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Hongwei Wang
Key Laboratory of Oasis Ecology, Ministry of Education, Xinjiang University, Urumqi 830046, China

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Journal article
Published: 02 July 2021 in Sustainability
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To explore the future development state of urban and rural settlements, we combined random forest algorithm (RFA) and cellular automata (CA) to simulate high precision in urban and rural settlements in Aksu city. The settlement distribution was predicted for the next 10 years, and suggestions for urban and rural settlements were proposed based on a “production–life–ecology” space. The results show the following: Transportation factors and administrative location have an important influence on the development of settlements, and infrastructure has a greater impact on the development of settlements. The overall accuracy of the 2019 settlement distribution obtained through the RFA–CA model simulation is 93.8%, with a G-mean coefficient of 0.815. The simulation accuracy is better and more suitable for the simulation and prediction of settlement expansion than the logistic-CA model. The forecasted settlement expansion in 2029 for Aksu city is 58.36 km2 of settlement expansion compared to the 2019 settlement distribution, with an overall growth trend for sparse north-south and dense central areas. This study analyzed the causes of settlement expansion in 19 regions of Aksu city, explored the main function of “production–life–ecology” space in different areas, and proposed layout optimizations from the perspective of production, life, and ecology. The results of this study can provide a reference for the spatial planning and rural revitalization strategy of Aksu city.

ACS Style

Jiayao Heng; Hongwei Wang; Ying Fan; Zhengwei Wang; Yibo Gao. Simulation and Optimization of Urban–Rural Settlement Development from the Perspective of Production–Life–Ecology Space: A Case Study for Aksu City. Sustainability 2021, 13, 7452 .

AMA Style

Jiayao Heng, Hongwei Wang, Ying Fan, Zhengwei Wang, Yibo Gao. Simulation and Optimization of Urban–Rural Settlement Development from the Perspective of Production–Life–Ecology Space: A Case Study for Aksu City. Sustainability. 2021; 13 (13):7452.

Chicago/Turabian Style

Jiayao Heng; Hongwei Wang; Ying Fan; Zhengwei Wang; Yibo Gao. 2021. "Simulation and Optimization of Urban–Rural Settlement Development from the Perspective of Production–Life–Ecology Space: A Case Study for Aksu City." Sustainability 13, no. 13: 7452.

Journal article
Published: 10 May 2021 in Sustainability
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Given the background of urbanization and rural revitalization in the new era, it is important to explore the synergy between regional macroeconomics and rural transformation, as a balanced and coordinated urban–rural relationship must be built to promote regional sustainable development and rural revitalization. This paper used the spatial econometric model to study the spatiotemporal synergy and interaction between Xinjiang’s county economy and rural transformation from 2007 to 2017. The conclusions were as follows. A clear spatial difference exists between the county economy and the rural transformation level, and regional bulk agricultural products lack competitiveness. The synergy between the county economy and rural transformation is weak, as the county economy is lagging while rural transformation progresses without collaboration, indicating different types of non-equivalence. The county economy has a stronger spatial dependence on rural transformation and insufficient spillover, a stagnating effect, mainly negative driving effects, and unstable interaction effects; while the unstable changes in rural transformation affect the county economy. The urbanization rate, urban wage level, rural employment structure, and planting area per capita were the main influencing factors. It is necessary to deepen rural transformation, consolidate and enhance its stability, cultivate regional growth poles, promote overall development, and promote regional coordination.

ACS Style

Bo Tan; Hongwei Wang; Chen Ma; Xiaoqin Wang; Jing Zhou. Spatial and Temporal Measurement of the Interaction between the County Economy and Rural Transformation in Xinjiang, China. Sustainability 2021, 13, 5318 .

AMA Style

Bo Tan, Hongwei Wang, Chen Ma, Xiaoqin Wang, Jing Zhou. Spatial and Temporal Measurement of the Interaction between the County Economy and Rural Transformation in Xinjiang, China. Sustainability. 2021; 13 (9):5318.

Chicago/Turabian Style

Bo Tan; Hongwei Wang; Chen Ma; Xiaoqin Wang; Jing Zhou. 2021. "Spatial and Temporal Measurement of the Interaction between the County Economy and Rural Transformation in Xinjiang, China." Sustainability 13, no. 9: 5318.

Journal article
Published: 09 May 2021 in Minerals
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The purpose of this study is to explore the degree and spatial distribution of dust heavy metal pollution in Tianshui City, the health risks, and the sources of heavy metals. The geoaccumulation index and health risk assessment are used to study pollution levels and human health risks, and Cu, Zn, and Pb pollution are found to be serious. The total exposure of children to dust and heavy metals is 8.329 × 10−3 mg·kg−1·d−1, which is 4.66 times that of adults. The effect of carcinogenic heavy metal exposure is more significant for adults than for children. The total non-carcinogenic risk quotient to children via multiple pathways is 2.1690, which is higher than that of adults. Children’s Pb non-carcinogenic risk quotient is 4.79 times that of adults, and children are more sensitive than adults to the health risks of Pb pollution. The GeoDetector and Unmix 6.0 models are used for source analysis, revealing that Zn, Pb, and As pollution originate primarily from urban transportation systems, V is sourced from soil-forming parent materials, and Mn, Ni, Cu, and Co arise from mixed sources. Therefore, the treatment of heavy metal pollution in cities needs to focus more on the urban transportation system.

ACS Style

Bo Tan; Hongwei Wang; Xinmin Wang; Chen Ma; Jing Zhou; Xinyan Dai. Health Risks and Source Analysis of Heavy Metal Pollution from Dust in Tianshui, China. Minerals 2021, 11, 502 .

AMA Style

Bo Tan, Hongwei Wang, Xinmin Wang, Chen Ma, Jing Zhou, Xinyan Dai. Health Risks and Source Analysis of Heavy Metal Pollution from Dust in Tianshui, China. Minerals. 2021; 11 (5):502.

Chicago/Turabian Style

Bo Tan; Hongwei Wang; Xinmin Wang; Chen Ma; Jing Zhou; Xinyan Dai. 2021. "Health Risks and Source Analysis of Heavy Metal Pollution from Dust in Tianshui, China." Minerals 11, no. 5: 502.

Journal article
Published: 05 May 2021 in International Journal of Environmental Research and Public Health
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Hand, foot, and mouth disease (HFMD) remains a serious health threat to young children. Urumqi is one of the most severely affected cities in northwestern China. This study aims to identify the spatiotemporal distribution characteristics of HFMD, and explore the relationships between driving factors and HFMD in Urumqi, Xinjiang. Methods: HFMD surveillance data from 2014 to 2018 were obtained from the China Center for Disease Control and Prevention. The center of gravity and geographical detector model were used to analyze the spatiotemporal distribution characteristics of HFMD and identify the association between these characteristics and socioeconomic and meteorological factors. Results: A total of 10,725 HFMD cases were reported in Urumqi during the study period. Spatially, the morbidity number of HFMD differed regionally and the density was higher in urban districts than in rural districts. Overall, the development of HFMD in Urumqi expanded toward the southeast. Temporally, we observed that the risk of HFMD peaked from June to July. Furthermore, socioeconomic and meteorological factors, including population density, road density, GDP, temperature and precipitation were significantly associated with the occurrence of HFMD. Conclusions: HFMD cases occurred in spatiotemporal clusters. Our findings showed strong associations between HFMD and socioeconomic and meteorological factors. We comprehensively considered the spatiotemporal distribution characteristics and influencing factors of HFMD, and proposed some intervention strategies that may assist in predicting the morbidity number of HFMD.

ACS Style

Yibo Gao; Hongwei Wang; Suyan Yi; Deping Wang; Chen Ma; Bo Tan; Yiming Wei. Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Their Influencing Factors in Urumqi, China. International Journal of Environmental Research and Public Health 2021, 18, 4919 .

AMA Style

Yibo Gao, Hongwei Wang, Suyan Yi, Deping Wang, Chen Ma, Bo Tan, Yiming Wei. Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Their Influencing Factors in Urumqi, China. International Journal of Environmental Research and Public Health. 2021; 18 (9):4919.

Chicago/Turabian Style

Yibo Gao; Hongwei Wang; Suyan Yi; Deping Wang; Chen Ma; Bo Tan; Yiming Wei. 2021. "Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Their Influencing Factors in Urumqi, China." International Journal of Environmental Research and Public Health 18, no. 9: 4919.

Journal article
Published: 17 February 2021 in International Journal of Environmental Research and Public Health
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Background: As the global climate changes, the number of cases of hand-foot-and-mouth disease (HFMD) is increasing year by year. This study comprehensively considers the association of time and space by analyzing the temporal and spatial distribution changes of HFMD in the Ili River Valley in terms of what climate factors could affect HFMD and in what way. Methods: HFMD cases were obtained from the National Public Health Science Data Center from 2013 to 2018. Monthly climate data, including average temperature (MAT), average relative humidity (MARH), average wind speed (MAWS), cumulative precipitation (MCP), and average air pressure (MAAP), were obtained from the National Meteorological Information Center. The temporal and spatial distribution characteristics of HFMD from 2013 to 2018 were obtained using kernel density estimation (KDE) and spatiotemporal scan statistics. A regression model of the incidence of HFMD and climate factors was established based on a geographically and temporally weighted regression (GTWR) model and a generalized additive model (GAM). Results: The KDE results show that the highest density was from north to south of the central region, gradually spreading to the whole region throughout the study period. Spatiotemporal cluster analysis revealed that clusters were distributed along the Ili and Gongnaisi river basins. The fitted curves of MAT and MARH were an inverted V-shape from February to August, and the fitted curves of MAAP and MAWS showed a U-shaped change and negative correlation from February to May. Among the individual climate factors, MCP coefficient values varied the most while MAWS values varied less from place to place. There was a partial similarity in the spatial distribution of coefficients for MARH and MAT, as evidenced by a significant degree of fit performance in the whole region. MCP showed a significant positive correlation in the range of 15–35 mm, and MAAP showed a positive correlation in the range of 925–945 hPa. HFMD incidence increased with MAT in the range of 15–23 °C, and the effective value of MAWS was in the range of 1.3–1.7 m/s, which was positively correlated with incidences of HFMD. Conclusions: HFMD incidence and climate factors were found to be spatiotemporally associated, and climate factors are mostly non-linearly associated with HFMD incidence.

ACS Style

Suyan Yi; Hongwei Wang; Shengtian Yang; Ling Xie; Yibo Gao; Chen Ma. Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Its Response to Climate Factors in the Ili River Valley Region of China. International Journal of Environmental Research and Public Health 2021, 18, 1954 .

AMA Style

Suyan Yi, Hongwei Wang, Shengtian Yang, Ling Xie, Yibo Gao, Chen Ma. Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Its Response to Climate Factors in the Ili River Valley Region of China. International Journal of Environmental Research and Public Health. 2021; 18 (4):1954.

Chicago/Turabian Style

Suyan Yi; Hongwei Wang; Shengtian Yang; Ling Xie; Yibo Gao; Chen Ma. 2021. "Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Its Response to Climate Factors in the Ili River Valley Region of China." International Journal of Environmental Research and Public Health 18, no. 4: 1954.

Journal article
Published: 24 March 2020 in Sensors
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Soil organic matter (SOM) is a crucial indicator for evaluating soil quality and an important component of soil carbon pools, which play a vital role in terrestrial ecosystems. Rapid, non-destructive and accurate monitoring of SOM content is of great significance for the environmental management and ecological restoration of mining areas. Visible-near-infrared (Vis-NIR) spectroscopy has proven its applicability in estimating SOM over the years. In this study, 168 soil samples were collected from the Zhundong coal field of Xinjiang Province, Northwest China. The SOM content (g kg−1) was determined by the potassium dichromate external heating method and the soil reflectance spectra were measured by the spectrometer. Two spectral feature extraction strategies, namely, principal component analysis (PCA) and the optimal band combination algorithm, were introduced to choose spectral variables. Linear models and random forests (RF) were used for predictive models. The coefficient of determination (R2), root mean square error (RMSE), and the ratio of the performance to the interquartile distance (RPIQ) were used to evaluate the predictive performance of the model. The results indicated that the variables (2DI and 3DI) derived from the optimal band combination algorithm outperformed the PCA variables (1DV) regardless of whether linear or RF models were used. An inherent gap exists between 2DI and 3DI, and the performance of 2DI is significantly poorer than that of 3DI. The accuracy of the prediction model increases with the increasing number of spectral variable dimensions (in the following order: 1DV < 2DI < 3DI). This study proves that the 3DI is the first choice for the optimal band combination algorithm to derive sensitive parameters related to SOM in the coal mining area. Furthermore, the optimal band combination algorithm can be applied to hyperspectral or multispectral images and to convert the spectral response into image pixels, which may be helpful for a soil property spatial distribution map.

ACS Style

Chuanmei Zhu; Zipeng Zhang; Hongwei Wang; Jingzhe Wang; Shengtian Yang. Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions. Sensors 2020, 20, 1795 .

AMA Style

Chuanmei Zhu, Zipeng Zhang, Hongwei Wang, Jingzhe Wang, Shengtian Yang. Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions. Sensors. 2020; 20 (6):1795.

Chicago/Turabian Style

Chuanmei Zhu; Zipeng Zhang; Hongwei Wang; Jingzhe Wang; Shengtian Yang. 2020. "Assessing Soil Organic Matter Content in a Coal Mining Area through Spectral Variables of Different Numbers of Dimensions." Sensors 20, no. 6: 1795.