The Experts below are selected from a list of 282 Experts worldwide ranked by ideXlab platform
Nobukazu Nakagoshi - One of the best experts on this subject based on the ideXlab platform.
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spatial temporal Gradient Analysis of urban green spaces in jinan china
Landscape and Urban Planning, 2006Co-Authors: Fanhua Kong, Nobukazu NakagoshiAbstract:Abstract In China, rapid urbanization has profoundly transformed the spatial pattern of urban land use, including urban green spaces. The government plans to optimize green spaces to integrate with urban development; this requires an understanding of the process of green space change. Quantification of green space patterns is a prerequisite to understanding green space changes, and is essential for monitoring and assessing green space functions. This paper presents a new method for quantifying and capturing changes in green space patterns, through a case study of Jinan City, China, during 1989–2004. Supported by GIS and remote sensing, the method comprises quantification of local area green spaces by the “moving window” technique (using FRAGSTATS), and a Gradient Analysis involving sampling from the urban center to the fringe. Results demonstrate that the significantly altered green space pattern could be quantified using landscape metrics in each local area. Gradient Analysis undertaken in eight directions from the urban center reflects the changes in and effects of urbanization, and the implementation of government policy. In comparison with quantifying metrics in entire landscapes, this method more effectively links patterns and processes, and can establish an important basis for subsequent Analysis of ecological and socioeconomic functions of green spaces.
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SPATIAL Gradient Analysis OF URBAN GREEN SPACES COMBINED WITH LANDSCAPE METRICS IN JINAN CITY OF CHINA
Chinese Geographical Science, 2005Co-Authors: Kong Fan-hua, Nobukazu Nakagoshi, Yin Hai-wei, Akira KikuchiAbstract:Urban green spaces have been arisen growing concern responded to the social and environmental costs of urban sprawl. A wide range of planning and policies has been and/or will be designed to protect urban green spaces and optimize their spatial pattern. A better design or planning of urban green space can make a major contribution to quality of environment and urban life, and furthermore can decide whether we can have a sustainable development in the urban area. Information about the status quo of urban green spaces can help planners design more effectively. However, how to quantify and capture such information will be the essential question we face. In this paper, to quantify the urban green space, a new method comprising Gradient Analysis, landscape metrics and GIS was developed through a case of Jinan City. The results demonstrate; 1) the Gradient Analysis is a valid and reliable instrument to quantify the urban green space spatial pattern precisely; 2) using moving window, explicit landscape metrics were spatially realized. Compared with quantifying metrics in the entire landscape, it would be better to link pattern with process and establish an important basis for analyzing the ecological and socioeconomic functions of green spaces.
Fanhua Kong - One of the best experts on this subject based on the ideXlab platform.
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spatial temporal Gradient Analysis of urban green spaces in jinan china
Landscape and Urban Planning, 2006Co-Authors: Fanhua Kong, Nobukazu NakagoshiAbstract:Abstract In China, rapid urbanization has profoundly transformed the spatial pattern of urban land use, including urban green spaces. The government plans to optimize green spaces to integrate with urban development; this requires an understanding of the process of green space change. Quantification of green space patterns is a prerequisite to understanding green space changes, and is essential for monitoring and assessing green space functions. This paper presents a new method for quantifying and capturing changes in green space patterns, through a case study of Jinan City, China, during 1989–2004. Supported by GIS and remote sensing, the method comprises quantification of local area green spaces by the “moving window” technique (using FRAGSTATS), and a Gradient Analysis involving sampling from the urban center to the fringe. Results demonstrate that the significantly altered green space pattern could be quantified using landscape metrics in each local area. Gradient Analysis undertaken in eight directions from the urban center reflects the changes in and effects of urbanization, and the implementation of government policy. In comparison with quantifying metrics in entire landscapes, this method more effectively links patterns and processes, and can establish an important basis for subsequent Analysis of ecological and socioeconomic functions of green spaces.
Kenbu Teramoto - One of the best experts on this subject based on the ideXlab platform.
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Eigenvalue Imaging of A0-Mode Lamb Wave Field Based on Spatio-Temporal Gradient Analysis
Acoustical Imaging, 2008Co-Authors: Kenbu Teramoto, A. UekiharaAbstract:The eigenvalue imaging based on the spatio-temporal Gradient Analysis is proposed in this paper. The third largest eigenvalue of a covariance matrix defined over the 4-dimensional vector space which is spanned by following components: (1) a vertical (z-directional) displacement, (2) its vertical particle velocity, (3) x-directional and (4) y-directional out-of-plane strains has an ability to classify the Lamb-wave field. Focusing the rank of the covariance matrix, we can find following facts: (1) rank=2: when no-reflected wave exists over the Lamb-wave field, or even when reflected waves exist only on the collinearly with an incident waves, (2) rank=3: in other cases. In this study, the eigenvalue imaging based on the spatio-temporal Gradient Analysis is discussed and the physical meanings of the eigenvalue imaging are investigated by numerical and acoustical experiments.
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Multilayered spatio‐temporal Gradient Analysis for acoustic blind source separation
The Journal of the Acoustical Society of America, 2006Co-Authors: Kenbu Teramoto, Tawhidul Islam Khan, Seiichirou Torisu, Akito UekiharaAbstract:A novel blind source separation of a mixture of two or more voice signals has been proposed in the present paper. The separation system has been focused based on the spatio‐temporal Gradient Analysis. The proposed algorithm utilizes the linearity among the signals: sound pressure of source signals, the three‐dimensional (x, y, and z directional) particle velocity vector, and its Gradient of the observed signals, all of which are governed by the equation of motion. Principally, as the mechanism of blind source separation uses no‐ priori information about the parameters of convolution, filtering as well as mixing of source signals, some simple assumptions such as the statistical independency of the linearly combined (mixed) observed signals containing zero mean as well as unit variance have been implied in the present separation algorithm. Therefore, the proposed method has successfully simplified the convoluted blind source separation problem into an instantaneous blind source separation problem over the s...
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Omnidirectional robotic ear based on the spatio-temporal Gradient Analysis with blind signal separation
2004Co-Authors: K. Tsuruta, Kenbu TeramotoAbstract:This paper presents a method for a robotic ear based on the spatio-temporal Gradient Analysis with blind signal separation that estimates the object signals from overlapped signals. By using the spatial derivatives of mixed signals, not only the object source signals but also the arrival directions are estimated. The effectiveness of the proposed method is confirmed through the numerical experiment.
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Local phase velocimetry based on the spatio-temporal Gradient Analysis
2004Co-Authors: Kenbu Teramoto, Kohsuke TsurutaAbstract:Ultrasonic Lamb-wave techniques are potential candidates of non-destructive evaluation (NDE) methodology. The phase velocimetry in the material mostly is done by measuring the time-of-flight and distance between a pair of transmitter and receiver. This paper proposes a novel method of local phase velocimetry based on the spatio-temporal Gradient Analysis. The method has an ability to measure the local phase velocity of the zeroth order anti-symmetric Lamb wave field through the linearity among the four-dimensional vectors which is defined by following components: 1:a vertical displacement, 2:vertical particle velocity, and 3,4:a pair of shear strains of the surface. In this study, the computational process of the local phase velocimetry is discussed and their physical meanings are investigated through numerical experiments.
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delamination monitoring by the local velocimetry based on the spatio temporal Gradient Analysis
Society of Instrument and Control Engineers of Japan, 2003Co-Authors: Kenbu Teramoto, K. TsurutaAbstract:In this paper, a novel method of local phase velocimetry based on the spatio-temporal Gradient Analysis is proposed. The proposed method has an ability to measure the local phase velocity of the zero/sup th/ order anti-symmetric Lamb wave field through the linearity among following four components: a vertical displacement, its vertical velocity, and a pair of out-of-plane shearing strains of the surface. In this study, the computational process in the Lamb wave field near the defects is discussed and their physical meanings are investigated through FDTD-simulations.
Glenn De'ath - One of the best experts on this subject based on the ideXlab platform.
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Principal curves: A new technique for indirect and direct Gradient Analysis
Ecology, 1999Co-Authors: Glenn De'athAbstract:Principal curves are smooth one-dimensional curves in a high dimensional space that are ideally suited for indirect Gradient Analysis of multispecies abundance data. A principal curves ordination will simultaneously estimate the species response curves and locate sites on a single ecological Gradient. By means of theoretical argument and simulations, they are shown to be superior to both correspondence Analysis and multidimensional scaling, outperforming them in 77% and 72% of simulations, respectively. The species response curves used in the simulations varied from simple Gaussian form with equal maxima and tolerances to complex multimodal curves with varying maxima and tolerances. Simulations were conducted both with and without noise. When species response curves are smooth, and a reasonable initial configuration is provided, principal curve Gradient Analysis can succeed even when the curves are complex and beta diversity is high. Principal curves can also be adapted for direct Gradient Analysis in order to relate species composition to environmental variables. Although ordination techniques are used both to uncover ecological Gradients and to represent species composition, it is argued that these two aims are distinct. Hence, a single ordination technique cannot generally achieve both objectives simultaneously. However, by superimposing a principal curve on a principal components biplot, joint representation of an ecological Gradient and species composition can be achieved. Information from either an indirect or direct principal curve Gradient Analysis can be added to the biplot, thereby relating environmental variables to species composition and locations of sites on the Gradient. Two ecological data sets, comprising abundances of hunting spiders and species of grasses, are analyzed using principal curve Gradient Analysis. The results are contrasted with previous analyses, using canonical-correspondence Analysis and canonical-correlation Analysis, and indicate that principal curve Gradient Analysis can find one-dimensional Gradients that explain species composition as well as, or better than, higher dimensional solutions from other techniques. This, in turn, can lead to a more succinct representation and better understanding of ecological systems.
Ladislav Mucina - One of the best experts on this subject based on the ideXlab platform.
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Quantifying the effects of ecological constraints on trait expression using novel trait-Gradient Analysis parameters.
Ecology and evolution, 2017Co-Authors: Gianluigi Ottaviani, James L. Tsakalos, Gunnar Keppel, Ladislav MucinaAbstract:CITATION: Ottaviani, G., et al. 2017. Quantifying the effects of ecological constraints on trait expression using novel trait-Gradient Analysis parameters. Ecology and Evolution, 8(1):435-440, doi:10.1002/ece3.3541.
