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This study takes Changsha, an emerging mega-city in China, as a sample to analyze the influence of natural amenity (NA) on housing prices during different periods. We divided the NA into four categories according to their characteristics: Green Space (GS), Wetland Park (WP), XiangRiver Scenic Belt (XR), and green ratio within a community. The housing transaction data is used to calculate the accessibility of a settlement to nearest NA via the distance. The capitalization effect of NA is investigated through a geographic weighted regression (GWR), combined with the hedonic theory. Results show that ①the impact and scope of NA on housing prices gradually expanded during years. ②As the key nature landscape of Changsha, the impact coefficient of XR has risen from 2.34% in 2012 to 5.32% in 2020. WP has a remarkable increase for affecting housing prices, rising from 1.24 to 3.65%. Effect of GS keeps in line during years, at 2.34–3.72%. And green ratio’s impact increase from 3.61 to 4.55%. ③The higher capitalization effect of NA undergoes a spatial expansion from the central area to urban fringe over time, which also implies the capitalization of NA is becoming more pronounced. ④Residential communities impacted by NA have a propensity to separate over time. This study provides a different perspective in defining the importance of natural amenities in urban habitat of modern China.

Urban nature spaces are increasingly recognized as essential urban features providing crucial amenities to the residents’ health and well-being. While many studies have been conducted focusing on the influence of green spaces on house prices, very few have explored the impact of urban blue spaces. In this study, we analyzed the proximity effects of different types and sizes of urban blue spaces on property value in Changsha metropolis, China, and examined the spatial quantile effect across different housing prices. A two-stage instrumental method (2SLS) hedonic model was employed to evaluate the impact of different types of urban blue space: river (mainstream and tributary), wetland park, and lakes (large, medium, and small). Spatial quantile regression (SQR) was then used to measure the spatial effect of accessibility on various house price ranges. The 2SLS results show that, except for small-sized lakes, proximity to blue spaces significantly increases property value. Analysis of the SQR model reveals that proximity to major blue spaces increases the marginal willingness-to-pay among homebuyers of high-priced properties, while ordinary blue spaces are more attractive to buyers of low- and medium-priced houses. This may be broadly related to the level of education, utility, and sensitivity to ecosystem services across income groups. Based on these findings, we recommend that urban planners adopt different strategies to promote space utilization efficiency. This is one of the few studies that analyze the capitalization of blue space accessibility in house prices across different quantiles. By categorizing blue spaces and employing the SQR model, this study found the effect of blue spaces on housing prices to be heterogeneous, providing new perspectives to the existing literature.

In developing countries, urban agglomerations have become one of the most important carriers of urbanization. In China, one of the largest national urban agglomerations is the UAMRYR (urban agglomeration in the middle reaches of the Yangtze River), which has the fastest urban development in Central China and is home to critical ecological spaces. On this basis, this study analyzed the urban expansion and loss of ecological lands in UAMRYR by establishing a spatial database, grid system, rose maps, and scenario simulation. The highlights of results are as follows: the urban expansion of UAMRYR includes four stages of development: steady growth, accelerated development, peak, and deceleration. Polarized development has occurred in the region, with the Wuhan, Changsha-Zhuzhou-Xiangtan, and Nanchang metropolitan areas having high levels of urban expansion while the other cities have varying levels of urban growth. The loss of ecological land was found to have a highly similar curve and spatial distribution with the urban growth. In terms of ecological land types, the loss of agricultural land accounted for more than half of ecological lands lost overall. Losses in forests, grasslands, wetlands, and water areas varied for different areas, depending on particular conditions and specific environmental characteristics of the city. The three metropolitan areas experienced the highest increases in urban built-up areas; they also had the highest loss of ecological land, which can have critical consequences given their proximity to the Yangtze River, Poyang Lake, Dongting Lake, and other important environmental sensitive areas. The simulation results show that the UAMRYR is projected to maintain a rapid expansion rate from 2020 to 2030. If the urban expansion, particularly in the metropolitan areas, is not managed well and controlled, serious ecological damage could be inflicted on the Yangtze River Basin.

The minimum Steiner tree (MST) problem is a nonlinear programming hard (NP-hard) problem in the Euclidean plane, polynomial time algorithm is absent for solving MST for a group of arbitrary terminal points, and the most difficult thing is how to determine the position and number of Steiner points. A new method is proposed by using an immune algorithm to solve MST problem in this paper. According to the breadth — first traversal sequence of minimum spanning tree and Melzak method, the terminal points can be divided into different convex hull sets, and the full Steiner tree can be structured from the convex hull. A non-full Steiner tree can be decomposed into some full Steiner trees which terminal point appears in full Steiner tree, it is the most critical issue. We put Steiner points as a vaccine, the vaccine tries inoculation corresponding to the location of the minimum spanning tree, after several iterations, the final optimal Steiner tree is the MST. We choose the path of three cases to verify the effectiveness of the proposed algorithm, the results showed that it can reduce by 21.16%, 19.68% and 18.78% respectively. And we used the visual experimental instrument to verify the results of immune algorithm, the ratio of the length obtained by the immune algorithm and the visualization experiment is 99.95%, it is very close and the performance of algorithm is remarkable and outstanding effectively.

In this paper, we design and implemente an embedded system of video capture and transmission, which is applied in remote monitoring for wheelchair-bed robots. In the system, on the basis of the embeded linux and S3C2410AL microprocessor, an embedded App Web 3.0 server is transplanted and a programme of viedo capture is designed by Video4Linux2. In order to get better compression of video data, it is optimized for the block-matching motion estimation algorithm in MPEG-4. By which, we eventually realize the video transmission through the internet with JRTPLIB.