data collected by the Coastal Zone Color Seamier between 1979-86, this work aims to improve the understanding of the spatial and temporal changes that occurred in chlorophyll a abundance in the southeastern Indian Ocean. The highest seasonal mean concentrations occur in Summer (January-March) and Autumn (April-June); the former occurring in waters of the North West Shelf and the latter in close coastal areas of Western Australia south of North West. Cape. Concentrations observed in the offshore oceanic regions are mostly poor. Exceptions to this occur in proximity to the adjacent Indonesian islands and directly south of Albany (possibly due to northwards flow of subantarctic nutrient-rich waters). A considerable interannual variation was also noted, with the highest mean chlorophyll concentrations occurring in 1981. 1982 and 1983.The influence of the forcing terms on chlorophyll a appears to vary significantly among the waters of North West Shelf, Western and southern Western Australian coastline. This is most notable in the interseasonal variations. The changes observed interannually and their influence on chlorophyll a are not easily discernible. but there may be some connection with the La Nina/El Nino related changes in both currents and winds.
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Main, Russell Stuart. "A Remote sensing change detection study in the arid Richtersveld region of South Africa." Thesis, University of the Western Cape, 2007. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_3173_1257322677.
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The Richtersveld falls within the succulent karoo and dester biomes. This studu made use of remote sensing technologies in order to investigate possible vegetation cover changes that have taken place over time, and which have manifested through a combination of threats to the region. Te aims of the study were adressed using three key questions that sought to gainan understanding of the relationship between vegetation response and moisture, in order to interpret teporal and spatial vegetyation cover changes. A spartially and temporarily representative remotely sensed dataset was used together with techniques that are repeatable and able to quantify change with a limited human bias.
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Corner, Robert J. "Passive spectral bathymetry using satellite remote sensing in Cockburn Sound, W.A." Thesis, Curtin University, 1992. http://hdl.handle.net/20.500.11937/2571.
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Conventional bathymetric surveying is a costly and time consuming business. Even today many areas of shallow inshore ocean, some which encompass potential oil and gas fields, are only minimally charted. There is a need for reconnaissance systems which can effectively direct more expensive detailed surveys to best effect. Remote spectral bathymetry is one such system.A review of candidate sensor systems and processing algorithms highlighted problems due to changing bottom cover types and water quality parameters. A method, proposed and theoretically validated by other workers, was chosen for further investigation. This method develops an approximate relationship between the spectral content of the satellite data and water depths and then, by an iterative phase in the spatial domain, seeks to minimise the effect of spatially dependant variations.A study site in Cockburn Sound, Western Australia was chosen for a demonstration of this method. Spectral data are from the Landsat Thematic Mapper instrument and depth data are taken from Admiralty Charts. A variation on the originally proposed algorithm introduces spatial preprocessing phase, in which the image is segmented into zones where spectral relationships are expected to be more uniform. Two different methods of spatial mapping are used.The results demonstrate the capability of spatial modelling to improve remotely sensed depth estimates in the depth range of 5 to 12 m. The need for further research to better understand the shallow water spectral relationships is identified.
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Marinelli, Marco Antonio. "An ocean colour remote sensing study of the phytoplankton cycle off Western Australia." Curtin University of Technology, School of Applied Science, 2002. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=14199.
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The concentration of phytoplankton in waters off the Western Australian coastline contrast with the coastal waters west of southern Africa and South America. The lack of favourable upwelling conditions results in the majority of the southeastern Indian Ocean surface waters being nutrient poor. Which is reflected in their low productivity. Several areas either on or in close proximity to the coastline are notably more productive. The associated forcing terms generating phytoplankton favourable conditions differ between areas. as do the seasons in which they occur. Measurements of chlorophyll a concentration. the major photosynthetic pigment contained in phytoplankton, may be directly related to oceanic bioproductivity. Using data collected by the Coastal Zone Color Seamier between 1979-86, this work aims to improve the understanding of the spatial and temporal changes that occurred in chlorophyll a abundance in the southeastern Indian Ocean. The highest seasonal mean concentrations occur in Summer (January-March) and Autumn (April-June); the former occurring in waters of the North West Shelf and the latter in close coastal areas of Western Australia south of North West. Cape. Concentrations observed in the offshore oceanic regions are mostly poor. Exceptions to this occur in proximity to the adjacent Indonesian islands and directly south of Albany (possibly due to northwards flow of subantarctic nutrient-rich waters). A considerable interannual variation was also noted, with the highest mean chlorophyll concentrations occurring in 1981. 1982 and 1983.The influence of the forcing terms on chlorophyll a appears to vary significantly among the waters of North West Shelf, Western and southern Western Australian coastline. This is most notable in the interseasonal variations. The changes observed interannually and their influence on chlorophyll a are not easily discernible. but there may be some connection with the La Nina/El Nino related changes in both currents and winds.
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Grundling, Althea Theresa. "Evaluation of remote sensing sensors for monitoring of rehabilitated wetlands." Diss., Prtoria: [s.n.], 2004. http://upetd.up.ac.za/thesis/available/etd-05132005-145705/.
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Johnson, Michele K. "Remote sensing and the South, a critical evaluation of common approaches." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq37557.pdf.
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Corner, Robert J. "Passive spectral bathymetry using satellite remote sensing in Cockburn Sound, W.A." Curtin University of Technology, School of Surveying and Mapping, 1992. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=10329.
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Conventional bathymetric surveying is a costly and time consuming business. Even today many areas of shallow inshore ocean, some which encompass potential oil and gas fields, are only minimally charted. There is a need for reconnaissance systems which can effectively direct more expensive detailed surveys to best effect. Remote spectral bathymetry is one such system.A review of candidate sensor systems and processing algorithms highlighted problems due to changing bottom cover types and water quality parameters. A method, proposed and theoretically validated by other workers, was chosen for further investigation. This method develops an approximate relationship between the spectral content of the satellite data and water depths and then, by an iterative phase in the spatial domain, seeks to minimise the effect of spatially dependant variations.A study site in Cockburn Sound, Western Australia was chosen for a demonstration of this method. Spectral data are from the Landsat Thematic Mapper instrument and depth data are taken from Admiralty Charts. A variation on the originally proposed algorithm introduces spatial preprocessing phase, in which the image is segmented into zones where spectral relationships are expected to be more uniform. Two different methods of spatial mapping are used.The results demonstrate the capability of spatial modelling to improve remotely sensed depth estimates in the depth range of 5 to 12 m. The need for further research to better understand the shallow water spectral relationships is identified.
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Tyoda, Zipho. "Landslide susceptibility mapping : remote sensing and GIS approach." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/79856.
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Thesis (MSc)--Stellenbosch University, 2013.Landslide susceptibility maps are important for development planning and disaster management. The current synthesis of landslide susceptibility maps largely applies GIS and remote sensing techniques. One of the most critical stages on landslide susceptibility mapping is the selection of landslide causative factors and weighting of the selected causative factors, in accordance to their influence to slope instability. GIS is ideal when deriving static factors i.e. slope and aspect and most importantly in the synthesis of landslide susceptibility maps. The integration of landslide causative thematic maps requires the selection of the weighting method; in order to weight the causative thematic maps in accordance to their influence to slope instability. Landslide susceptibility mapping is based on the assumption that future landslides will occur under similar circumstances as historic landslides. The weight of evidence method is ideal for landslide susceptibility mapping, as it calculates the weights of the causative thematic maps using known landslides points. This method was applied in an area within the Western Cape province of South Africa, the area is known to be highly susceptible to landslide occurrences. A prediction rate of 80.37% was achieved. The map combination approach was also applied and achieved a prediction rate of 50.98%. Satellite remote sensing techniques can be used to derive the thematic information needed to synthesize landslide susceptibility maps and to monitor the variable parameters influencing landslide susceptibility. Satellite remote sensing techniques can contribute to landslide investigation at three distinct phases namely: (1) detection and classification of landslides (2) monitoring landslide movement and identification of conditions leading up to an event (3) analysis and prediction of slope failures. Various sources of remote sensing data can contribute to these phases. Although the detection and classification of landslides through the remote sensing techniques is important to define landslide controlling parameters, the ideal is to use remote sensing data for monitoring of areas susceptible to landslide occurrence in an effort to provide an early warning. In this regard, optical remote sensing data was used successfully to monitor the variable conditions (vegetation health and productivity) that make an area susceptible to landslide occurrence.
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Chedzey, Helen Claire. "Remote sensing of cloud properties and rainfall: three decades of satellite observations over Australia." Thesis, Curtin University, 2017. http://hdl.handle.net/20.500.11937/65385.
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A remote sensing study of global and Australian cloud cover was undertaken using a combination of High-resolution Infrared Radiation Sounder (HIRS) and MODerate-resolution Imaging Spectroradiometer (MODIS) data for a 31-year period (1985 to 2015). Regional characterisations of potential rain clouds were investigated in the Southwest and Kimberley regions of Western Australia using satellite-derived cloud physical and micro-physical properties (cloud top pressure, cloud effective emissivity, cloud top temperature, cloud optical thickness and cloud effective radius).
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Hellmark, Robert. "Variations and correlations among climatic and environmental variables in Australia using GIS and remote sensing." Thesis, Stockholms universitet, Institutionen för naturgeografi och kvartärgeologi (INK), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-95237.
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This study was performed because of the potential vulnerability to climate change of the Australian continent. For example, global warming may increase the frequency and severity of drought [McAlpine, C.A., Syktus, J., Ryan, J.G., Deo, R.C., McKeon, G.M., McGowan, H.A. & Phinn, S.R., 2009: A continent under stress: interactions, feedbacks and risks associated with impact of modified land cover on Australia’s climate. Global Change Biology 15, 2206-2223]. The aim of this study is therefore to investigate spatial and temporal patterns in temperature, rainfall, and solar radiation and how native vegetation (represented by NDVI) and land-use correlate with these climatic parameters. The correlations are investigated during the 1982-2006 period across the Australian continent. To meet this general aim, three objectives are implemented: (1) to identify how these variables vary spatially and temporally; (2) to investigate whether spatial variations in these variables correlate; (3) to investigate whether temporal variations in these variables correlate. Using GIS software, maps are produced that show how the selected parameters vary over the study period across the Australian continent. During winter there is a trend of increasing temperature, solar radiation, and vegetation density and spatial distribution during 1982-2006. It is likely that the climatic variation over the 1982-2006 period is forcing the observed change in winter vegetation. The systematic variations of the trend indicate that winter is the key season over the 1982-2006 study period. Decreased winter rainfall over 1982-2006 across all of Western Australia, along with a trend of increasing summer rainfall displayed over the same period, indicate a negative outcome for this part of the continent. This is because there is more water runoff to streams and soils in the winter, because of low evapotranspiration and cool temperatures. The strongest correlation between spatial variations in vegetation distribution and climatic parameters during winter seasons 1982-2006 occurs between vegetation and temperature. During summer seasons over the same period, the strongest correlation occurs between vegetation and solar radiation. Correlations between expansion of selected land-use areas and spatial variations in climate during 1992-2005 show ambiguous patterns and could possibly be random. These findings are also unreliable because the land-use data has some significant errors, e.g. in estimated agriculture areas. During 1982-2006, the strongest correlation between temporal variations in vegetation density-distribution and climatic parameters occurs in the summer vegetation-temperature relationship (mean R² = -0.53). Vegetation density displays over 1982-2006 negative correlations with temperature and solar radiation, and positive with rainfall. Relationships between temporal variations in climate and selected landuse areas over the 1992-2005 period indicate a specific pattern. Areas of water, conservation, and production from relatively natural environments show, in general, higher mean values in all climatic parameters (except for winter rainfall) than other land-use areas. Because these land-use areas are mainly distributed in hot and arid Australian climate zones, the climate is unsuitable for agriculture, which might explain their higher mean values in the climatic parameters than, for example, croplands. The findings of variations (trends) and correlations in the present study, together with previous predictions, indicate that the future for Australia might be challenging because of increasing frequency of droughts and forest fires. Therefore, the potential vulnerability to future climate change of the Australian continent is of great concern.
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Mundava, Charity. "Estimating Above Ground Biomass using Remote Sensing in the Sub-Tropical Climate Zones of Australia." Thesis, Curtin University, 2015. http://hdl.handle.net/20.500.11937/1866.
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The study focused on assessing the total above ground biomass using remote sensing in the Kimberley rangelands of Western Australia. Remote sensing has the advantage that it can rapidly provide estimates non-destructively on a large scale with a high temporal frequency. In this thesis a field sampling protocol was developed and mono- and multi-temporal above ground biomass estimation models could be calibrated and validated with field based measurements for the most significant vegetation types.
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Pretorius, Cindy. "Digital satellite remote sensing for terrestrial coastal zone management." Thesis, Stellenbosch : Stellenbosch University, 2002. http://hdl.handle.net/10019.1/52804.
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Thesis (MA)--Stellenbosch University, 2002.ENGLISH ABSTRACT: The unique and often fragile environment of the coastal zone is placed under increasing pressure by human development. It is expected that three quarters of the world's population will be living within 60km of the coast by the year 2020. Thorough planning and management are required to prevent coastal degradation. In South Africa, coastal management efforts are being promoted through the implementation of a White Paper for sustainable coastal development. A Coastal Decision Support System (CDSS) was developed to empower local authorities to demarcate and manage sensitive coastal areas by giving them access to relevant botanical and physical information. Land cover/use information for the CDSS was previously mapped manually from hardcopy aerial photography. This method was found to be time-consuming and costly. This study investigated the potential for digital satellite imagery as primary source of data for populating the land cover/use information of the CDSS. A methodology was designed utilising semi-supervised isodata clustering for extracting relevant information for a study area covering 40x20km of coast along the southern coastal sector of South Africa. Digital mapping of SPOT 4 multispectral satellite data was used successfully to map land cover/use information such as wetlands, coastal lakes, dune vegetation, urban areas, forest plantations, natural forest and agricultural areas. A cost comparison was also made between the digital mapping method from satellite imagery used in this research project and the manual mapping from aerial photography. Digital mapping from satellite imagery was found to be more cost-effective in terms of both data and human resource costs. The method outlined and discussed in the research project should provide sufficient guidance for future application of the techniques in populating the CDSS with land cover/use information.
AFRIKAANSE OPSOMMING: Die unieke en dikwels sensitiewe landskap in die kussone is onder aansienlike druk weens ontwikkeling deur mense. Daar word verwag dat 'n derde van die wêreldbevolking teen die jaar 2020 binne 60km van die kus woonagtig sal wees. Dit sal deeglike beplanning en bestuur verg om die agteruigang van hierdie gebied te bekamp. Kussonebestuur word in Suid Afrika aangemoedig deur die implementering van 'n Witskrif vir volhoubare kussone-ontwikkeling. 'n Kusgebied-besluitnemingsondersteuningstelsel (KBOS) is ontwikkel in 'n poging om plaaslike owerhede te bemagtig om sensitiewe kusgebiede af te baken en te bestuur. Die KBOS verleen plaaslike owerhede toegang tot toepaslike inligting oor botaniese en fisiese o~standighede. Grondbedekkinginligting vir die KBOS is in die verlede vanaf hardekopie lugfoto's gekarteer. Hierdie metode is tydrowend en duur. Die potensiaal van digitale satellietbeelde as hoof databron om grondbedekkinginligting vir die KBOS te voorsien is in hierdie studie ondersoek. 'n Metode word in die tesis uiteengesit om 'semi-supervised isodata clustering' te gebruik om die nodige inligting uit die data te onttrek. Die studiegebied sluit 'n area van 40x20km langs die suid kus van Suid Afrika in. Digitale kartering vanaf SPOT 4 multispektrale satellietdata is suksesvol gebruik om grondbedekkingsinligting soos vleilande, kusmere, duin-plantegroei, stedelike gebiede, bosbou, natuurlike bos en landbougebiede te karteer. 'n Kostevergelyking is gedoen tussen die digitale karteringsmetode vanaf satellietbeelde in vergeleke met handkartering vanaf lugfotografie. Die digitale karteringsmetode blyk meer koste-effektief te wees beide in terme van die datakoste sowel as die koste verbonde aan mannekrag. Die omskrywing van die metode in die tesis behoort as goeie riglyn te dien vir die toepassing van die tegniek om grondbedekkinginligting voor te berei vir die KBOS.
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Engelbrecht, Jeanine. "Remote sensing for assessing wetland-groundwater interaction in the Kogelberg Biosphere Reserve." Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/50436.
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Thesis (MA)--Stellenbosch University, 2005.ENGLISH ABSTRACT: The Table Mountain Group (TMG) Aquifer System is a regional fractured aquifer system with a large potential as a source of future water supplies in the Western and Eastern Cape. This system is currently under consideration for large-scale water abstraction. Many terrestrial ecosystems, however, are dependent on these groundwater resources for survival. Exploitation of ground water resources at a rate exceeding the rate of natural recharge would result in a lowering of the water table and the drying up of seeps. The main objective of this study was to determine if satellite remote sensing data can be used for the detection of groundwater-dependent wetlands, and secondly, to use multi-temporal imagery for estimating seasonal changes experienced in wetland communities in relation to surrounding vegetation. The Kogelberg Biosphere Reserve, situated approximately 30km to the east of Cape Point in the Western Cape, South Africa, was selected for investigation. To accomplish the objectives, three Landsat 7 ETM+ images (path/row: 175/84) captured on 22 September 2001, 18 May 2002 and 23 September 2002 were acquired. Image fusion of the multispectral bands (30m resolution) with the panchromatic band (15m resolution) provided 15m multispectral images for analysis purposes. Geometric correction, radiometric normalisation and atmospheric corrections was performed in order to ensure pixel-level comparability between images. Once comparability between images was guaranteed, vegetation indices and tasselled cap components were derived to provide threshold values of moisture stress indicators and productivity estimations of wetland communities in relation to surrounding non-wetland communities. Additionally, change vector analysis on these transformations provided the ability to detect and assess the seasonal changes experienced by these communities during an annual cycle. The results of these transformations were combined in a rule-based image classifier in order to assist in estimating the seasonal dependency of observed wetland communities. The ability to use Landsat 7 images and the abovementioned image processing procedures to identify wetland communities with a high probability of groundwater interaction was demonstrated with a high degree of accuracy (78%). It is recommended that future studies concentrate on increasing classification accuracies, while focusing on incorporating these techniques into a remote monitoring system for assessing the impacts of groundwater extraction on the groundwater-dependent wetland communities.
AFRIKAANSE OPSOMMING: Die Tafelberg Groep (TBG) Akwifer is 'n regionale verskuiwingsakwifer sisteem met groot potensiaal as toekomstige waterbron vir die Wes- en Oos-Kaap. Grootskaalse grondwateronttrekking uit hierdie sisteem word tans ondersoek. Baie terrestriële ekosisteme is egter vir oorlewing van grondwaterbronne afhanklik. Grondwaterontginning teen 'n tempo hoër as die natuurlike aanvultempo sal die watertafel laat daal en syfersones laat opdroog. Die hoofdoel van die studie was om te bepaal of satellietbeelde gebruik kan word om grondwater-afhanklike vleilande waar te neem, en om 'n tydsreeks van beelde te gebruik om die seisoenale verandering in vleilandgemeenskappe relatief tot omliggende plantegroei te raam. Die Kogelberg Biosfeer Reservaat, ongeveer 30km oos van Kaappunt, is as studiegebied geïdentifiseer. Drie Landsat 7 beelde (baan/ry: 175/84) van 22 September 2001, 18 Mei 2002 en 23 September 2002 is ontleed. Die Landsat 7 multispektrale bande (30m resolusie) is met behulp van beeld-fusietegnieke met die panchromatiese band (15m resolusie) gekombineer om multispektrale beelde te lewer met 15m grondresolusie. Geometriese korreksie, radiometriese normalisering en atmosferiese korreksie is op elk van die beelde toegepas om beeld-selvlak vergelykings tussen beelde 'n moontlikheid te maak. Met beeldvergelykbaarheid verseker, is plantegroei-indekse en 'tassled cap' transformasies gebruik om afsnywaardes vir vleiland-identifikasie te bereken. Verder is veranderingsvektoranalises op die transformasies bereken om die seisoenale veranderinge oor die jaarsiklus in vleilande te bepaal. Die resultate hiervan is vervat in 'n reël-gebaseerde beeldklassifiseerder waarmee vleilande se seisoenale grondwater afhanklikheid geraam is. Die vermoë om vleilande met 'n hol! waarskynlikheid van grondwater interaksie uit Landsat 7 beelde te identifiseer is met 'n hol! vlak van totale akkuraatheid (78%) gedemonstreer. Die aanbeveling is dat toekomstige studies moet fokus op die verhoging van hierdie klassifikasie akkuraathede. Die tegnieke moet toegespits word op die ontwikkeling van 'n afstandswaarnemingstelsel om die
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Hajigholizadeh, Mohammad. "Water Quality Modelling Using Multivariate Statistical Analysis and Remote Sensing in South Florida." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2992.
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The overall objective of this dissertation research is to understand the spatiotemporal dynamics of water quality parameters in different water bodies of South Florida. Two major approaches (multivariate statistical techniques and remote sensing) were used in this study. Multivariate statistical techniques include cluster analysis (CA), principal component analysis (PCA), factor analysis (FA), discriminant analysis (DA), absolute principal component score-multiple linear regression (APCS-MLR) and PMF receptor modeling techniques were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, a 15-year (2000–2014) data set of 12 water quality variables, and about 35,000 observations were used. Agglomerative hierarchical CA grouped 16 monitoring sites into three groups (low pollution, moderate pollution, and high pollution) based on their similarity of water quality characteristics. DA, as an important data reduction method, was used to assess the water pollution status and analysis of its spatiotemporal variation. PCA/FA identified potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules, and causes were explained. The APCS-MLR and PMF models apportioned their contributions to each water quality variable.
Also, the bio-physical parameters associated with the water quality of the two important water bodies of Lake Okeechobee and Florida Bay were investigated based on remotely sensed data. The principal objective of this part of the study is to monitor and assess the spatial and temporal changes of water quality using the application of integrated remote sensing, GIS data, and statistical techniques. The optical bands in the region from blue to near infrared and all the possible band ratios were used to explore the relation between the reflectance of a waterbody and observed data. The developed MLR models appeared to be promising for monitoring and predicting the spatiotemporal dynamics of optically active and inactive water quality characteristics in Lake Okeechobee and Florida Bay. It is believed that the results of this study could be very useful to local authorities for the control and management of pollution and better protection of water quality in the most important water bodies of South Florida.
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Phaladi, Shikoane Given. "Using GPS bistatic signal for land and ocean remote sensing in South Africa." Master's thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/4920.
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Includes bibliographical references (leaves 73-77).This project discusses the basic principles and theory of this new technology, and concentrates on reflection points and Fresnel zones. The CPS receivers are placed at different coastal regions within South Africa, and the simulation of the reflection points and Fresnel zones are observed as the CPS satellites pass over South Africa. The East London area was chosen as the location to place the receiver throughout my analysis.
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Ceron, Cristobal N. "Operational Actual Wetland Evapotranspiration Estimation for South Florida Using MODIS Imagery." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1454.
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The purpose of this study is to validate the ability of the Simplified Surface Energy Balance (SSEB) approach and the Simple Method to provide AET estimates for wetland recovery efforts. The study utilizes the MODIS sensor aboard NASA's Terra satellite and SFWMD solar radiation data to derive AET values for South Florida. The SSEB/Simple-Method approach provided mixed results with good agreement with control values during dry season (rave (59) = 0.700, pave < 0.0005) and poor agreement during wet season (rave(46) = 0.137, pave = 0.304). Further refinement is needed to make this method viable for yearly estimates due to the poor performance during wet season months. This approach can prove useful for short term wetland recovery assessment projects that occur during the dry season and/or long term projects that compare AET rates from a site from dry season to dry season.
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Blessing, Sithole Vhusomuzi. "A multiscale remote sensing assessment of subtropical indigenous forests along the wild coast, South Africa." Thesis, Nelson Mandela Metropolitan University, 2015. http://hdl.handle.net/10948/d1021169.
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The subtropical forests located along South Africa’s Wild Coast region, declared as one of the biodiversity hotspots, provide benefits to the local and national economy. However, there is evidence of increased pressure exerted on the forests by growing population and reduced income from activities not related to forest products. The ability of remote sensing to quantify subtropical forest changes over time, perform species discrimination (using field spectroscopy) and integrating field spectral and multispectral data were all assessed in this study. Investigations were conducted at pixel, leaf and sub-pixel levels. Both per-pixel and sub-pixel classification methods were used for improved forest characterisation. Using SPOT 6 imagery for 2013, the study determined the best classification algorithm for mapping sub-tropical forest and other land cover types to be the maximum likelihood classifier. Maximum likelihood outperformed minimum distance, spectral angle mapper and spectral information divergence algorithms, based on overall accuracy and Kappa coefficient values. Forest change analysis was made based on spectral measurements made at top of the atmosphere (TOC) level. When applied to the 2005 and 2009 SPOT 5 images, subtropical forest changes between 2005-2009 and 2009-2013 were quantified. A temporal analysis of forest cover trends in the periods 2005-2009 and 2009-2013 identified a decreasing trend of -3648.42 and -946.98 ha respectively, which translated to 7.81 percent and 2.20 percent decrease. Although there is evidence of a trend towards decreased rates of forest loss, more conservation efforts are required to protect the Wild Coast ecosystem. Using field spectral measurements data, the hierarchical method (comprising One-way ANOVA with Bonferroni correction, Classification and Regression Trees (CART) and Jeffries Matusita method) successfully selected optimal wavelengths for species discrimination at leaf level. Only 17 out of 2150 wavelengths were identified, thereby reducing the complexities related to data dimensionality. The optimal 17 wavelength bands were noted in the visible (438, 442, 512 and 695 nm), near infrared (724, 729, 750, 758, 856, 936, 1179, 1507 and 1673 nm) and mid-infrared (2220, 2465, 2469 and 2482 nm) portions of the electromagnetic spectrum. The Jeffries-Matusita (JM) distance method confirmed the separability of the selected wavelength bands. Using these 17 wavelengths, linear discriminant analysis (LDA) classified subtropical species at leaf level more accurately than partial least squares discriminant analysis (PLSDA) and random forest (RF). In addition, the study integrated field-collected canopy spectral and multispectral data to discriminate proportions of semi-deciduous and evergreen subtropical forests at sub-pixel level. By using the 2013 land cover (using MLC) to mask non-forested portions before sub-pixel classification (using MTMF), the proportional maps were a product of two classifiers. The proportional maps show higher proportions of evergreen forests along the coast while semi-deciduous subtropical forest species were mainly on inland parts of the Wild Coast. These maps had high accuracy, thereby proving the ability of an integration of field spectral and multispectral data in mapping semi-deciduous and evergreen forest species. Overall, the study has demonstrated the importance of the MLC and LDA and served to integrate field spectral and multispectral data in subtropical forest characterisation at both leaf and top-of-atmosphere levels. The success of both the MLC and LDA further highlighted how essential parametric classifiers are in remote sensing forestry applications. Main subtropical characteristics highlighted in this study were species discrimination at leaf level, quantifying forest change at pixel level and discriminating semi-deciduous and evergreen forests at sub-pixel level.
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Siemon, Noel, and n/a. "Civil remote sensing policy in Australia : a case study concerning the commercialisation of a government-developed technology." University of Canberra. Administrative Studies, 1993. http://erl.canberra.edu.au./public/adt-AUC20061108.154949.
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Oliveira, Sofia Luísa de Jesus. "Frequency, patchiness and intensity of tropical savanna fires: analysis using field data and remote sensing." Doctoral thesis, ISA/UL, 2014. http://hdl.handle.net/10400.5/7322.
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Doutoramento em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de AgronomiaIn tropical savannas, one of the most fire-prone biomes on Earth, fire management is a continuous and iterative process that can only be effectively achieved with thorough consideration of fire regimes. Based on remotely sensed imagery and in-situ field data, key fire regime components were assessed for tropical savannas of northern Australia (frequency, patchiness, intensity, and severity) and Brazil (frequency). The discrete lognormal model was found to be the best method for modelling fire frequency in tropical savannas, and demonstrated that fire frequency is very high in both countries. In northern Australia, fire patchiness was lower in the late dry season, characterized by shorter and fewer unburned patches, than in the early dry season. Fire intensity and severity were highest in the late dry season. The observed temporal differences are consistent with the hypothesis that climate is the main driver of fire regime seasonality. Fuel load and fuel continuity explained fire regime differences between vegetation types. Fire season was bimodal, with peaks in May and October, related to periods of anthropogenic fire and optimal fire weather conditions. Prescribed burning in the early dry season can increase the patchiness and reduce the intensity of late dry season fires, with substantial benefits for biodiversity and a reduction in greenhouse gas emissions
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Gerolemou, Rosie Victoria, and Dirk Roux. "The suitability of remote sensing for prioritising management of invasive plants in the Garden Route South Africa." Thesis, Nelson Mandela Metropolitan University, 2017. http://hdl.handle.net/10948/14300.
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Invasive tree species pose a huge problem in the Garden Route and are particularly damaging to aquatic ecosystems, including wetlands, riparian zones, lakes and estuaries. Therefore, this study aimed to determine priority areas for invasive tree species management, with a focus on aquatic ecosystems. This was achieved by using existing literature to identify priority species, based on their impact on aquatic ecosystems and their associated ecosystem services, and then testing the suitability of SPOT-6 and WorldView-3 multispectral data at detecting these focal species. The priority species identified were: Acacia cyclops (rooikrans), Acacia longifolia (long-leaved wattle), Acacia mearnsii (black wattle), Acacia melanoxylon (blackwood), Acacia saligna (Port Jackson willow), Eucalyptus camaldulensis (red river gum), Pinus pinaster (cluster pine) and Pinus radiata (radiata pine). The Random Forest classifier on SPOT-6 data achieved an overall accuracy of 62.5% and this method was consequently deemed ineffective at separating invasive tree species from other tree species in the Garden Route. The overall accuracy of the WorldView-3 classifier was higher (78.9%) but the cost of the data limited the use of more images for the detection of the focal species throughout the Garden Route. Therefore, to identify priority areas for invasive tree management, criteria derived from existing literature were input into spatial conservation planning software. The analysis identified the: Saasveld section of the Garden Route National Park, the Wilderness Lakes, Knysna Forest, Knysna Estuary, Tsitsikamma Forest around Stormsriver and a disturbed area of fynbos southeast of Kareedouw as management priorities. Currently spatial conservation planning software proved to be cost-affordable and useful tool and is recommended for invasive tree management in the Garden Route.
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Twala, Mthokozisi Nkosingiphile. "Use of multispectral remote sensing data to map magnetite bodies in the Bushveld Complex, South Africa : a case study of Roossenekal, Limpopo." Diss., University of Pretoria, 2019. http://hdl.handle.net/2263/75756.
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Mineral detection and geological mapping through conventional ground survey methods based on field observation and other geological techniques are tedious, time-consuming and expensive. Hence, the use of remote sensing in mineral detection and lithological mapping has become a generally accepted augmentative tool in exploration. With the advent of multispectral sensors (e.g. ASTER, Landsat and PlanetScope) having suitable wavelength coverage and bands in the Shortwave Infrared (SWIR) and Thermal Infrared (TIR) regions, multispectral sensors, along with common and advanced algorithms, have become efficient tools for routine lithological discrimination and mineral potential mapping. It is with this paradigm in mind that this project sought to evaluate and discuss the detection and mapping of magnetite on the Eastern Limb of the Bushveld Complex, using specialized common traditional and machine learning algorithms. Given the wide distribution of magnetite, its economic importance, and its potential as an indicator of many important geological processes, the delineation of magnetite is warranted. Before this study, few studies had looked at the detection and exploration of magnetite using remote sensing, although remote sensing tools have been regularly applied to diverse aspects of geosciences. Maximum Likelihood, Minimum Distance to Means, Artificial Neural Networks, Support Vector Machine classification algorithms were assessed for their respective ability to detect and map magnetite using the PlanetScope Analytic Ortho Tiles in ENVI, QGIS, and Python. For each classification algorithm, a thematic landcover map was attained and an error matrix, depicting the user's and producer's accuracies, as well as kappa statistics, was derived, which was used as a comparative measure of the accuracy of the four classification algorithms. The Maximum Likelihood Classifier significantly outperformed the other techniques, achieving an overall classification accuracy of 84.58% and an overall kappa value of 0.79. Magnetite was accurately discriminated from the other thematic landcover classes with a user’s accuracy of 76.41% and a producer’s accuracy of 88.66%. Despite the Maximum Likelihood classification algorithm illustrating better class categorization, a large proportion of the mining activity pixels were erroneously classified as magnetite. However, this observation was not merely limited to the Maximum Likelihood classification algorithm, but all image classifications algorithms. The overall results of this study illustrated that remote sensing techniques are effective instruments for geological mapping and mineral investigation, especially in iron oxide mineralization in the Eastern Limb of Bushveld Complex.Dissertation (MSc)--University of Pretoria, 2019.
Geology
MSc
Unrestricted
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Dorij, Passang. "Satellite Remote Sensing Algorithm Development to Estimate Total Suspended Sediment Concentration for Highly Turbid Waters of Western Australia." Thesis, Curtin University, 2017. http://hdl.handle.net/20.500.11937/55102.
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Satellite-based remote sensing of total suspended sediment (TSS) concentration is studied for highly turbid waters of northern Western Australia. A robust multi-sensor red band semi-analytic sediment model was developed for coastal waters, and the implications of using a wide range of sensors with different spatial resolutions were also explored. In addition, historical TSS models were critically compared, and the feasibility of the geostationary satellite sensor AHI was also explored with respect to mapping TSS.
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Mhangara, Paidamwoyo. "Land use/cover change modelling and land degradation assessment in the Keiskamma catchment using remote sensing and GIS." Thesis, Nelson Mandela Metropolitan University, 2011. http://hdl.handle.net/10948/1467.
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Land degradation in most communal parts of the Keiskamma catchment has reached alarming proportions. The Keiskamma catchment is particularly predisposed to severe land degradation associated with soil erosion, thicket degradation and deteriorating riparian vegetation. There is a close coupling between land use/cover dynamics and degradation trends witnessed in the catchment. Soil erosion is prevalent in most of the communal areas in the catchment. The principal aim of this study was to investigate land use/cover trends, model the spatial patterns of soil loss and predict future land use/cover scenarios as a means of assessing land degradation in the Keiskamma catchment. Multi-temporal Landsat satellite imagery from 1972 to 2006 was used for land use/cover change analyses using object-oriented post-classification comparison. Fragmentation analysis was performed by computing and analyzing landscape metrics in the riparian and adjacent hillslope areas to determine the land cover structural changes that have occurred since 1972. The landscape function analysis was used to validate the current rangeland conditions in the communal areas and the former commercial farms. The current condition of the riparian zones and proximal hillslopes was assessed using the Rapid Appraisal of Riparian Condition and future land use/cover scenarios were simulated using the Markovcellular automata model. Spatial patterns of soil loss in the Keiskamma catchment were determined using the Sediment Assessment Tool for Effective Erosion Control (SATEEC), which is a GIS based RUSLE model that integrates sediment delivery ratios. Object oriented classification was used to map soil erosion surfaces and valley infill in ephemeral stream channels as a means of demonstrating the major sediment transfer processes operating in the Keiskamma catchment. The Mahalanobis distance method was used to compute the topographic thresholds for gully erosion. To understand the effect of soil characteristics in severe forms of erosion, laboratory analyses were undertaken to determine the physico-chemical soil properties. iv The temporal land use/cover analysis done using the post-classification change detection indicated that intact vegetation has undergone a significant decline from 1972 to 2006. The temporal changes within the intermediate years are characterized by cyclic transitions of decline and recovery of intact vegetation. An overall decline in intact vegetation cover, an increase in degraded vegetation and bare eroded soil was noted. Fragmentation analyses done in the communal villages of the central Keiskamma catchment indicated increasing vegetation fragmentation manifested by an increase in smaller and less connected vegetation patches, and a subsequent increase of bare and degraded soil patches which are much bigger and more connected. The Landscape Organisation Index revealed very low vegetation connectivity in the communal rangelands that have weak local traditional institutions. Fragmentation analyses in the riparian and proximal hillslopes revealed evidence of increasing vegetation fragmentation from 1972 to 2006. The Markov Cellular Automata simulation predicted a decline in intact vegetation and an increase in bare and degraded soil in 2019. The Keiskamma catchment was noted as experiencing high rates of soil loss that are above provincial and national averages. The classification of erosion features and valley infill showcased the vegetation enrichment in the ephemeral streams which is occurring at the expense of high soil losses from severe gully erosion on the hillslopes. This in turn has led to an inversion of grazing patterns within the catchment, such that grazing is now concentrated within the ephemeral stream channels. Soil chemical analyses revealed a high sodium content and low soluble salt concentration, which promote soil dispersion, piping and gully erosion. The presence of high amounts of illite-smectite in the catchment also accounts for the highly dispersive nature of the soil even at low SAR values. Significant amounts of swelling 2:1 silicate clays such as smectites cause cracking and contribute to the development of piping and gullying in the catchment. Given the worsening degradation trends in the communal areas, a systematic re-allocation of state land in sections of the catchment that belonged to the former commercial farms is recommended to alleviate anthropogenic pressure. Strengthening local institutions that effectively monitor and manage natural resources will be required in order to maintain v optimum flow regimes in rivers and curb thicket degradation. Measures to curb environmental degradation in the Keiskamma catchment should encompass suitable ecological interventions that are sensitive to the socio-economic challenges facing the people in communal areas.
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Jackson, Victoria L. "Use of GIS and Remote Sensing Technologies to Study Habitat Requirements of Ocelots, Leopardus pardalis, in south Texas." Thesis, University of North Texas, 2002. https://digital.library.unt.edu/ark:/67531/metadc3244/.
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The goals of this study were to use Geographic Information Systems (GIS) and remote sensing technologies to gain a better understanding of habitat requirements of a population of ocelots in south Texas, and then apply this knowledge to form a predictive model to locate areas of suitable habitat in Willacy and Cameron counties, Texas. Satellite imagery from August 1991 and August 2000 were classified into four land cover types: closed canopy, open canopy, water, and urban/barren. These classified images were converted into digital thematic maps for use in resource utilization studies and modeling. Location estimates (762 from 1991 and 406 from 2000) were entered into a GIS in order to extract information about home range and resource selection. Each animal's home range was calculated using both Minimum Convex Polygon (MCP) and Kernel home range estimators (95% and 50%). Habitat parameters of interest were: soil, land cover, human density, road density, and distance to closest road, city and water body. Ocelots were found to prefer closed canopy and avoid open canopy land cover types. Ocelots preferred soils known to support thorn scrub, an indication of the importance of this habitat. Landscape metrics associated with habitat used by ocelots were determined through the use of Patch Analyst, an extension for ArcView 3.2. Contrary to expectations, ocelots utilized areas with greater fragmentation than random areas available for use. However, this use of highly fragmented areas was an indication of the degree of fragmentation of suitable habitat in the area. Further investigation of patch size selection indicated that ocelots used large sized patches disproportionately to availability, indicating a preference for larger patches. A model was created using the resource selection and habitat preference GIS database from 1991. This model was used to identify areas of “optimal”, ”sub-optimal”, and “unsuitable” habitat for ocelots in 2000. This resultant map was compared to known locations of ocelots in 2000. Ocelots were found to prefer optimal habitat and avoid unsuitable habitat, an indication that the model created was valid.
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Shi, Xianzhong. "Hyperspectral sensing of acid sulphate soils and their environmental impacts in South Yunderup, Western Australia." Thesis, Curtin University, 2014. http://hdl.handle.net/20.500.11937/1820.
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Several sources of hyperspectral data were used to map the occurrence and spread of acid sulfate soils (AAS). Surface evolution of mineralogy during controlled oxidation of sulphidic material showed the formation of secondary iron minerals linked to soil pH ranges. Spectral characterization, image classification and PLSR of hyperspectral data successfully mapped the occurrence of surface and subsurface acid conditions and related toxicity by linking mineralogy to pH.
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Kutzner, Kendy. "Processing MODIS Data for Fire Detection in Australia." Thesis, Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200200831.
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The aim of this work was to use remote sensing data from the MODIS instrument of the Terra satellite to detect bush fires in Australia. This included preprocessing the demodulator output, bit synchronization and reassembly of data packets. IMAPP was used to do the geolocation and data calibration. The fire detection used a combination of fixed threshold techniques with difference tests and background comparisons. The results were projected in a rectangular latidue/longitude map to remedy the bow tie effect. Algorithms were implemented in C and Matlab. It proved to be possible to detect fires in the available data. The results were compared with fire detection done done by NASA and fire detections based on other sensors and found to be very similarDas Ziel dieser Arbeit war die Nutzung von Fernerkundungsdaten des MODIS Instruments an Bord des Satelliten Terra zur Erkennung von Buschfeuern in Australien. Das schloss die Vorverarbeitung der Daten vom Demodulator, die Bitsynchronisation und die Umpacketierung der Daten ein. IMAPP wurde genutzt um die Daten zu kalibrieren und zu geolokalisieren. Die Feuererkennung bedient sich einer Kombination von absoluten Schwellwerttests, Differenztests und Vergleichen mit dem Hintergrund. Die Ergebnisse wurden in eine rechteckige Laengen/Breitengradkarte projiziert um dem BowTie Effekt entgegenzuwirken. Die benutzten Algrorithmen wurden in C und Matlab implementiert. Es zeigte sich, dass es moeglich ist in den verfuegbaren Daten Feuer zu erkennen. Die Ergebnisse wurden mit Feuererkennungen der NASA und Feuererkennung die auf anderen Sensoren basieren verglichen und fuer sehr aehnlich befunden
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Matoti, Andiswa. "Assessing the groundwater resources within the Table Mountain Group using remote sensing and geographic information system." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53298.
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Thesis (MSc)--Stellenbosch University, 2003.ENGLISH ABSTRACT: The Cape Town metropolitan area has limited water supply due to rapid population and urban growth. In many instances, surface water is the only source in water supply schemes. There is a need for additional water supplies to supplement the existing water sources. Groundwater systems can be used as primary or supplemental water supply sources especially in areas where there is high demand for water resources. The aim of this study is to evaluate the groundwater potential within the Table Mountain Group (TMG) with the assistance of remote sensing and Geographical Information System (GIS). Previous hydrogeological studies have found the TMG to be the second largest hydrogeological unit in South Africa with extensively fractured and multi-porous rock. The study area is 5660 km2 with TMG covering 1336 km". In this study a Landsat Enhanced Thematic Mapper Plus (ETM+) image was used to identify lineaments. The identified lineaments were overlaid with vegetation, drainage patterns, faults and fractures digitized from 1:250 000 geological maps and borehole yields to show areas with promising groundwater resources. The results did not show correlation between vegetation and lineaments. Most of the lineaments intersected drainage lines at some points, and a few were parallel to the drainage lines. Forty five percent of the digitized faults and fractures overlap with the Landsat lineament. The most dominating lineaments are oriented in a NW-SE direction. High yielding boreholes with average yield of about 12 lIs were found within the distance of 150m from the lineaments. The lineaments were further analysed to locate areas that could be suitable for groundwater exploration. These areas were identified using Landsat lineaments, boreholes and a Digital Elevation Model (DEM). The results showed that the most favourable lineaments and geological features were oriented in a 135-180° and 0-45° direction and areas with slopes of less than 40% were found to be suitable for drilling boreholes. The amount of available groundwater within the TMG was also investigated by looking at both volume of recharge and amount that could be held in storage. Rainfall data was used to estimate recharge. Groundwater recharge was calculated to be 5% of the total precipitation that falls on this area. Based on the average rainfall of 600mm per annum, the results show that TMG has an average recharge value of 30mm per annum. The total recharge for the area covered by TMG, which has an area of 1336km2 , is 160 million nr'. Geological profiles and cross sections were drawn to determine the storage capacity of the TMG, which was estimated to be 525 million m.3 According to a study done by the Department of Water Affairs and Forestry (DW AF) in 1996, the anticipated water demand in the Cape Town metropolitan area will increase from 243 million m3 in 1990 to 560 million m3 in 2020. The estimated volume of water that can be stored within the TMG can meet the current demand for the next 10 years and supplement the existing surface water sources. Groundwater vulnerability of the TMG to contamination was assessed and mapped by using the DRASTIC index. The results demonstrate that the TMG area is at low risk to contamination.
AFRIKAANSE OPSOMMING: 'n Vinnig groeiende bevolking en stedelike uitbreiding plaas toenemende druk op Kaapstad se water voorraad. Addisionele waterbronne sal benodig word om bestaande bronne aan te vul. Oppervlakwater is in die meeste gevalle die enigste waterbron, maar grondwater het die potensiaal om te dien as 'n primêre of aanvullende voorsieningsbron, veral in areas waar groot water tekorte bestaan. Die doel van hierdie studie is om die grondwaterpotensiaal van gesteentes van die Tafelberg Groep (TBG) te evalueer deur van afstandswaarneming en geografiese inligtingstelsels gebruik te maak. Geohidrologiese studies het getoon dat die TBG gesteentes met sy veelvuldige nate en breuksones, die tweede grootste geohidrologiese eenheid in Suid Afrika is. Die studiegebied beslaan 5660 km", waarvan 1336 km2 deur Tafelberg Sandsteen beslaan word. Vir hierdie studie is 'n "Landsat Enhanced Thematic Mapper Plus (ETM+)" beeld gebruik in die identifisering van breuksones (lineamente). Verdere analises is uitgevoer om areas geskik vir grondwater ontginning te identifiseer. Geïdentifiseerde verskuiwings op Landsat beelde is met plantegroei, dreinerings patrone en bekende verskuiwings en fraktuur sones vanaf gelogiese kaarte vergelyk in 'n poging om areas met belowende grondwaterbronne uit te wys. Bekende boorgat posisies en lewerings volumes was 'n primêre databron vir die berekening van groundwater reserves. Die studie het egter geen korrelasie tussen plantegroei en die voorkoms van lineamente gevind nie. Die riviere in die studiegebied word op verskeie plekke deur verskuiwings gekruis. Slegs 'n paar van die verskuiwings lê parallel met die dreinering. Daar is gevind dat vyf-en-veertig persent van bekende verskuiwings en fraktuursones met die geïdentifiseerd op Landsat beelde oorvleuel. Die mees prominente lineamente het 'n NW-SO oriëntasie. Boorgate met lewerings van gemiddeld 12 lis is binne 'n 150m afstand van die verskuiwings gevind. Die verskuiwings is ook geanaliseer om die mees produktiewe areas vir grondwater ontginning te identifiseer. Landsat beelde, boorgate en 'n Digitale Elevasie Model (DEM) is gebruik om moontlike boorposisies te identifiseer. Die mees produktiewe verskuiwings en geologiese verskynsels het 'n N 135-180W en NO-450 oriëntasie, terwyl areas met 'n helling < 40% vir die boor van boorgate geskik is. Berekeninge oor die hoeveelheid water wat binne die TBG gesteentes beskikbaar is, is gemaak deur die hoeveelheid aanvulling en stoorkapasiteit van die TBG gesteentes te beraam. Grondwater aanvulling, soos bereken vanaf reënval data, is 5% van die totale presipitasie van 'n gegewe area. Met 'n gemiddelde jaarlikse reënval van 600mm in die studie gebied is die TBG se jaarlikse aanvulling ongeveer 30mm. Daar word beraam dat die totale aanvulling in die 1336km2 TBG area 160-miljoen m3 per jaar is. Geologiese profiele en dwarsnitte is gemaak om die stoorvermoë van die TBG te bepaal, en is beraam op 525-miljoen rrr'. 'n 1996 navorsing studie deur die Departement van Waterwese en Bosbou toon dat waterverbruik in die Kaapse Metropolitaanse gebied sal toeneem vanaf die 1990 vlak van 243-miljoen m3 tot 560 miljoen m3 teen 2020. Die berekende volume water wat binne die TBG gestoor word, kan die water aanvraag oor die volgende 10 jaar bevredig en as aanvulling dien vir oppervlak waterbronne. Die kwesbaarheid van die TBG akwifer vir besoedeling is met behulp van die DRASTIC indeks geëvalueer en gekarteer. Die resultate toon dat die TBG 'n lae risiko vir besoedeling het.
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Grant, Elizabeth Maree. "Aboriginal housing in remote South Australia : an overview of housing at Oak Valley, Maralinga Tjarutja Lands /." Title page, table of contents and abstract only, 1999. http://web4.library.adelaide.edu.au/theses/09ENV/09envg7611.pdf.
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Gubb, Andrew Alan. "An evaluation of Landsat MSS data for ecological land classification and mapping in the Northern Cape." Master's thesis, University of Cape Town, 1989. http://hdl.handle.net/11427/23662.
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This paper examines the issues that arise in the use of visual interpretation of Landsat data during the analysis, classification and mapping of the natural vegetation of the semi-arid Northern Cape. Initial research involved the classifying and mapping of the vegetation using conventional methods. A vegetation map, accompanying legend and descriptive key were produced. The problems encountered during this process, and the constraints of manpower, time and funds, stimulated the investigation of Landsat imagery as a means of improving the speed and accuracy of vegetation classification and mapping. A study area comprising one Landsat scene and which met certain requirements was selected: a) The area had already been surveyed and mapped at a scale of 1:250 000. b) As many vegetation units as possible were included. c) There was maximum diversity, complexity and variability in terms of soil, geology and terrain morphology. Initially a suitable mapping scale was selected, viz. 1:250 000, as it met the requirements of nature conservation authorities and agricultural planners. The scales of survey and remote sensing were based on this. The basic unit of survey was the 1:50 000 topographical map and satellite imagery at a scale of 1:250 000 was found to meet the requirements of reconnaissance level mapping. The usefulness of Landsat imagery was markedly affected by the quality of image production and enhancement. Optimum image production was vitally important and to this end, interaction between the user and the operations engineer at the Satellite Applications Centre, Hartebeeshoek was essential. All images used, were edge-enhanced and systematically corrected. While these procedures were costly, they proved to be fundamental to the success of the investigation. Precision geometric correction was not required for reconnaissance level investigation. The manual superimposition of the UTM grid, using ground control points from 1:250 000 topographical maps, proved to be accurate and convenient. Pattern recognition on single-band, panchromatic imagery was difficult. The scene lacked crispness and contrast, and it was evident that black and white imagery did not satisfy the objectives of the study. Three-band false colour composite imagery was superior to single-band imagery in terms of clarity and number of cover classes. The addition of colour undoubtedly facilitated visual interpretation. False colour composite imagery was investigated further to establish which year, season and possibly time of season would best suit the objectives of the investigation. It was found that the environmental parameters affecting reflectance are relatively stable over time and it was not necessary to acquire imagery of the same year as field surveys. However, the year of imagery should be chosen so that similar climatic conditions prevail. While, in certain instances, imagery captured during winter had advantages in separating complex mosaics, summer imagery was superior in most respects. Furthermore, given "normal" climatic conditions, the ideal period during which there was maximum contrast between and within ground classes, and thus spectral classes, was narrowed to mid-January to mid-April. Units which were acceptably heterogeneous (relatively homogeneous) in terms of reflectance levels were delineated manually on the image. This delineation was done at three levels of complexity and the units were compared with the vegetation map. A series of field trips aided the interpretation of the images, especially where discrepancies occurred between the map and the image. In general, there was a close degree of correspondence between the prepared vegetation map and the delineated image. Field investigation revealed the image units to be more accurate than those on the vegetation map, and the image served to highlight the inadequacies inherent in classifying and mapping vegetation of extensive areas with limited resources.
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Nyamugama, Adolph. "Monitoring carbon stocks in the sub-tropical thicket biome using remote sensing and GIS techniques : the case of the Great Fish River Nature Reserve and its environs, Eastern Cape province, South Africa." Thesis, Nelson Mandela Metropolitan University, 2013. http://hdl.handle.net/10948/d1020303.
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The subtropical thicket biome in the Eastern Cape Province of South Africa has been heavily degraded and transformed due overutilization during the last century. The highly degraded and transformed areas exhibit a significant loss of above ground carbon stocks (AGC) and loss of SOC content. Information about land use /cover change and fragmentation dynamics is a prerequisite for measuring carbon stock changes. The main aim of this study is to assess the trends of land use/cover change, fragmentation dynamics, model the temporal changes of AGC stocks in the Great Fish River Nature Reserve and its environs from 1972 to 2010, quantify and map the spatial distribution of SOC concentrations in the partial subtropical thicket cover in the Great Fish River Nature Reserve and environs (communal rangelands). Multi-temporal analyses based on 1972 Landsat MSS, 1982 and 1992 Landsat TM, 2002 Landsat ETM and 2010 SPOT 5 High Resolution images were used for land use/cover change detection and fragmentation analysis. Object oriented post-classification comparison was applied for land use/cover change detection analysis. Fragmentation dynamics analysis was carried out by computing and analyzing landscape metrics in land use/cover classes. Landscape fragmentation analyses revealed that thicket vegetation has increasingly become fragmented, characterized by smaller less linked patches of intact thicket cover. Landscape metrics for intact thicket and degraded thicket classes reflected fragmentation, as illustrated by the increase in the Number of Patches (NP), Patch Density (PD), Landscape Shape Index (LSI), and a decrease in Mean Patch Size (MPS). The use of remote sensing techniques and landscape metrics was vital for the understanding of the dynamics of land use/cover change and fragmentation. Baseline land use/cover maps produced for 1972, 1982, 1992 2002 and 2010 and fragmentation analyses were then used for analyzing carbon stock changes in the study area. To model the temporal changes of AGC stocks in the Great Fish River Nature Reserve and its environs from 1972 to 2010, a method based on the integration of RS and GIS was employed for the estimation of AGC stocks in a time series. A non-linear regression model was developed using NDVI values generated from SPOT 5 HRG satellite imagery of 2010 as the independent variable and AGC stock estimates from field plots as the dependent variable. The regression model was used to estimate AGC stocks for the entire study area on the 2010 SPOT 5 HRG and also extrapolated to the 1972 Landsat MSS, 1982 and 1992 Landsat TM, and 2002 Landsat ETM. The AGC stocks for the period 1972 -1982, 1982-1992, 1992-200) and 2002-2010 were compared by means of change detection analysis. The comparison of AGC stocks was carried out at subtropical thicket class level. The results showed a decline of AGC stocks in all the classes from 1972 to 2010. Degraded and transformed thicket classes had the highest AGC stock losses. The decline of AGC stocks was attributed to thicket transformation and degradation which were caused by anthropogenic activities. To map and quantify SOC concentration in partial (fractional) thicket vegetation cover, the spectral reflectance of both thicket vegetation and bare-soils was measured in situ. Soil samples were collected from the sampling sites and transported to the laboratory for spectral reflectance and SOC measurements. Thicket vegetation and bare soil reflectance were measured using spectroscopy both in situ and under laboratory conditions. Their respective endmembers were extracted from ASTER imagery using the Pixel Purity Index (PPI). The endmembers were validated with in situ and laboratory thicket and bare-soil reflectance signatures. The spectral unmixing technique was applied to ASTER imagery to discriminate pure pixels of thicket vegetation and bare-soils; a residual spectral image was produced. The Residual Spectral Unmixing (RSU) procedure was applied to the residual spectral image to produce an RSU soil spectrum image. Partial Least Squares Regression (PSLR) model was developed using spectral signatures of a residual soil spectrum image as the independent variable and SOC concentration measured from soil samples as the dependent variable. The PSLR prediction model was used to predict SOC concentration on the RSU soil spectral image. The predicted SOC concentration was then validated with SOC concentration measured from the field plots. A Strong correlation (R2 = 0.82) was obtained between the predicted SOC concentration and the SOC concentration measured from field samples. The PSLR was then used to generate a map of SOC concentration for the Great Fish River Nature Reserve and its environs. Areas with very low SOC concentrations were found in the degraded communal villages, as opposed to the higher SOC values in the protected area. The results confirmed that RS techniques are key to estimating and mapping the spatial distribution of SOC concentration in partial subtropical thicket vegetation. Partial thicket vegetation has a huge influence on the soil spectra; it can influence the prediction of SOC concentration. The use of the RSU approach eliminates partial thicket vegetation cover from bare soil spectra. The residual soil spectrum image contains enough information for the mapping of SOC concentration. The technique has the potential to augment the applicability of airborne imaging spectroscopy for soil studies in the sub-tropical thicket biome and similar environments.
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Zhang, Ning. "Soil Moisture Mapping in South Central United States by Blending In-situ, Modeled and Remote Sensing Data." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1584465849013608.
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Matthews, Mark William. "Remote Sensing of Water Quality Parameters in Zeekoevlei, a Hypertrophic, Cyanobacteria-Dominated Lake, Cape Town, South Africa." Doctoral thesis, University of Cape Town, 2009. http://hdl.handle.net/11427/4782.
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Rand, Andrew M. "Using Geographic Information Systems and remote sensing to improve the management of kelp resources in South Africa." Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/6165.
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Includes bibliographical references.In 2002 the Department of Environmental Affairs and Tourism (DEA&T), Marine and Coastal Management (M&CM) and the Seaweed Unit undertook a program to document the localities and quantities of the standing crop of the economically important kelps, Ecklonia maxima and Laminaria pallida, in the fourteen commercial seaweed Concession Areas that contain commercial quantities of kelps. The primary objective of this study was to establish a coastal kelp resource database for the South African coastline from Cape Agulhas to the Orange River (the international border with Namibia). The method was designed to integrate past and current analysis of multi-year kelp data from commercial harvesting, biomass and kelp bed extent while allowing for the integration of future surveys within the inventories.
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Zhu, Kefeng. "Application of Satellite Remote Sensing on Mountain Glacier and Coastal Zone Classification And Monitoring in South Asia." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437652636.
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Ndlala, Noluthando. "Remote sensing drought impacts on wetland vegetation productivity at the Soetendalsvlei in the Heuningnes Catchment, South Africa." University of Western Cape, 2021. http://hdl.handle.net/11394/8329.
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>Magister Scientiae - MScThis work aimed at assessing the response of wetland vegetation productivity to the 2014-2017 climate-induced drought at the Soetendalsvlei wetland system in the Western Cape province of South Africa. To achieve this objective, firstly a literature review on the progress of remotely sensed data applications in assessing and monitoring wetland vegetation productivity was conducted. The review elaborates on the role of remote sensing in monitoring and assessing wetland vegetation productivity, with a detailed discussion of the climate change and variability impacts on wetland vegetation productivity. Accurate assessment results are produced when suitable processing techniques are selected as well as appropriate spatial and spectral resolution for extracting spectral information of wetland vegetation productivity. Secondly, wetland vegetation changes and productivity status was assessed using multi-temporal resolution Landsat series imagery and Normalized Difference Vegetation Index (NDVI) during the wet and dry seasons for the period between 2014 and 2018.
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Smit, Walter J. (Walter Johan). "A comparison of selected satellite remote sensing techniques for mapping fire scars in limestone fynbos." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52064.
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Thesis (MA.)--Stellenbosch University, 2001.ENGLISH ABSTRACT: There are many reasons to conserve fynbos. Not only does fynbos form part of the Cape floral kingdom, one of the richest floral kingdoms in the world, but the contribution that it makes to the regional economy through utilisation, education, recreation and tourist opportunities is immeasurable. Fire plays an integral role in fynbos ecosystems. According to Van Wilgen, Richardson & Seydack (1994: 322) " ... managing fynbos equates to managing fire". Therefore managers need accurate fire information about a fynbos area to manage it properly. This is where satellite remote sensing can provide the manager with useful information about the fire regime. In other words, satellite remote sensing can help a manager establish where and when an area has burnt. Using readily available satellite data, this study attempts to establish (through comparison) what techniques would be most suitable and affordable to compile a fire information database. Landsat Thematic Mapper data from 1990 - 1996 of the southwestern Cape was used and compared with existing fire records of the area. The results show that techniques such as supervised and unsupervised classification are reliable in identifying burnt areas, but a major drawback of these techniques is that they require a large amount of user input and knowledge. They are thus not regarded as simple or easily repeatable. - The' more simple techniques like image differencing and image ratioing were also found to be reliable in identifying burnt areas. These techniques require less user input and in some instances less data (image bands) to produce similar (or better) results than supervised and unsupervised classification techniques. The results show that differencing temporally different Images, obtained from applying principle components analysis, produces reliable results with very little confusion and little user input. Using such a technique could enable users to procure only two bands of Landsat data and still produce reliable fire information for managing a fynbos ecosystem.
AFRIKAANSE OPSOMMING: Daar is verskeie redes waarom fynbos bewaar moet word. Nie net vorm dit deel van een van die rykste blommeryke in die wereld nie, maar die bydrae wat dit tot die streeksekonomie maak, deur die benutting van veldblomme en die geleenthede wat dit bied vir toerisme en ontspanning, is enorm. Vuur speel 'n belangrike rol in die bestuur van fynbos ekosisteme. Soos beklemtoon deur Van Wilgen, Richardson & Seydack (1994: 322) se stelling: " ... managing fynbos equates to managing fire". Om hierdie rede is dit belangrik dat 'n bestuurder akkurate inligting oor die verspreiding van veldbrande moet he. Satellietafstandwaarneming kan hier 'n belangrike rol speel deur sulke inligting te verskaf Deur gebruik te maak van maklik bekombare satellietdata, poog hierdie studie om te bepaal (d.m.v. vergelyking) watter tegnieke die mees geskikte is in terme van bekostigbaarheid en gebruikersvriendelikheid. Landsat Thematic Mapper data van 1990 tot 1996 van die suidwes-Kaap is gebruik en vergelyk met bestaande branddata van die studiegebied. Daar is gevind dat tegnieke soos gerigte en nie-gerigte klassifikasie in staat is om gebrande dele betroubaar uit te ken. Hierdie tegnieke verg egter baie insette en kennis van die gebruiker en is ook nie maklik om jaar na jaar te herhaal nie. Daarom word hierdie tegnieke nie aanbeveel nie. Daar is gevind dat die eenvoudiger tegnieke soos veranderingsanalise ook gebrande dele betroubaar kon uitken. Hierdie tegnieke het die voordeel dat die gebruiker nie baie' kennis van die gebied hoef te he nie en ook nie so baie insette hoef te lewer nie. Hierdie tegnieke word bo gerigte en nie-gerigte klassifikasie aanbeveel. - Die resultate dui daarop dat betroubare resultate verkry kan word deur tempo reel verskillende beeIde, verkry deur hoofkomponentanalise, van mekaar af te trek. Hierdie tegniek vereis relatief min gebruikersinsette en daar kan selfs met slegs twee Landsat bande gewerk word. So 'n tegniek kan beslis 'n bekostigbare en effektiewe manier wees om nodige inligting vir die bestuur van 'n fynbos ekosisteem te bekom.
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McIntyre, Daniel Lester. "Application of high resolution remote sensing to detect and map the pasture weed Paterson’s curse (Echium plantagineum) in Western Australia." Thesis, Curtin University, 2015. http://hdl.handle.net/20.500.11937/1511.
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This study investigated the utility of three types of remotely sensed data (field spectroscopy, airborne multispectral and satellite hyperspectral) for detecting and mapping Paterson’s curse (Echium plantagineum) in the Wheatbelt Region of Western Australia. Using different classification, statistical and quantitative validation approaches, the study found that spectral resolution and timing of image capture were the most important factors for discriminating Paterson’s curse and producing acceptable levels of mapping accuracy.
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Stewart-Yates, Zoe. "Evaluating impact and recovery of mangroves following extreme climatic events using satellite remote sensing in Exmouth Gulf, north western Australia." Thesis, Stewart-Yates, Zoe (2022) Evaluating impact and recovery of mangroves following extreme climatic events using satellite remote sensing in Exmouth Gulf, north western Australia. Masters by Coursework thesis, Murdoch University, 2022. https://researchrepository.murdoch.edu.au/id/eprint/64522/.
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The objective of this study was to study mangrove response (impact and recovery) from extreme climatic events such as tropical cyclones, marine heatwaves, and drought events on the eastern shores of Exmouth Gulf. Mangroves in arid regions, like those in Exmouth, are considered the most sensitive to disturbances due to already existing at their physiological limits. Projected increase in frequency, severity and duration of climate extremes is also considered a major challenge for mangroves in the future. Mangroves are critically important communities providing a wide variety of essential ecosystem services and coastal protection, making it important to monitor them from these events and assess recovery.
This study used satellite remote sensing and a multiple endmember spectral mixture analysis (MESMA) to detect and quantify impact and track recovery of mangroves from 1998 to 2021. This study found that greater impacts on mangroves were associated with cyclone and drought events, whereas marine heatwaves did not cause much impact. It was also demonstrated that cyclones tended to result in increases in mangrove cover. A cyclone associated with rainfall occurring before a drought event may have ameliorated extreme drought conditions, potentially reducing the disturbance of this event on mangroves. In addition, recovery from one cyclone was particularly slow, however this may be attributed to an extreme drought event that occurred four years later which also resulted in high impact and slow recovery. This raises the concern of compound impacts slowing recovery of mangroves in the area. Impacts associated with one marine heatwave, considered due to other causes, which resulted in lower magnitudes of negative impact resulted in more rapid mangrove recovery.
This study has found additional impacts on mangroves in Exmouth Gulf that had previously gone unreported, demonstrating the importance of remote sensing in monitoring these communities. In addition, demonstrating the need for further long-term monitoring of these mangroves.
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Motswaledi, Mokhine. "Using remote sensing indices to evaluate habitat intactness in the Bushbuckridge area : a key to effective planning." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96798.
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Thesis (MSc)--Stellenbosch University, 2015.ENGLISH ABSTRACT: Anthropological influences are threatening the state of many savanna ecosystems in most rural landscapes around the world. Effective monitoring and management of these landscapes requires up to date maps and data on the state of the environment. Degradation data over a range of scales is often not readily available due to a lack of financial resources, time and technical capabilities. The aim of this research was to use a medium resolution multispectral SPOT 5 image from 2010 and Landsat 8 images from 2014 to map habitat intactness in the Bushbuckridge and Kruger National Park (KNP) region. The images were pre-processed and segmented into meaningful image objects using an object based image analysis (OBIA) approach. Five image derivatives namely: brightness, compactness, NIR standard deviation, area and the normalised difference vegetation index (NDVI) were evaluated for their capability to model habitat intactness. A habitat intactness index was generated by combining the five derivatives and rescaling them to a data range of 0 to 10, with 0 representing completely transformed areas, 10 being undisturbed natural vegetation. Field data were collected in October 2014 using a field assessment form consisting of 10 questions related to ecosystem state, in order to facilitate comparisons with the remote sensing habitat intactness index. Both satellite data sets yielded low overall accuracies below 30%. The results were improved by applying a correction factor to the reference data. The results significantly improved with SPOT 5 producing the highest overall accuracy of 62.6%. The Landsat 8 image for May 2014 achieved an improved accuracy of 60.2%. The SPOT 5 results showed to be a better predictor of habitat intactness as it assigned natural vegetation with better accuracy, while Landsat 8 correctly assigned mostly degraded areas. These findings suggest that the method was not easily transferable between the different satellite sensors in this savanna landscape, with a high occurrence of forest plantations and rural settlements too. These areas caused high omission errors in the reference data, resulting in the moderate overall accuracies obtained. It is recommended that these sites be clipped out of the analysis in order to obtain acceptable accuracies for non-transformed areas. The study nevertheless demonstrated that the habitat intactness index maps derived can be a useful data source for mapping general patterns of degradation especially on a regional scale. Therefore, the methods tested in this study can be integrated in habitat mapping projects for effective conservation planning.
AFRIKAANSE OPSOMMING: Antropologiese invloede bedreig die toestand van savanna-ekostelsels in die meeste landelike landskappe regoor die wêreld. Doeltreffende monitering en bestuur van hierdie landskappe vereis op datum kaarte en inligting oor die toestand van die omgewing. Agteruitgangsdata van verskillende skale is dikwels nie geredelik beskikbaar nie weens 'n gebrek aan finansiële hulpbronne, tyd en tegniese vermoëns. Die doel van hierdie navorsing was om ‘n hoë resolusie multispektrale SPOT 5 beeld van 2010 en Landsat 8 beelde van 2014 te gebruik om die habitatongeskondenheid in die Bushbuckridge en Kruger Nasionale Park (KNP) streek te karteer. Die beelde is voorverwerk en gesegmenteer om sinvolle beeldvoorwerpe te skep deur die gebruik van ‘n voorwerp gebaseerde beeldanalise (OBIA) benadering. Vyf beeldafgeleides naamlik: helderheid, kompaktheid, NIR standaardafwyking, area en die genormaliseerde verskil plantegroei-indeks (NDVI) is geëvalueer vir hul vermoë om habitat ongeskondenheid te modelleer. ‘n Habitatongeskondenheidsindeks is gegenereer deur die kombinasie van die vyf afgeleides wat herskaal is na 'n datareeks van 0 tot 10, met 0 om totaal getransformeerde gebiede te verteenwoordig en 10 om ongestoorde natuurlike plantegroei voor te stel. Velddata is versamel in Oktober 2014 met gebruik van 'n veldassesseringsvorm, bestaande uit 10 vrae wat verband hou met die toestand van die ekostelsel, om vergelykings met die afstandswaarneming habitatongeskondenheidsindeks te fasiliteer. Beide satellietdatastelle het lae algehele akkuraatheid onder 30% opgelewer. Die resultate is deur die toepassing van 'n regstellingsfaktor tot die verwysing data verbeter. Die resultate het aansienlik verbeter met SPOT 5 wat die hoogste algehele akkuraatheid van 62.6% gelewer het. Die Landsat 8 beeld vir Mei 2014 bereik 'n verbeterde akkuraatheid van 60.2%. Die SPOT 5 resultate het geblyk om ‘n beter voorspeller van habitatongeskondenheid te wees as gevolg van ‘n beter akkuraatheid vir natuurlike plantegroei, terwyl Landsat meestal gedegradeerde gebiede kon voorspel. Hierdie bevindinge dui daarop dat die metode nie maklik oordraagbaar was tussen die verskillende satelliet sensors in hierdie savanna landskap nie, veral as gevolg van ‘n hoë voorkoms van bosbouplantasies en landelike nedersettings. Hierdie gebiede veroorsaak hoë weglatingsfoute in die verwysing data, wat lei tot gematigde algehele akkuraatheid. Dit word aanbeveel dat hierdie areas gemasker word tydens die ontleding om aanvaarbare akkuraatheid te verkry vir nie-getransformeerde gebiede. Nogtans het die studie getoon dat die afgeleide habitatongeskondenheidsindekskaarte ‘n nuttige bron van data kan wees vir die kartering van algemene patrone van agteruitgang, veral op 'n plaaslike skaal. Daarom kan die getoetsde metodes in die studie in habitatkarteringsprojekte vir doeltreffende bewaring beplanning geïntegreer word. Stellenbosch University https://scholar.sun.ac.za
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Prananto, Agnes Kristina. "The use of remotely sensed data to analyse spatial and temporal trends in vegetation patchiness within rehabilitated bauxite mines in the Darling Range, W.A." University of Western Australia. School of Earth and Geographical Sciences, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0012.
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[Truncated abstract] The assessment of rehabilitation success is time consuming and costly for bauxite miners because large areas of land (~550 ha per year) are involved. In some cases, rehabilitation results in patches of bare or sparsely vegetated soil. This study uses remote sensing imagery to evaluate the growth of vegetation in rehabilitated bauxite mines in the Darling Range, W.A. This work has five aims, which are to (1) compare vegetation biomass within rehabilitated areas and nearby native forest; (2) analyse temporal changes in vegetation growth within the selected rehabilitated areas, in particular rehabilitated areas with patches of bare soil; (3) compare vegetation growth pre- and post- mining; (4) identify the best type of remotely sensed data for this particular study area, and (5) develop an index, which can classify the degree of vegetation patchiness within rehabilitated mine sites. This information will enable rehabilitation workers to identify patches in rehabilitated areas that may require further remediation. The study used RADARSAT, nine years of Normalised Difference Vegetation Index (NDVI) maps (extracted from LANDSAT TM multivariate imagery and Quickbird imagery) and aerial photographs to evaluate forty-seven ~1 ha study sites. Image and map analyses were conducted mainly using ESRI’s software ArcGIS 8.3 and ER Mapper 6.4. Ground truthing was carried out to confirm and recognise the causes of bare patches within the rehabilitated mine sites ... The results indicate that differences in rehabilitation management do not affect this index but the extent of bare patches does. Due to the sensitivity of radar imagery to surface roughness, rehabilitated areas cannot be distinguished from the native forest using radar images. A building (crusher) appears to be the same as mature vegetation. Knowledge of the features in an area is therefore crucial when utilising RADARSAT. The beam elevation angle and profile of the RADARSAT image used, made superimposition of radar and optical imageries impossible. Speckle noise in RADARSAT images made it impossible to detect relatively small bare patches. In addition, the many cloud free days in Western Australia make optical imaging possible so that the ability of radar imagery to penetrate cloud is redundant for this type of study.
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net, matt@harves, and Matthew Harvey. "Development of techniques to classify marine benthic habitats using hyperspectral imagery in oligotrophic, temperate waters." Murdoch University, 2009. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20091118.110704.
Full textAbstract:
There is an increasing need for more detailed knowledge about the spatial distribution and structure of shallow water benthic habitats for marine conservation and planning. This, linked with improvements in hyperspectral image sensors provides an increased opportunity to develop new techniques to better utilise these data in marine mapping projects. The oligotrophic, optically-shallow waters surrounding Rottnest Island, Western Australia, provide a unique opportunity to develop and apply these new mapping techniques. The three flight lines of HyMap hyperspectral data flown for the Rottnest Island Reserve (RIR) in April 2004 were corrected for atmospheric effects, sunglint and the influence of the water column using the Modular Inversion and Processing System. A digital bathymetry model was created for the RIR using existing soundings data and used to create a range of topographic variables (e.g. slope) and other spatially relevant environmental variables (e.g. exposure to waves) that could be used to improve the ecological description of the benthic habitats identified in the hyperspectral imagery. A hierarchical habitat classification scheme was developed for Rottnest Island based on the dominant habitat components, such as Ecklonia radiata or Posidonia sinuosa. A library of 296 spectral signatures at HyMap spectral resolution (~15 nm) was created from >6000 in situ measurements of the dominant habitat components and subjected to spectral separation analysis at all levels of the habitat classification scheme. A separation analysis technique was developed using a multivariate statistical optimisation approach that utilised a genetic algorithm in concert with a range of spectral metrics to determine the optimum set of image bands to achieve maximum separation at each classification level using the entire spectral library. These results determined that many of the dominant habitat components could be separated spectrally as pure spectra, although there were almost always some overlapping samples from most classes at each split in the scheme. This led to the development of a classification algorithm that accounted for these overlaps. This algorithm was tested using mixture analysis, which attempted to identify 10 000 synthetically mixed signatures, with a known dominant component, on each run. The algorithm was applied directly to the water-corrected bottom reflectance data to classify the benthic habitats. At the broadest scale, bio-substrate regions were separated from bare substrates in the image with an overall accuracy of 95% and, at the finest scale, bare substrates, Posidonia, Amphibolis, Ecklonia radiata, Sargassum species, algal turf and coral were separated with an accuracy of 70%. The application of these habitat maps to a number of marine planning and management scenarios, such as marine conservation and the placement of boat moorings at dive sites was demonstrated.