As responses to metropolitan suburbanization and rural urbanization,the formation and evolution of urban fringes should be understood against the background of overall economic development and spatial reconstruction o...As responses to metropolitan suburbanization and rural urbanization,the formation and evolution of urban fringes should be understood against the background of overall economic development and spatial reconstruction of entire metropolises.At the same time,however,endogenous interactions between industrial structure and spatial patterns of non-agricultural activities are also worthy of scholarly attention.Since the 1980s,studies on urban fringes in China have been restricted by the lack of micro-level data.This paper investigates the spatial expansion and structural evolution of the urban fringe by taking the case of Beijing and uses systematic firm-level data in 1996 and 2001 from the National Census of Basic Units.The diversity of distribution patterns across industrial sectors brings about two interrelated results.On the one hand,structural adjustment of non-agricultural industries promotes the expansion and spatial evolution of the urban fringe.On the other hand,the stability and dynamics of industrial structure coexist in the moving urban fringe.This study also reveals that the outward-moving urban fringe is the optimal location for manufacturing,especially heavy manufacturing,as well as traditional producer and consumer services.However,industries with spatial stickiness such as tourism and sports have not moved with the fringe.Most advanced services remain concentrated in the city center.The authors argue that it is essential for understanding and managing urban fringes to take into account spatial evolution and industrial structural adjustment together with their interaction with each other.展开更多
A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rat...A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.展开更多
In this paper, we propose the novel method of complex least squares adjustment （CLSA） to invert vegetation height accurately using single-baseline polarimetric synthetic aperture radar interferometry （PollnSAR） da...In this paper, we propose the novel method of complex least squares adjustment （CLSA） to invert vegetation height accurately using single-baseline polarimetric synthetic aperture radar interferometry （PollnSAR） data. CLSA basically estimates both volume-only coherence and ground phase directly without assuming that the ground-to-volume amplitude radio of a particular polarization channel （e.g., HV） is less than -10 dB, as in the three-stage method. In addition, CLSA can effectively limit errors in interferometric complex coherence, which may translate directly into erroneous ground-phase and volume-only coherence estimations. The proposed CLSA method is validated with BioSAR2008 P-band E-SAR and L-band SIR-C PollnSAR data. Its results are then compared with those of the traditional three-stage method and with external data. It implies that the CLSA method is much more robust than the three-stage method.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.40830746,40871075)
文摘As responses to metropolitan suburbanization and rural urbanization,the formation and evolution of urban fringes should be understood against the background of overall economic development and spatial reconstruction of entire metropolises.At the same time,however,endogenous interactions between industrial structure and spatial patterns of non-agricultural activities are also worthy of scholarly attention.Since the 1980s,studies on urban fringes in China have been restricted by the lack of micro-level data.This paper investigates the spatial expansion and structural evolution of the urban fringe by taking the case of Beijing and uses systematic firm-level data in 1996 and 2001 from the National Census of Basic Units.The diversity of distribution patterns across industrial sectors brings about two interrelated results.On the one hand,structural adjustment of non-agricultural industries promotes the expansion and spatial evolution of the urban fringe.On the other hand,the stability and dynamics of industrial structure coexist in the moving urban fringe.This study also reveals that the outward-moving urban fringe is the optimal location for manufacturing,especially heavy manufacturing,as well as traditional producer and consumer services.However,industries with spatial stickiness such as tourism and sports have not moved with the fringe.Most advanced services remain concentrated in the city center.The authors argue that it is essential for understanding and managing urban fringes to take into account spatial evolution and industrial structural adjustment together with their interaction with each other.
基金Project(2013CB733605)supported by the National Basic Research Program of ChinaProject(21176073)supported by the National Natural Science Foundation of China
文摘A modified harmony search algorithm with co-evolutional control parameters(DEHS), applied through differential evolution optimization, is proposed. In DEHS, two control parameters, i.e., harmony memory considering rate and pitch adjusting rate, are encoded as a symbiotic individual of an original individual(i.e., harmony vector). Harmony search operators are applied to evolving the original population. DE is applied to co-evolving the symbiotic population based on feedback information from the original population. Thus, with the evolution of the original population in DEHS, the symbiotic population is dynamically and self-adaptively adjusted, and real-time optimum control parameters are obtained. The proposed DEHS algorithm has been applied to various benchmark functions and two typical dynamic optimization problems. The experimental results show that the performance of the proposed algorithm is better than that of other HS variants. Satisfactory results are obtained in the application.
基金supported by the National Basic Research Program of China(Grant No.2013CB733303)National Natural Science Foundation of China(Grant Nos.41274010,41371335)supported by PA-SB ESA EO Project Campaign of"Development of methods for Forest Biophysical Parameters Inversion Using POLIn SAR Data"(Grant No.ID.14655)
文摘In this paper, we propose the novel method of complex least squares adjustment （CLSA） to invert vegetation height accurately using single-baseline polarimetric synthetic aperture radar interferometry （PollnSAR） data. CLSA basically estimates both volume-only coherence and ground phase directly without assuming that the ground-to-volume amplitude radio of a particular polarization channel （e.g., HV） is less than -10 dB, as in the three-stage method. In addition, CLSA can effectively limit errors in interferometric complex coherence, which may translate directly into erroneous ground-phase and volume-only coherence estimations. The proposed CLSA method is validated with BioSAR2008 P-band E-SAR and L-band SIR-C PollnSAR data. Its results are then compared with those of the traditional three-stage method and with external data. It implies that the CLSA method is much more robust than the three-stage method.
