The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Yoshiki Yamagata - One of the best experts on this subject based on the ideXlab platform.
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landsat analysis of urban growth how tokyo became the world s largest megacity during the last 40 years
Remote Sensing of Environment, 2012Co-Authors: Héctor Bagán, Yoshiki YamagataAbstract:Abstract Combining remote sensing data and socio-economic data to quantitatively analyze urban growth is a topic growing in importance. We used square grid cells to investigate the spatial and temporal dynamics of urban growth in the Tokyo, Japan, metropolitan area by using remote sensing imagery from 1972 to 2011 and census population data from 1970 to 2010. First, we used the subspace classification method to produce land-cover maps by using Landsat images from 1972, 1987, 2001, and 2011. Next, we integrated the land-cover maps with basic grid cell maps (using the standard 1 km2 grid cell system of Japan) to represent the proportion of each land-cover category within each 1 km2 grid cell area. Finally, we combined the proportional land-cover maps and population census data to investigate the relationship between land-cover Changes and population Density Change based on grid cells. By using grid cells it is straightforward to (i) integrate remote sensing, geographic information system (GIS), and statistical data within the cells; (ii) quantify land-cover Changes in terms of the percentage of area affected and rates of Change and compare them with population census data; and (iii) analyze the spatial-temporal dynamics of urban growth patterns. Between 1972 and 2011 the rapid expansion of the urban area was accompanied by extensive shrinking of the agricultural area around the new settlements. As a result, the urban growth rate exceeded the population growth rate by more than a factor of 2.6. We used the grid cells to investigate the spatial relationship between the Changes of land-cover classes and population Density Change, and then calculated the correlation coefficients of land-cover categories and population Density Changes for 3 intervals between 1972 and 2011 (1972–1987, 1987–2001, and 2001–2011). The results showed that the urban/built-up Density decreased in the metropolitan inner core as the city center experienced depopulation. Spatial correlation analysis showed a strong positive correlation between urban expansion and population Density Change (r = 0.59), and that urban expansion was strongly negatively correlated with cropland Change (r = − 0.77). The results also demonstrated that grid cells allow remote sensing and statistics data to be combined, improving the knowledge, understanding, and analysis of urban dynamics.
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Landsat analysis of urban growth: How Tokyo became the world's largest megacity during the last 40years
Remote Sensing of Environment, 2012Co-Authors: Héctor Bagán, Yoshiki YamagataAbstract:Combining remote sensing data and socio-economic data to quantitatively analyze urban growth is a topic growing in importance. We used square grid cells to investigate the spatial and temporal dynamics of urban growth in the Tokyo, Japan, metropolitan area by using remote sensing imagery from 1972 to 2011 and census population data from 1970 to 2010. First, we used the subspace classification method to produce land-cover maps by using Landsat images from 1972, 1987, 2001, and 2011. Next, we integrated the land-cover maps with basic grid cell maps (using the standard 1km2grid cell system of Japan) to represent the proportion of each land-cover category within each 1km2grid cell area. Finally, we combined the proportional land-cover maps and population census data to investigate the relationship between land-cover Changes and population Density Change based on grid cells. By using grid cells it is straightforward to (i) integrate remote sensing, geographic information system (GIS), and statistical data within the cells; (ii) quantify land-cover Changes in terms of the percentage of area affected and rates of Change and compare them with population census data; and (iii) analyze the spatial-temporal dynamics of urban growth patterns. Between 1972 and 2011 the rapid expansion of the urban area was accompanied by extensive shrinking of the agricultural area around the new settlements. As a result, the urban growth rate exceeded the population growth rate by more than a factor of 2.6. We used the grid cells to investigate the spatial relationship between the Changes of land-cover classes and population Density Change, and then calculated the correlation coefficients of land-cover categories and population Density Changes for 3 intervals between 1972 and 2011 (1972-1987, 1987-2001, and 2001-2011). The results showed that the urban/built-up Density decreased in the metropolitan inner core as the city center experienced depopulation. Spatial correlation analysis showed a strong positive correlation between urban expansion and population Density Change (r=0.59), and that urban expansion was strongly negatively correlated with cropland Change (r=-0.77). The results also demonstrated that grid cells allow remote sensing and statistics data to be combined, improving the knowledge, understanding, and analysis of urban dynamics. © 2012 Elsevier Inc.
Simone Raoux - One of the best experts on this subject based on the ideXlab platform.
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Density Change upon crystallization of Ga-Sb films
Applied Physics Letters, 2014Co-Authors: Magali Putero, Marie-vanessa Coulet, Christophe Muller, Guy Cohen, Marinus Hopstaken, Carsten Baehtz, Simone RaouxAbstract:Besides crystallization time and temperature, the mass Density Change upon crystallization is a key parameter governing the reliability of phase Change random access memory. Indeed, few percentages Density Change induces considerable mechanical stress in memory cells, leading to film delamination with subsequent electrical failures. This letter presents an extensive study of Density Change upon crystallization in a series of Ga-Sb thin films with various antimony contents. The mass Density of the films is precisely determined by x-ray reflectivity in both their amorphous and crystalline states. The variations of the Density in crystalline and amorphous films according to the Sb content found to cross with a zero-Density Change for 70 at. % Sb. The peculiar behavior of Ga-Sb thin films upon crystallization may be linked to their stress state and mechanical properties.
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phase transition in stoichiometric gasb thin films anomalous Density Change and phase segregation
Applied Physics Letters, 2013Co-Authors: Magali Putero, Marie-vanessa Coulet, Christophe Muller, Carsten Baehtz, Toufik Ouledkhachroum, Simone RaouxAbstract:The crystallization of stoichiometric GaSb thin films was studied by combined in situ synchrotron techniques and static laser testing. It is demonstrated that upon crystallization, GaSb thin films exhibit an unusual behaviour with increasing thickness and concomitant decreasing mass Density while its electrical resistance drops as commonly observed in phase Change materials. Furthermore, beyond GaSb amorphous-to-crystalline phase transition, an elemental segregation and a separate crystallization of a pure Sb phase is evidenced.
Héctor Bagán - One of the best experts on this subject based on the ideXlab platform.
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landsat analysis of urban growth how tokyo became the world s largest megacity during the last 40 years
Remote Sensing of Environment, 2012Co-Authors: Héctor Bagán, Yoshiki YamagataAbstract:Abstract Combining remote sensing data and socio-economic data to quantitatively analyze urban growth is a topic growing in importance. We used square grid cells to investigate the spatial and temporal dynamics of urban growth in the Tokyo, Japan, metropolitan area by using remote sensing imagery from 1972 to 2011 and census population data from 1970 to 2010. First, we used the subspace classification method to produce land-cover maps by using Landsat images from 1972, 1987, 2001, and 2011. Next, we integrated the land-cover maps with basic grid cell maps (using the standard 1 km2 grid cell system of Japan) to represent the proportion of each land-cover category within each 1 km2 grid cell area. Finally, we combined the proportional land-cover maps and population census data to investigate the relationship between land-cover Changes and population Density Change based on grid cells. By using grid cells it is straightforward to (i) integrate remote sensing, geographic information system (GIS), and statistical data within the cells; (ii) quantify land-cover Changes in terms of the percentage of area affected and rates of Change and compare them with population census data; and (iii) analyze the spatial-temporal dynamics of urban growth patterns. Between 1972 and 2011 the rapid expansion of the urban area was accompanied by extensive shrinking of the agricultural area around the new settlements. As a result, the urban growth rate exceeded the population growth rate by more than a factor of 2.6. We used the grid cells to investigate the spatial relationship between the Changes of land-cover classes and population Density Change, and then calculated the correlation coefficients of land-cover categories and population Density Changes for 3 intervals between 1972 and 2011 (1972–1987, 1987–2001, and 2001–2011). The results showed that the urban/built-up Density decreased in the metropolitan inner core as the city center experienced depopulation. Spatial correlation analysis showed a strong positive correlation between urban expansion and population Density Change (r = 0.59), and that urban expansion was strongly negatively correlated with cropland Change (r = − 0.77). The results also demonstrated that grid cells allow remote sensing and statistics data to be combined, improving the knowledge, understanding, and analysis of urban dynamics.
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Landsat analysis of urban growth: How Tokyo became the world's largest megacity during the last 40years
Remote Sensing of Environment, 2012Co-Authors: Héctor Bagán, Yoshiki YamagataAbstract:Combining remote sensing data and socio-economic data to quantitatively analyze urban growth is a topic growing in importance. We used square grid cells to investigate the spatial and temporal dynamics of urban growth in the Tokyo, Japan, metropolitan area by using remote sensing imagery from 1972 to 2011 and census population data from 1970 to 2010. First, we used the subspace classification method to produce land-cover maps by using Landsat images from 1972, 1987, 2001, and 2011. Next, we integrated the land-cover maps with basic grid cell maps (using the standard 1km2grid cell system of Japan) to represent the proportion of each land-cover category within each 1km2grid cell area. Finally, we combined the proportional land-cover maps and population census data to investigate the relationship between land-cover Changes and population Density Change based on grid cells. By using grid cells it is straightforward to (i) integrate remote sensing, geographic information system (GIS), and statistical data within the cells; (ii) quantify land-cover Changes in terms of the percentage of area affected and rates of Change and compare them with population census data; and (iii) analyze the spatial-temporal dynamics of urban growth patterns. Between 1972 and 2011 the rapid expansion of the urban area was accompanied by extensive shrinking of the agricultural area around the new settlements. As a result, the urban growth rate exceeded the population growth rate by more than a factor of 2.6. We used the grid cells to investigate the spatial relationship between the Changes of land-cover classes and population Density Change, and then calculated the correlation coefficients of land-cover categories and population Density Changes for 3 intervals between 1972 and 2011 (1972-1987, 1987-2001, and 2001-2011). The results showed that the urban/built-up Density decreased in the metropolitan inner core as the city center experienced depopulation. Spatial correlation analysis showed a strong positive correlation between urban expansion and population Density Change (r=0.59), and that urban expansion was strongly negatively correlated with cropland Change (r=-0.77). The results also demonstrated that grid cells allow remote sensing and statistics data to be combined, improving the knowledge, understanding, and analysis of urban dynamics. © 2012 Elsevier Inc.
Per Hall - One of the best experts on this subject based on the ideXlab platform.
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heritability of mammographic breast Density Density Change microcalcifications and masses
Cancer Research, 2020Co-Authors: Natalie Holowko, Mikael Eriksson, Ralf Kujahalkola, Shadi Azam, Wei He, Per Hall, Kamila CzeneAbstract:Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer (N = 49,674) and a polygenic risk score (PRS, N = 9,365). The heritability of mammographic features such as dense area (MD), microcalcifications, masses, and Density Change (MDC, cm2/year) was estimated using 1,940 sister pairs. Heritability was estimated at 58% [95% confidence interval (CI), 48%–67%) for MD, 23% (2%–45%) for microcalcifications, and 13% (1%–25%)] for masses. The estimated heritability for MDC was essentially null (2%; 95% CI, −8% to 12%). The association between a genetic predisposition to breast cancer (using PRS) and MD and microcalcifications was positive, while for masses this was borderline significant. In addition, for MDC, having a family history of breast cancer was associated with slightly greater MD reduction. In summary, we have confirmed previous findings of heritability in MD, and also established heritability of the number of microcalcifications and masses at baseline. Because these features are associated with breast cancer risk and can improve detecting women at short-term risk of breast cancer, further investigation of common loci associated with mammographic features is warranted to better understand the etiology of breast cancer. Significance: These findings provide novel data on the heritability of microcalcifications, masses, and Density Change, which are all associated with breast cancer risk and can indicate women at short-term risk.
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mammographic Density Change and risk of breast cancer
Journal of the National Cancer Institute, 2020Co-Authors: Shadi Azam, Mikael Eriksson, Kamila Czene, Arvid Sjolander, Roxanna Hellgren, Marike Gabrielson, Per HallAbstract:BACKGROUND: We examined the association between annual mammographic Density Change (MDC) and breast cancer (BC) risk, and how annual MDC influences the association between baseline mammographic Density (MD) and BC risk. METHODS: We used the KARMA cohort of Swedish women (N = 43,810) aged 30-79 years with full access to BC risk factors and mammograms. MD was measured as dense area (cm2) and percent MD using the STRATUS method. We used the contralateral mammogram for women with BC, and randomly selected a mammogram from either left or right breast for healthy women. We calculated relative area MDC between repeated examinations. Relative area MDC was categorized as decreased (>10% decrease/year), stable (no Change) or increased (>10% increase/year). We used Cox proportional hazards regression to estimate the association of BC with MDC and interaction analysis to investigate how MDC modified the association between baseline MD and BC risk. All tests of statistical significance were two sided. RESULTS: In all, 563 women were diagnosed with BC. Compared to women with a decreased MD over time, no statistically significant different in BC risk was seen for women with either stable MD or increasing MD (HR = 1.01, 95% CI = 0.82 to 1.23, P = 0.90 and HR = 0.98, 95%CI= 0.80 to 1.22, P = 0.90 respectively). Categorizing baseline MD and subsequently adding MDC did not seem to influence the association between baseline MD and BC risk. CONCLUSIONS: Our results suggest that annual MDC does not influence BC risk. Furthermore, MDC does not seem to influence the association between baseline MD and BC risk.
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A comprehensive tool for measuring mammographic Density Changes over time.
Breast Cancer Research and Treatment, 2018Co-Authors: Mikael Eriksson, Kamila Czene, Jingmei Li, Karin Leifland, Per HallAbstract:Mammographic Density is a marker of breast cancer risk and diagnostics accuracy. Density Change over time is a strong proxy for response to endocrine treatment and potentially a stronger predictor of breast cancer incidence. We developed STRATUS to analyse digital and analogue images and enable automated measurements of Density Changes over time. Raw and processed images from the same mammogram were randomly sampled from 41,353 healthy women. Measurements from raw images (using FDA approved software iCAD) were used as templates for STRATUS to measure Density on processed images through machine learning. A similar two-step design was used to train Density measures in analogue images. Relative risks of breast cancer were estimated in three unique datasets. An alignment protocol was developed using images from 11,409 women to reduce non-biological variability in Density Change. The protocol was evaluated in 55,073 women having two regular mammography screens. Differences and variances in densities were compared before and after image alignment. The average relative risk of breast cancer in the three datasets was 1.6 [95% confidence interval (CI) 1.3–1.8] per standard deviation of percent mammographic Density. The discrimination was AUC 0.62 (CI 0.60–0.64). The type of image did not significantly influence the risk associations. Alignment decreased the non-biological variability in Density Change and re-estimated the yearly overall percent Density decrease from 1.5 to 0.9%, p
Magali Putero - One of the best experts on this subject based on the ideXlab platform.
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Density Change upon crystallization of Ga-Sb films
Applied Physics Letters, 2014Co-Authors: Magali Putero, Marie-vanessa Coulet, Christophe Muller, Guy Cohen, Marinus Hopstaken, Carsten Baehtz, Simone RaouxAbstract:Besides crystallization time and temperature, the mass Density Change upon crystallization is a key parameter governing the reliability of phase Change random access memory. Indeed, few percentages Density Change induces considerable mechanical stress in memory cells, leading to film delamination with subsequent electrical failures. This letter presents an extensive study of Density Change upon crystallization in a series of Ga-Sb thin films with various antimony contents. The mass Density of the films is precisely determined by x-ray reflectivity in both their amorphous and crystalline states. The variations of the Density in crystalline and amorphous films according to the Sb content found to cross with a zero-Density Change for 70 at. % Sb. The peculiar behavior of Ga-Sb thin films upon crystallization may be linked to their stress state and mechanical properties.
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phase transition in stoichiometric gasb thin films anomalous Density Change and phase segregation
Applied Physics Letters, 2013Co-Authors: Magali Putero, Marie-vanessa Coulet, Christophe Muller, Carsten Baehtz, Toufik Ouledkhachroum, Simone RaouxAbstract:The crystallization of stoichiometric GaSb thin films was studied by combined in situ synchrotron techniques and static laser testing. It is demonstrated that upon crystallization, GaSb thin films exhibit an unusual behaviour with increasing thickness and concomitant decreasing mass Density while its electrical resistance drops as commonly observed in phase Change materials. Furthermore, beyond GaSb amorphous-to-crystalline phase transition, an elemental segregation and a separate crystallization of a pure Sb phase is evidenced.