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Recent Changes in Glacier Facies Zonation on Devon Ice Cap, Nunavut, Detected from SAR Imagery and Field Validation Methodsde Jong, Johannes Tyler 29 July 2013 (has links)
Glacier facies represent distinct regions of a glacier surface characterized by near surface structure and density that develop as a function of spatial variations in surface melt and accumulation. In post freeze-up (autumn) synthetic aperture radar (SAR) satellite imagery, the glacier ice zone and dry snow zone have a relatively low backscatter due to the greater penetration of the radar signal into the surface. Conversely, the saturation and percolation zones are identifiable based on their high backscatter due to the presence of ice lenses and pipes acting as efficient scatterers. In this study, EnviSat ASAR imagery is used to monitor the progression of facies zones across Devon Ice Cap (DIC) from 2004 to 2011. This data is validated against in situ surface temperatures, mass balance data, and ground penetrating radar surveys from the northwest sector of DIC. Based on calibrated (sigma nought) EnviSat ASAR backscatter values, imagery from autumn 2004 to 2011 shows the disappearance of the ‘pseudo’ dry snow zone at high elevations, the migration of the glacier and superimposed ice zones to higher elevations, and reduction in area of the saturation/percolation zone. In 2011, the glacier and superimposed ice zone were at their largest extent, occupying 92% of the ice cap, leaving the saturation/percolation zone at 8% of the total area. This is indicative of anomalously high summer melt and strongly negative mass balance conditions on DIC, which results in the infilling of pore space in the exposed firn and consequent densification of the ice cap at higher elevations.
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Recent Changes in Glacier Facies Zonation on Devon Ice Cap, Nunavut, Detected from SAR Imagery and Field Validation Methodsde Jong, Johannes Tyler January 2013 (has links)
Glacier facies represent distinct regions of a glacier surface characterized by near surface structure and density that develop as a function of spatial variations in surface melt and accumulation. In post freeze-up (autumn) synthetic aperture radar (SAR) satellite imagery, the glacier ice zone and dry snow zone have a relatively low backscatter due to the greater penetration of the radar signal into the surface. Conversely, the saturation and percolation zones are identifiable based on their high backscatter due to the presence of ice lenses and pipes acting as efficient scatterers. In this study, EnviSat ASAR imagery is used to monitor the progression of facies zones across Devon Ice Cap (DIC) from 2004 to 2011. This data is validated against in situ surface temperatures, mass balance data, and ground penetrating radar surveys from the northwest sector of DIC. Based on calibrated (sigma nought) EnviSat ASAR backscatter values, imagery from autumn 2004 to 2011 shows the disappearance of the ‘pseudo’ dry snow zone at high elevations, the migration of the glacier and superimposed ice zones to higher elevations, and reduction in area of the saturation/percolation zone. In 2011, the glacier and superimposed ice zone were at their largest extent, occupying 92% of the ice cap, leaving the saturation/percolation zone at 8% of the total area. This is indicative of anomalously high summer melt and strongly negative mass balance conditions on DIC, which results in the infilling of pore space in the exposed firn and consequent densification of the ice cap at higher elevations.
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Monitoramento da zona superficial de neve úmida da Península Antártica pelo uso de dados dos sensores SMMR e SSM/IMendes Junior, Claudio Wilson January 2011 (has links)
Dados EASE-grid do Special Sensor Microwave-Imager (SSM/I) e imagens classificadas ASAR wideswath (WS), cobrindo a Península Antártica (PA), foram processadas e usadas em um Modelo Linear de Mistura Espectral (MLME), para a análise subpixel da Zona Superficial de Neve Úmida (ZSNU) em imagens SSM/I. As proporções dos componentes puros (imagens-fração) da área de estudo (ZSNU, Zona Superficial de Neve Seca e rochas) foram derivadas das imagens ASAR classificadas. As imagens-fração e imagens SSM/I co-registradas de mesma data (bandas 19H, 19V, 37H e 37V) foram usadas no MLME para estimar as assinaturas espectrais desconhecidas (i.e., temperatura de brilho em cada banda SSM/I). Essas assinaturas espectrais foram então usadas no MLME para estimar as imagens-fração da ZSNU, as quais foram comparadas com as imagens-fração ASAR correspondentes, por meio do cálculo do coeficiente de correlação. Foram identificadas as duas assinaturas espectrais que resultaram nos dados mais correlacionados, sendo também calculadas as correlações das imagens-fração da ZSNU resultantes do uso no MLME dos valores médio e mediano das assinaturas espectrais mais similares. Os valores medianos dessas assinaturas espectrais produziram as imagens-fração da ZSNU mais correlacionadas, que tiveram uma precisão global de classificação média (PGCM) de 95,6% e 97,3%, nas imagens de primavera e outono, respectivamente (amplitude de classes de 0,1), e uma PGCM de 72,6% nas imagens de verão (amplitude de classes de 0,2). Essas assinaturas espectrais medianas foram então usadas no MLME para estimar, com esses níveis de precisão global, a intensidade e extensão da ZSNU na PA, pelo uso de imagens calibradas SSM/I e SMMR (Scanning Multichannel Microwave Radiometer), possibilitando assim a análise diária e em nível subpixel dessa fácie superficial, de 1978 a 2008. Na análise espacial das imagens-fração da ZSNU estimadas, observou-se que o derretimento superficial médio começava no final de outubro e terminava no final de março, com auge em 7 de janeiro (cerca de 172.237 km2 ou 31,6% da área da PA). A área total mediana da ZSNU no verão foi de aproximadamente 105.100 km2. A análise de regressão com as imagens-fração dos verões entre 1978-1979 a 2007-2008 revelou a tendência de redução da área da ZSNU, totalizando 330,854 km2 nesse período. Todavia, essa tendência não é estatisticamente significante, devido à alta variabilidade interanual da área da ZSNU na PA. Forte derretimento superficial ocorreu nos verões de 1984-1985 (176.507,289 km2) e 1989-1990 (172.681,867 km2), enquanto fraco derretimento, nos verões de 1993-1994 (26.392,208 km2) e 1981-1982 (23.244,341 km2). O mais persistente e intenso derretimento superficial foi observado nas plataformas de gelo Larsen, Wilkins, George VI e Wordie e isto foi relacionado com os eventos de fragmentação e desintegração dessas massas de gelo, ocorridos nas últimas décadas. O derretimento superficial está intimamente relacionado com a estabilidade do sistema glacial antártico e com mudanças no nível médio dos mares. Esse poderia ser monitorado em toda a Antártica, por meio da análise subpixel de imagens SMMR e SSM/I proposta neste estudo. / Special Sensor Microwave-Imager (SSM/I) EASE-grid data and classified ASAR wideswath (WS) images, covering the Antarctic Peninsula (AP), were processed and used in a Spectral Linear Mixing Model (SLMM) for a subpixel analysis of the Wet Snow Zone (WSZ) in SSM/I images. The components’ proportions (fraction images) of the endmembers in the study area, namely WSZ, Dry Snow Zone and rock outcrops, were derived from classified ASAR images. These fraction images and co-registered SSM/I images (bands 19H, 19V, 37H and 37V), acquired on the same date, were used in the SLMM to estimate the unknown spectral signatures (i.e., brightness temperature on each SSM/I band). These spectral signatures were used to estimate WSZ fraction images, which were compared with the ASAR fraction images, by calculating the correlation coefficients. This work identified two spectral signatures that produced the most correlated data, and determined the WSZ fraction images correlations resulting from the use, in the SLMM, of the mean and median values of the most similar spectral signatures. The median values of these spectral signatures produced the most correlated WSZ fraction images, which had an average overall classification accuracy (AOCA) of 95.6% and 97.3% for spring and autumn fraction images, respectively (class range of 0.1), and an AOCA of 72.6% for summer fraction images (class range of 0.2). These median spectral signatures were then used in a SLMM to estimate accurately the WSZ intensity and its extension on the AP, by using calibrated SSM/I and SMMR (Scanning Multichannel Microwave Radiometer) imageries, allowing a daily subpixel analysis of this glacier facie on the AP from 1978 to 2008. Based on the spatial analysis of the WSZ fraction images, it was observed that melt primarily takes place in late October and ends in late March, with peak on January 7th (about 172,237 km2 or 31,6% of the AP area). The WSZ median total area in summer was about 105,100 km2. Regression analysis over the 1978-1979 to 2007-2008 summers, revealed a negative interanual trend in surface melt of 330.854 km2. Nevertheless, this trend inference is not statistically significant, due to the high WSZ interanual variability. Extremely high melt occurred in the 1984-1985 (176,507.289 km2) and 1989-1990 (172,681.867 km2) summers, while extremely weak melt occurred in the 1993-1994 (26,392.208 km2) and 1981-1982 (23,244.341 km2) summers. The most persistent and intensive melt was observed on Larsen, Wilkins, George VI and Wordie ice shelves and it was related to the break-up and disintegration events that occurred on these glaciers in the last decades. Surface melting is closely related to the stability of the Antarctic glacial system and global sea level changes. It could be monitored for the whole Antarctica, by using the WSZ subpixel analysis in SMMR and SSM/I imageries proposed by this study.
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Monitoramento da zona superficial de neve úmida da Península Antártica pelo uso de dados dos sensores SMMR e SSM/IMendes Junior, Claudio Wilson January 2011 (has links)
Dados EASE-grid do Special Sensor Microwave-Imager (SSM/I) e imagens classificadas ASAR wideswath (WS), cobrindo a Península Antártica (PA), foram processadas e usadas em um Modelo Linear de Mistura Espectral (MLME), para a análise subpixel da Zona Superficial de Neve Úmida (ZSNU) em imagens SSM/I. As proporções dos componentes puros (imagens-fração) da área de estudo (ZSNU, Zona Superficial de Neve Seca e rochas) foram derivadas das imagens ASAR classificadas. As imagens-fração e imagens SSM/I co-registradas de mesma data (bandas 19H, 19V, 37H e 37V) foram usadas no MLME para estimar as assinaturas espectrais desconhecidas (i.e., temperatura de brilho em cada banda SSM/I). Essas assinaturas espectrais foram então usadas no MLME para estimar as imagens-fração da ZSNU, as quais foram comparadas com as imagens-fração ASAR correspondentes, por meio do cálculo do coeficiente de correlação. Foram identificadas as duas assinaturas espectrais que resultaram nos dados mais correlacionados, sendo também calculadas as correlações das imagens-fração da ZSNU resultantes do uso no MLME dos valores médio e mediano das assinaturas espectrais mais similares. Os valores medianos dessas assinaturas espectrais produziram as imagens-fração da ZSNU mais correlacionadas, que tiveram uma precisão global de classificação média (PGCM) de 95,6% e 97,3%, nas imagens de primavera e outono, respectivamente (amplitude de classes de 0,1), e uma PGCM de 72,6% nas imagens de verão (amplitude de classes de 0,2). Essas assinaturas espectrais medianas foram então usadas no MLME para estimar, com esses níveis de precisão global, a intensidade e extensão da ZSNU na PA, pelo uso de imagens calibradas SSM/I e SMMR (Scanning Multichannel Microwave Radiometer), possibilitando assim a análise diária e em nível subpixel dessa fácie superficial, de 1978 a 2008. Na análise espacial das imagens-fração da ZSNU estimadas, observou-se que o derretimento superficial médio começava no final de outubro e terminava no final de março, com auge em 7 de janeiro (cerca de 172.237 km2 ou 31,6% da área da PA). A área total mediana da ZSNU no verão foi de aproximadamente 105.100 km2. A análise de regressão com as imagens-fração dos verões entre 1978-1979 a 2007-2008 revelou a tendência de redução da área da ZSNU, totalizando 330,854 km2 nesse período. Todavia, essa tendência não é estatisticamente significante, devido à alta variabilidade interanual da área da ZSNU na PA. Forte derretimento superficial ocorreu nos verões de 1984-1985 (176.507,289 km2) e 1989-1990 (172.681,867 km2), enquanto fraco derretimento, nos verões de 1993-1994 (26.392,208 km2) e 1981-1982 (23.244,341 km2). O mais persistente e intenso derretimento superficial foi observado nas plataformas de gelo Larsen, Wilkins, George VI e Wordie e isto foi relacionado com os eventos de fragmentação e desintegração dessas massas de gelo, ocorridos nas últimas décadas. O derretimento superficial está intimamente relacionado com a estabilidade do sistema glacial antártico e com mudanças no nível médio dos mares. Esse poderia ser monitorado em toda a Antártica, por meio da análise subpixel de imagens SMMR e SSM/I proposta neste estudo. / Special Sensor Microwave-Imager (SSM/I) EASE-grid data and classified ASAR wideswath (WS) images, covering the Antarctic Peninsula (AP), were processed and used in a Spectral Linear Mixing Model (SLMM) for a subpixel analysis of the Wet Snow Zone (WSZ) in SSM/I images. The components’ proportions (fraction images) of the endmembers in the study area, namely WSZ, Dry Snow Zone and rock outcrops, were derived from classified ASAR images. These fraction images and co-registered SSM/I images (bands 19H, 19V, 37H and 37V), acquired on the same date, were used in the SLMM to estimate the unknown spectral signatures (i.e., brightness temperature on each SSM/I band). These spectral signatures were used to estimate WSZ fraction images, which were compared with the ASAR fraction images, by calculating the correlation coefficients. This work identified two spectral signatures that produced the most correlated data, and determined the WSZ fraction images correlations resulting from the use, in the SLMM, of the mean and median values of the most similar spectral signatures. The median values of these spectral signatures produced the most correlated WSZ fraction images, which had an average overall classification accuracy (AOCA) of 95.6% and 97.3% for spring and autumn fraction images, respectively (class range of 0.1), and an AOCA of 72.6% for summer fraction images (class range of 0.2). These median spectral signatures were then used in a SLMM to estimate accurately the WSZ intensity and its extension on the AP, by using calibrated SSM/I and SMMR (Scanning Multichannel Microwave Radiometer) imageries, allowing a daily subpixel analysis of this glacier facie on the AP from 1978 to 2008. Based on the spatial analysis of the WSZ fraction images, it was observed that melt primarily takes place in late October and ends in late March, with peak on January 7th (about 172,237 km2 or 31,6% of the AP area). The WSZ median total area in summer was about 105,100 km2. Regression analysis over the 1978-1979 to 2007-2008 summers, revealed a negative interanual trend in surface melt of 330.854 km2. Nevertheless, this trend inference is not statistically significant, due to the high WSZ interanual variability. Extremely high melt occurred in the 1984-1985 (176,507.289 km2) and 1989-1990 (172,681.867 km2) summers, while extremely weak melt occurred in the 1993-1994 (26,392.208 km2) and 1981-1982 (23,244.341 km2) summers. The most persistent and intensive melt was observed on Larsen, Wilkins, George VI and Wordie ice shelves and it was related to the break-up and disintegration events that occurred on these glaciers in the last decades. Surface melting is closely related to the stability of the Antarctic glacial system and global sea level changes. It could be monitored for the whole Antarctica, by using the WSZ subpixel analysis in SMMR and SSM/I imageries proposed by this study.
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Monitoramento da zona superficial de neve úmida da Península Antártica pelo uso de dados dos sensores SMMR e SSM/IMendes Junior, Claudio Wilson January 2011 (has links)
Dados EASE-grid do Special Sensor Microwave-Imager (SSM/I) e imagens classificadas ASAR wideswath (WS), cobrindo a Península Antártica (PA), foram processadas e usadas em um Modelo Linear de Mistura Espectral (MLME), para a análise subpixel da Zona Superficial de Neve Úmida (ZSNU) em imagens SSM/I. As proporções dos componentes puros (imagens-fração) da área de estudo (ZSNU, Zona Superficial de Neve Seca e rochas) foram derivadas das imagens ASAR classificadas. As imagens-fração e imagens SSM/I co-registradas de mesma data (bandas 19H, 19V, 37H e 37V) foram usadas no MLME para estimar as assinaturas espectrais desconhecidas (i.e., temperatura de brilho em cada banda SSM/I). Essas assinaturas espectrais foram então usadas no MLME para estimar as imagens-fração da ZSNU, as quais foram comparadas com as imagens-fração ASAR correspondentes, por meio do cálculo do coeficiente de correlação. Foram identificadas as duas assinaturas espectrais que resultaram nos dados mais correlacionados, sendo também calculadas as correlações das imagens-fração da ZSNU resultantes do uso no MLME dos valores médio e mediano das assinaturas espectrais mais similares. Os valores medianos dessas assinaturas espectrais produziram as imagens-fração da ZSNU mais correlacionadas, que tiveram uma precisão global de classificação média (PGCM) de 95,6% e 97,3%, nas imagens de primavera e outono, respectivamente (amplitude de classes de 0,1), e uma PGCM de 72,6% nas imagens de verão (amplitude de classes de 0,2). Essas assinaturas espectrais medianas foram então usadas no MLME para estimar, com esses níveis de precisão global, a intensidade e extensão da ZSNU na PA, pelo uso de imagens calibradas SSM/I e SMMR (Scanning Multichannel Microwave Radiometer), possibilitando assim a análise diária e em nível subpixel dessa fácie superficial, de 1978 a 2008. Na análise espacial das imagens-fração da ZSNU estimadas, observou-se que o derretimento superficial médio começava no final de outubro e terminava no final de março, com auge em 7 de janeiro (cerca de 172.237 km2 ou 31,6% da área da PA). A área total mediana da ZSNU no verão foi de aproximadamente 105.100 km2. A análise de regressão com as imagens-fração dos verões entre 1978-1979 a 2007-2008 revelou a tendência de redução da área da ZSNU, totalizando 330,854 km2 nesse período. Todavia, essa tendência não é estatisticamente significante, devido à alta variabilidade interanual da área da ZSNU na PA. Forte derretimento superficial ocorreu nos verões de 1984-1985 (176.507,289 km2) e 1989-1990 (172.681,867 km2), enquanto fraco derretimento, nos verões de 1993-1994 (26.392,208 km2) e 1981-1982 (23.244,341 km2). O mais persistente e intenso derretimento superficial foi observado nas plataformas de gelo Larsen, Wilkins, George VI e Wordie e isto foi relacionado com os eventos de fragmentação e desintegração dessas massas de gelo, ocorridos nas últimas décadas. O derretimento superficial está intimamente relacionado com a estabilidade do sistema glacial antártico e com mudanças no nível médio dos mares. Esse poderia ser monitorado em toda a Antártica, por meio da análise subpixel de imagens SMMR e SSM/I proposta neste estudo. / Special Sensor Microwave-Imager (SSM/I) EASE-grid data and classified ASAR wideswath (WS) images, covering the Antarctic Peninsula (AP), were processed and used in a Spectral Linear Mixing Model (SLMM) for a subpixel analysis of the Wet Snow Zone (WSZ) in SSM/I images. The components’ proportions (fraction images) of the endmembers in the study area, namely WSZ, Dry Snow Zone and rock outcrops, were derived from classified ASAR images. These fraction images and co-registered SSM/I images (bands 19H, 19V, 37H and 37V), acquired on the same date, were used in the SLMM to estimate the unknown spectral signatures (i.e., brightness temperature on each SSM/I band). These spectral signatures were used to estimate WSZ fraction images, which were compared with the ASAR fraction images, by calculating the correlation coefficients. This work identified two spectral signatures that produced the most correlated data, and determined the WSZ fraction images correlations resulting from the use, in the SLMM, of the mean and median values of the most similar spectral signatures. The median values of these spectral signatures produced the most correlated WSZ fraction images, which had an average overall classification accuracy (AOCA) of 95.6% and 97.3% for spring and autumn fraction images, respectively (class range of 0.1), and an AOCA of 72.6% for summer fraction images (class range of 0.2). These median spectral signatures were then used in a SLMM to estimate accurately the WSZ intensity and its extension on the AP, by using calibrated SSM/I and SMMR (Scanning Multichannel Microwave Radiometer) imageries, allowing a daily subpixel analysis of this glacier facie on the AP from 1978 to 2008. Based on the spatial analysis of the WSZ fraction images, it was observed that melt primarily takes place in late October and ends in late March, with peak on January 7th (about 172,237 km2 or 31,6% of the AP area). The WSZ median total area in summer was about 105,100 km2. Regression analysis over the 1978-1979 to 2007-2008 summers, revealed a negative interanual trend in surface melt of 330.854 km2. Nevertheless, this trend inference is not statistically significant, due to the high WSZ interanual variability. Extremely high melt occurred in the 1984-1985 (176,507.289 km2) and 1989-1990 (172,681.867 km2) summers, while extremely weak melt occurred in the 1993-1994 (26,392.208 km2) and 1981-1982 (23,244.341 km2) summers. The most persistent and intensive melt was observed on Larsen, Wilkins, George VI and Wordie ice shelves and it was related to the break-up and disintegration events that occurred on these glaciers in the last decades. Surface melting is closely related to the stability of the Antarctic glacial system and global sea level changes. It could be monitored for the whole Antarctica, by using the WSZ subpixel analysis in SMMR and SSM/I imageries proposed by this study.
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