A multiscale remote sensing assessment of subtropical indigenous forests along the wild coast, South Africa
- Authors: Blessing, Sithole Vhusomuzi
- Date: 2015
- Subjects: Forests and forestry -- South Africa -- Remote sensing , Forest conservation , Remote sensing , Geographic information systems
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:10677 , http://hdl.handle.net/10948/d1021169
- Description: 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.
- Full Text:
- Date Issued: 2015
- Authors: Blessing, Sithole Vhusomuzi
- Date: 2015
- Subjects: Forests and forestry -- South Africa -- Remote sensing , Forest conservation , Remote sensing , Geographic information systems
- Language: English
- Type: Thesis , Doctoral , PhD
- Identifier: vital:10677 , http://hdl.handle.net/10948/d1021169
- Description: 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.
- Full Text:
- Date Issued: 2015
Properties of traveling ionospheric disturbances (TIDs) over the Western Cape, South Africa
- Authors: Tyalimpi, Vumile Mike
- Date: 2015
- Subjects: Doppler radar , Geographic information systems , Traveling ionospheric disturbances -- south Africa , Ionospheric disturbances -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5557 , http://hdl.handle.net/10962/d1017901
- Description: Travelling Ionospheric Disturbances (TIDs) are said to be produced by atmospheric gravitational waves propagating through the neutral ionosphere. These are smaller in amplitude and period when compared to most ionospheric disturbances and hence more difficult to measure. Very little is known about the properties of the travelling ionospheric disturbances (TIDs) over the Southern Hemisphere regions since studies have been conducted mostly over the Northern Hemisphere regions. This study presents a framework, using a High Frequency (HF) Doppler radar to investigate the physical properties and the possible driving mechanisms of TIDs. This research focuses on studying the characteristics of the TIDs, such as period, velocity and temporal variations, using HF Doppler measurements taken in South Africa. By making use of a Wavelet Analysis technique, the TIDs’ characteristics were determined. A statistical summary on speed and direction of propagation of the observed TIDs was performed. The winter medium scale travelling ionospheric disturbances (MSTIDs) observed are generally faster than the summer MSTIDs. For all seasons, the MSTIDs had a preferred south-southwest direction of propagation. Most of the large scale travelling ionospheric disturbances (LSTIDs) were observed during the night and of these, the spring LSTIDs were fastest when compared to autumn and summer LSTIDs. The general direction of travel of the observed LSTIDs is south-southeast. Total Electron Content (TEC), derived from Global Positioning System (GPS) measurements, were used to validate some of the TID results obtained from the HF Doppler data. The Horizontal Wind Model (HWM07), magnetic K index, and solar terminators were used to determine the possible sources of the observed TIDs. Only 41% of the observed TIDs were successfully linked to their possible sources of excitation. The information gathered from this study will be valuable in future radio communications and will serve as means to improve the existing ionospheric models over the South African region.
- Full Text:
- Date Issued: 2015
- Authors: Tyalimpi, Vumile Mike
- Date: 2015
- Subjects: Doppler radar , Geographic information systems , Traveling ionospheric disturbances -- south Africa , Ionospheric disturbances -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5557 , http://hdl.handle.net/10962/d1017901
- Description: Travelling Ionospheric Disturbances (TIDs) are said to be produced by atmospheric gravitational waves propagating through the neutral ionosphere. These are smaller in amplitude and period when compared to most ionospheric disturbances and hence more difficult to measure. Very little is known about the properties of the travelling ionospheric disturbances (TIDs) over the Southern Hemisphere regions since studies have been conducted mostly over the Northern Hemisphere regions. This study presents a framework, using a High Frequency (HF) Doppler radar to investigate the physical properties and the possible driving mechanisms of TIDs. This research focuses on studying the characteristics of the TIDs, such as period, velocity and temporal variations, using HF Doppler measurements taken in South Africa. By making use of a Wavelet Analysis technique, the TIDs’ characteristics were determined. A statistical summary on speed and direction of propagation of the observed TIDs was performed. The winter medium scale travelling ionospheric disturbances (MSTIDs) observed are generally faster than the summer MSTIDs. For all seasons, the MSTIDs had a preferred south-southwest direction of propagation. Most of the large scale travelling ionospheric disturbances (LSTIDs) were observed during the night and of these, the spring LSTIDs were fastest when compared to autumn and summer LSTIDs. The general direction of travel of the observed LSTIDs is south-southeast. Total Electron Content (TEC), derived from Global Positioning System (GPS) measurements, were used to validate some of the TID results obtained from the HF Doppler data. The Horizontal Wind Model (HWM07), magnetic K index, and solar terminators were used to determine the possible sources of the observed TIDs. Only 41% of the observed TIDs were successfully linked to their possible sources of excitation. The information gathered from this study will be valuable in future radio communications and will serve as means to improve the existing ionospheric models over the South African region.
- Full Text:
- Date Issued: 2015
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