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With the increasing population and continuation of climate change, an adequate food supply is vital to economic development and social stability. Winter crops are important crop types in China. Changes in winter crops planting areas not only have a direct impact on China’s production and economy, but also potentially affects China’s food security. Therefore, it is necessary to obtain information on the planting of winter crops. In this study, we use the time series data of individual pixels, calculate the temporal statistics of spectral bands and the vegetation indices of optical data based on the phenological characteristics of specific vegetation or crops and record them in the time series data, and apply decision trees and rule-based algorithms to generate annual maps of winter crops. First, we constructed a dataset combining all the available images from Landsat 7/8 and Sentinel-2A/B. Second, we generated an annual map of land cover types to obtain the cropland mask in 2019. Third, we generated a time series of a single cropland pixel, and calculated the phenological indicators for classification by extracting the differences in phenological characteristics of different crops: these phenological indicators include SOS (start of season), SDP (start date of peak), EOS (end of season), GUS (green-up speed) and GSL (growing-season length). Finally, we identified winter crops in 2019 based on their phenological characteristics. The main advantages of the phenology-based algorithm proposed in this study include: (1) Combining multiple sensor data to construct a high spatiotemporal resolution image collection. (2) By analyzing the whole growth season of winter crops, the planting area of winter crops can be extracted more accurately, and (3) the phenological indicators of different periods are extracted, which is conducive to monitoring winter crop planting information and seasonal dynamics. The results show that the algorithm constructed in this study can accurately extract the planting area of winter crops, with user, producer, overall accuracies and Kappa coefficients of 96.61%, 94.13%, 94.56% and 0.89, respectively, indicating that the phenology-based algorithm is reliable for large area crop classification. This research will provide a point of reference for crop area extraction and monitoring.
Li Pan; Haoming Xia; Xiaoyang Zhao; Yan Guo; Yaochen Qin. Mapping Winter Crops Using a Phenology Algorithm, Time-Series Sentinel-2 and Landsat-7/8 Images, and Google Earth Engine. Remote Sensing 2021, 13, 2510 .
AMA StyleLi Pan, Haoming Xia, Xiaoyang Zhao, Yan Guo, Yaochen Qin. Mapping Winter Crops Using a Phenology Algorithm, Time-Series Sentinel-2 and Landsat-7/8 Images, and Google Earth Engine. Remote Sensing. 2021; 13 (13):2510.
Chicago/Turabian StyleLi Pan; Haoming Xia; Xiaoyang Zhao; Yan Guo; Yaochen Qin. 2021. "Mapping Winter Crops Using a Phenology Algorithm, Time-Series Sentinel-2 and Landsat-7/8 Images, and Google Earth Engine." Remote Sensing 13, no. 13: 2510.
As the land use issue, caused by urban shrinkage in China, is becoming more and more prominent, research on urban shrinkage and expansion has become particularly challenging and urgent. Based on the points of interest (POI) data, this paper redefines the scope, quantity, and area of natural cities by using threshold methods, which accurately identify the shrinkage and expansion of cities in the Yellow River affected area using night light data in 2013 and 2018. The results show that: (1) there are 3130 natural cities (48118.75 km2) in the Yellow River affected area, including 604 shrinking cities (8407.50 km2) and 2165 expanding cities (32972.75 km2). (2) The spatial distributions of shrinking and expanding cities are quite different. The shrinking cities are mainly located in the upper Yellow River affected area, except for the administrative cities of Lanzhou and Yinchuan; the expanding cities are mainly distributed in the middle and lower Yellow River affected area, and the administrative cities of Lanzhou and Yinchuan. (3) Shrinking and expanding cities are typically smaller cities. The research results provide a quick data supported approach for regional urban planning and land use management, for when regional and central governments formulate the outlines of urban development monitoring and regional planning.
Wenhui Niu; Haoming Xia; Ruimeng Wang; Li Pan; Qingmin Meng; Yaochen Qin; Rumeng Li; Xiaoyang Zhao; Xiqing Bian; Wei Zhao. Research on Large-Scale Urban Shrinkage and Expansion in the Yellow River Affected Area Using Night Light Data. ISPRS International Journal of Geo-Information 2020, 10, 5 .
AMA StyleWenhui Niu, Haoming Xia, Ruimeng Wang, Li Pan, Qingmin Meng, Yaochen Qin, Rumeng Li, Xiaoyang Zhao, Xiqing Bian, Wei Zhao. Research on Large-Scale Urban Shrinkage and Expansion in the Yellow River Affected Area Using Night Light Data. ISPRS International Journal of Geo-Information. 2020; 10 (1):5.
Chicago/Turabian StyleWenhui Niu; Haoming Xia; Ruimeng Wang; Li Pan; Qingmin Meng; Yaochen Qin; Rumeng Li; Xiaoyang Zhao; Xiqing Bian; Wei Zhao. 2020. "Research on Large-Scale Urban Shrinkage and Expansion in the Yellow River Affected Area Using Night Light Data." ISPRS International Journal of Geo-Information 10, no. 1: 5.
With the rapid economic development and continuous growth of population in rapid urbanized area, the health status of urban ecosystem is undergoing profound changes, which will have a negative impact on the sustainable development. In order to systematically evaluate the health status of urban ecosystem in rapid urbanized area of central China, this paper puts forward a new assessment framework of structure-function-process-human health-development based on a deep understanding of the concept and general characteristics of urban ecosystem health, and establishes an expanded evaluation index system according to this evaluation framework. Then, on the basis of determining the index classification criteria in detail, the improved SI-MI model was used to evaluate the health status of urban ecosystem. As a case study, the framework and method were applied to the urban agglomeration in the middle reaches of the Yangtze river, a region of the rapid urbanized in China. The results showed that, the health level of most cities in the study area has been improved from 2005 to 2015. From the perspective of spatial pattern, the health level of the study area shows obvious spatial heterogeneity, and provincial capital cities and some eco-cities have better health status. It is worth noting that the function and development layer are the key parts that restrict the overall health level of urban ecosystem in the urban agglomeration in the middle reaches of the Yangtze River. After classifying all cities, we found the factors influencing the health level of different types of cities, and proposed the management suggestions for different types of cities.
Wei Shen; Zhicheng Zheng; Li Pan; Yaochen Qin; Yang Li. A integrated method for assessing the urban ecosystem health of rapid urbanized area in China based on SFPHD framework. Ecological Indicators 2020, 121, 107071 .
AMA StyleWei Shen, Zhicheng Zheng, Li Pan, Yaochen Qin, Yang Li. A integrated method for assessing the urban ecosystem health of rapid urbanized area in China based on SFPHD framework. Ecological Indicators. 2020; 121 ():107071.
Chicago/Turabian StyleWei Shen; Zhicheng Zheng; Li Pan; Yaochen Qin; Yang Li. 2020. "A integrated method for assessing the urban ecosystem health of rapid urbanized area in China based on SFPHD framework." Ecological Indicators 121, no. : 107071.
Quantifying the greenhouse gas (GHG) storage in forest ecosystems can support global change directly, from a biogeochemical perspective. However, accurately assessing the amount of GHG storage in forest ecosystems still faces challenges in China because of their wide distribution, varying types, and the changing definitions and areas of forests. We used land-use data with 5-year intervals during 1990–2015 to investigate the spatiotemporal variations of forest ecosystems in China. As three major greenhouse gases in forest ecosystems, the potential storage of carbon dioxide, methane, and nitrous oxide can be calculated by a greenhouse gas value (GHGV) model. The results showed that the total area of forest ecosystems decreased by 15 × 105 ha during the study period. The area of forest ecosystems reached its highest level in 1995 and then declined. For various forest ecosystem types, shrubbery (Sh) increased by 0.82% but the broad-leaved forest, evergreen coniferous forest (ECF), and mixed forest (MF) all showed a downward trend. Correspondingly, the potential GHG storage of forest ecosystems declined from 156.97 Pg CO2-equivalent (CO2-eq) to 155.56 Pg CO2-eq, a decrease of 1.41 Pg CO2-eq. Compared with previous research results, the GHGV model proved to be an important supplementary method for estimating the potential storage of GHGs in forest ecosystems, especially in highly fragmented landscapes at a large scale. Our study indicated that the impact of forest ecosystems changes on potential GHG storage was serious during the study period. Our findings highlight that the GHGV model can be an effective and low-cost strategy to simulate the forest change and corresponding GHG storage. And considering the efficiency of the model and the historical analysis results of many periods, some of the results can also be used to inform the future afforestation programs and assess the expected GHG storage in China.
Mengdi Li; Yaoping Cui; Yaochen Qin; Oliva Gabriel Chubwa; Yiming Fu; Nan Li; Xiaoyan Liu; Yadi Run. Parameter Localization of Greenhouse Gas Value Model and Greenhouse Gas Storage Simulation for Forest Ecosystems in China. Forests 2020, 11, 1150 .
AMA StyleMengdi Li, Yaoping Cui, Yaochen Qin, Oliva Gabriel Chubwa, Yiming Fu, Nan Li, Xiaoyan Liu, Yadi Run. Parameter Localization of Greenhouse Gas Value Model and Greenhouse Gas Storage Simulation for Forest Ecosystems in China. Forests. 2020; 11 (11):1150.
Chicago/Turabian StyleMengdi Li; Yaoping Cui; Yaochen Qin; Oliva Gabriel Chubwa; Yiming Fu; Nan Li; Xiaoyan Liu; Yadi Run. 2020. "Parameter Localization of Greenhouse Gas Value Model and Greenhouse Gas Storage Simulation for Forest Ecosystems in China." Forests 11, no. 11: 1150.
Garlic and winter wheat are major economic and grain crops in China, and their boundaries have increased substantially in recent decades. Updated and accurate garlic and winter wheat maps are critical for assessing their impacts on society and the environment. Remote sensing imagery can be used to monitor spatial and temporal changes in croplands such as winter wheat and maize. However, to our knowledge, few studies are focusing on garlic area mapping. Here, we proposed a method for coupling active and passive satellite imagery for the identification of both garlic and winter wheat in Northern China. First, we used passive satellite imagery (Sentinel-2 and Landsat-8 images) to extract winter crops (garlic and winter wheat) with high accuracy. Second, we applied active satellite imagery (Sentinel-1 images) to distinguish garlic from winter wheat. Third, we generated a map of the garlic and winter wheat by coupling the above two classification results. For the evaluation of classification, the overall accuracy was 95.97%, with a kappa coefficient of 0.94 by eighteen validation quadrats (3 km by 3 km). The user’s and producer’s accuracies of garlic are 95.83% and 95.85%, respectively; and for the winter wheat, these two accuracies are 97.20% and 97.45%, respectively. This study provides a practical exploration of targeted crop identification in mixed planting areas using multisource remote sensing data.
Haifeng Tian; Jie Pei; Jianxi Huang; Xuecao Li; Jian Wang; Boyan Zhou; Yaochen Qin; Li Wang. Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China. Remote Sensing 2020, 12, 3539 .
AMA StyleHaifeng Tian, Jie Pei, Jianxi Huang, Xuecao Li, Jian Wang, Boyan Zhou, Yaochen Qin, Li Wang. Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China. Remote Sensing. 2020; 12 (21):3539.
Chicago/Turabian StyleHaifeng Tian; Jie Pei; Jianxi Huang; Xuecao Li; Jian Wang; Boyan Zhou; Yaochen Qin; Li Wang. 2020. "Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China." Remote Sensing 12, no. 21: 3539.
The spatio-temporal change of the surface water is very important to agricultural, economic, and social development in the Hetao Plain, as well as the structure and function of the ecosystem. To understand the long-term changes of the surface water area in the Hetao Plain, we used all available Landsat images (7534 scenes) and adopted the modified Normalized Difference Water Index (mNDWI), Enhanced Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) to map the open-surface water from 1989 to 2019 in the Google Earth Engine (GEE) cloud platform. We further analyzed precipitation, temperature, and irrigated area, revealing the impact of climate change and human activities on long-term surface water changes. The results show the following. (1) In the last 31 years, the maximum, seasonal, and annual average water body area values in the Hetao Plain have exhibited a downward trend. Meanwhile, the number of maximum, seasonal, and permanent water bodies displayed a significant upward trend. (2) The variation of the surface water area in the Hetao Plain is mainly affected by the maximum water body area, while the variation of the water body number is mainly affected by the number of minimum water bodies. (3) Precipitation has statistically significant positive effects on the water body area and water body number, which has statistically significant negative effects with temperature and irrigation. The findings of this study can be used to help the policy-makers and farmers understand changing water resources and its driving mechanism and provide a reference for water resources management, agricultural irrigation, and ecological protection.
Ruimeng Wang; Haoming Xia; Yaochen Qin; Wenhui Niu; Li Pan; Rumeng Li; Xiaoyang Zhao; Xiqing Bian; Pinde Fu. Dynamic Monitoring of Surface Water Area during 1989–2019 in the Hetao Plain Using Landsat Data in Google Earth Engine. Water 2020, 12, 3010 .
AMA StyleRuimeng Wang, Haoming Xia, Yaochen Qin, Wenhui Niu, Li Pan, Rumeng Li, Xiaoyang Zhao, Xiqing Bian, Pinde Fu. Dynamic Monitoring of Surface Water Area during 1989–2019 in the Hetao Plain Using Landsat Data in Google Earth Engine. Water. 2020; 12 (11):3010.
Chicago/Turabian StyleRuimeng Wang; Haoming Xia; Yaochen Qin; Wenhui Niu; Li Pan; Rumeng Li; Xiaoyang Zhao; Xiqing Bian; Pinde Fu. 2020. "Dynamic Monitoring of Surface Water Area during 1989–2019 in the Hetao Plain Using Landsat Data in Google Earth Engine." Water 12, no. 11: 3010.
The global pandemic of COVID-19 has made it the focus of current attention. At present, the law of COVID-19 spread in cities is not clear. Cities have long been difficult areas for epidemic prevention and control because of the high population density, high mobility of people, and high frequency of contacts. This paper analyzed case information for 417 patients with COVID-19 in Shenzhen, China. The nearest neighbor index method, kernel density method, and the standard deviation ellipse method were used to analyze the spatio-temporal characteristics of the COVID-19 spread in Shenzhen. The factors influencing that spread were then explored using the multiple linear regression method. The results show that: (1) The development of COVID-19 epidemic situation in Shenzhen occurred in three stages. The patients showed significant hysteresis from the onset of symptoms to hospitalization and then to diagnosis. Prior to 27 January, there was a relatively long time interval between the onset of symptoms and hospitalization for COVID-19; the interval decreased thereafter. (2) The epidemic site (the place where the patient stays during the onset of the disease) showed an agglomeration in space. The degree of agglomeration constantly increased across the three time nodes of 31 January, 14 February, and 22 February. The epidemic sites formed a “core area” in terms of spatial distribution and spread along the “northwest–southeast” direction of the city. (3) Economic and social factors significantly impacted the spread of COVID-19, while environmental factors have not played a significant role.
Shirui Liu; Yaochen Qin; Zhixiang Xie; Jingfei Zhang. The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases. International Journal of Environmental Research and Public Health 2020, 17, 7450 .
AMA StyleShirui Liu, Yaochen Qin, Zhixiang Xie, Jingfei Zhang. The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases. International Journal of Environmental Research and Public Health. 2020; 17 (20):7450.
Chicago/Turabian StyleShirui Liu; Yaochen Qin; Zhixiang Xie; Jingfei Zhang. 2020. "The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases." International Journal of Environmental Research and Public Health 17, no. 20: 7450.
In our review of the research on PGS (park green space) spatial equity, little consideration has been given to the impacts of small spatial scales and measurement accuracy on spatial equity assessments. Based on the web map API open data platform (including location and navigation data, etc.), this study established a fine-scaled evaluation framework of spatial equity from the aspects of sensitivity to measurement and the urban micro-perspective. The framework was integrated within the KD2SFCA (kernel density two-step floating catchment area) method, which planners use to accurately locate areas of under or over supply of urban public facilities. Taking Zhengzhou as a case study, we identified 2494 residential areas and 106 PGSs to describe the spatial equity of residents accessing different PGS levels by four travel modes. The results showed that there were significant differences in spatial equity between different PGS levels. Of the three PGS levels, the overall spatial equity for district PGS was the highest, community PGS was second, and municipal PGS was the lowest. We also found that different travel modes had important impacts on PGS spatial equity. One interesting phenomenon was that when residents chose to walk to a higher level PGS, the percentages of the population with “no supply” increased; when residents chose bicycle and private car modes to reach higher level PGS, the percentages of the population with “weak supply” and “over supply” increased. In addition, it is worth noting that community PGS was originally established to meet the needs of residents for short-distance entertainment. However, we found that almost all residents in the study area were in the extreme states of “no supply” or “over supply” when they reached community PGS by walking. These results provide a scientific basis for more reasonable and equitable allocation of urban PGS and the optimization of transportation facilities. This work can also provide a more fine-scaled research perspective and improve the scientific evaluation system for studying urban infrastructure spatial equity.
Zhicheng Zheng; Wei Shen; Yang Li; Yaochen Qin; Lu Wang. Spatial equity of park green space using KD2SFCA and web map API: A case study of zhengzhou, China. Applied Geography 2020, 123, 102310 .
AMA StyleZhicheng Zheng, Wei Shen, Yang Li, Yaochen Qin, Lu Wang. Spatial equity of park green space using KD2SFCA and web map API: A case study of zhengzhou, China. Applied Geography. 2020; 123 ():102310.
Chicago/Turabian StyleZhicheng Zheng; Wei Shen; Yang Li; Yaochen Qin; Lu Wang. 2020. "Spatial equity of park green space using KD2SFCA and web map API: A case study of zhengzhou, China." Applied Geography 123, no. : 102310.
Accurately quantifying spatiotemporal changes in surface water is essential for water resources management, nevertheless, the dynamics of Poyang Lake surface water areas with high spatiotemporal resolution, as well as its responses to climate change, still face considerable uncertainties. Using the time series of Sentinel-1 images with 6- or 12-day intervals, the Sentinel-1 water index (SWI), and SWI-based water extraction model (SWIM) from 2015 to 2020 were used to document and study the short-term characteristics of southwest Poyang Lake surface water. The results showed that the overall accuracy of surface water area was satisfactory with an average of 91.92%, and the surface water area ranged from 129.06 km2 on 2 March 2017 to 1042.57 km2 on 17 July 2016, with significant intra- and inter-month variability. Within the 6-day interval, the maximum change of lake area was 233.42 km2 (i.e., increasing from 474.70 km2 up to 708.12 km2). We found that the correlation coefficient between the water area and the 45-day accumulated precipitation reached to 0.75 (p < 0.001). Moreover, a prediction model was built to predict the water area based on climate records. These results highlight the significance of high spatiotemporal resolution mapping for surface water in the erratic southwest Poyang Lake under a changing climate. The automated water extraction algorithm proposed in this study has potential applications in delineating surface water dynamics at broad geographic scales.
Haifeng Tian; Jian Wang; Jie Pei; Yaochen Qin; Lijun Zhang; Yongjiu Wang. High Spatiotemporal Resolution Mapping of Surface Water in the Southwest Poyang Lake and Its Responses to Climate Oscillations. Sensors 2020, 20, 4872 .
AMA StyleHaifeng Tian, Jian Wang, Jie Pei, Yaochen Qin, Lijun Zhang, Yongjiu Wang. High Spatiotemporal Resolution Mapping of Surface Water in the Southwest Poyang Lake and Its Responses to Climate Oscillations. Sensors. 2020; 20 (17):4872.
Chicago/Turabian StyleHaifeng Tian; Jian Wang; Jie Pei; Yaochen Qin; Lijun Zhang; Yongjiu Wang. 2020. "High Spatiotemporal Resolution Mapping of Surface Water in the Southwest Poyang Lake and Its Responses to Climate Oscillations." Sensors 20, no. 17: 4872.
This paper uses the exploratory spatial data analysis and the geodetector method to analyze the spatial and temporal differentiation characteristics and the influencing factors of the COVID-19 (corona virus disease 2019) epidemic spread in mainland China based on the cumulative confirmed cases, average temperature, and socio-economic data. The results show that: (1) the epidemic spread rapidly from January 24 to February 20, 2020, and the distribution of the epidemic areas tended to be stable over time. The epidemic spread rate in Hubei province, in its surrounding, and in some economically developed cities was higher, while that in western part of China and in remote areas of central and eastern China was lower. (2) The global and local spatial correlation characteristics of the epidemic distribution present a positive correlation. Specifically, the global spatial correlation characteristics experienced a change process from agglomeration to decentralization. The local spatial correlation characteristics were mainly composed of the‘high-high’ and ‘low-low’ clustering types, and the situation of the contiguous layout was very significant. (3) The population inflow from Wuhan and the strength of economic connection were the main factors affecting the epidemic spread, together with the population distribution, transport accessibility, average temperature, and medical facilities, which affected the epidemic spread to varying degrees. (4) The detection factors interacted mainly through the mutual enhancement and nonlinear enhancement, and their influence on the epidemic spread rate exceeded that of single factors. Besides, each detection factor has an interval range that is conducive to the epidemic spread.
Zhixiang Xie; Yaochen Qin; Yang Li; Wei Shen; Zhicheng Zheng; Shirui Liu. Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors. Science of The Total Environment 2020, 744, 140929 -140929.
AMA StyleZhixiang Xie, Yaochen Qin, Yang Li, Wei Shen, Zhicheng Zheng, Shirui Liu. Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors. Science of The Total Environment. 2020; 744 ():140929-140929.
Chicago/Turabian StyleZhixiang Xie; Yaochen Qin; Yang Li; Wei Shen; Zhicheng Zheng; Shirui Liu. 2020. "Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors." Science of The Total Environment 744, no. : 140929-140929.
Quantitative assessment can scientifically determine the health status of a regional ecosystem, identify regional eco-environmental problems, and assist in promoting regional sustainable development and environmental management. Taking China’s important ecological function region, the Yellow River affected area as an example, this study constructed an extended evaluation index system based on the pressure-state-response framework, and remote sensing and GIS techniques were used to dynamically evaluate the spatial and temporal characteristics of ecosystem health in the study area. Furthermore, influencing factors on ecosystem health in the study area were extensively analyzed using the GeoDetector model. The results show that the ecosystem health level in the study area shows significant spatial heterogeneity from 1995–2015, and showed a fluctuating change process. Areas with large fluctuations in health level were mainly distributed in extreme climate areas, ecologically fragile areas, on plains and in hilly areas. Spatial differences of ecosystem health were well explained by using the biological abundance index, relief degree of land surface, soil type, annual average precipitation, elevation, annual average temperature, and population density. Influencing factors have significant interactive effects on ecosystem health.
Wei Shen; Zhicheng Zheng; Yaochen Qin; Yang Li. Spatiotemporal Characteristics and Driving Force of Ecosystem Health in an Important Ecological Function Region in China. International Journal of Environmental Research and Public Health 2020, 17, 5075 .
AMA StyleWei Shen, Zhicheng Zheng, Yaochen Qin, Yang Li. Spatiotemporal Characteristics and Driving Force of Ecosystem Health in an Important Ecological Function Region in China. International Journal of Environmental Research and Public Health. 2020; 17 (14):5075.
Chicago/Turabian StyleWei Shen; Zhicheng Zheng; Yaochen Qin; Yang Li. 2020. "Spatiotemporal Characteristics and Driving Force of Ecosystem Health in an Important Ecological Function Region in China." International Journal of Environmental Research and Public Health 17, no. 14: 5075.
Low-carbon cognition can potentially impact low-carbon behavior, playing an important role in sustainable urban development. Traditional low-carbon cognition research has paid little attention to the built environment, causing an underestimation of the influence of urban spatial planning and regulation. Therefore, we constructed an analytical framework of low-carbon cognition and integrated the built environment 5D variables with local forces to investigate the cultural, local, and personal impact of low-carbon cognition. Low-carbon cognition in terms of energy use, daily travel, and consumption for 1485 households in Zhengzhou City was empirically studied. The results show that residents’ low-carbon cognition is hierarchical. Low-carbon travel cognition is highly susceptible to the external environment, while low-carbon energy use cognition is susceptible to cultural factors. There are differences in the effects of the three forces on residents’ low-carbon cognition. The personal and cultural forces have a greater impact on residents’ low-carbon energy use and consumption cognition, while the local force affects various low-carbon cognition of residents. The heterogeneity of the built environmental impact should be focused on. The “5D” built environment (Density, Diversity, Design, Distance to transit, and Destination accessibility) positively affects the level of low-carbon travel cognitive, but negatively affects the level of low-carbon consumption cognitive. This study comprehensively analyzes the low-carbon cognition of energy use, daily travel, and consumption, objectively measures the impact of “Regional force” on low-carbon cognition, and determines the heterogeneous effect of the external built environment on low-carbon cognition. We provide detailed policy recommendations for the construction of low-carbon cities and transformation of residents’ living behaviors.
Jingfei Zhang; Lijun Zhang; Yaochen Qin; Xia Wang; Zhicheng Zheng. Influence of the built environment on urban residential low-carbon cognition in zhengzhou, China. Journal of Cleaner Production 2020, 271, 122429 .
AMA StyleJingfei Zhang, Lijun Zhang, Yaochen Qin, Xia Wang, Zhicheng Zheng. Influence of the built environment on urban residential low-carbon cognition in zhengzhou, China. Journal of Cleaner Production. 2020; 271 ():122429.
Chicago/Turabian StyleJingfei Zhang; Lijun Zhang; Yaochen Qin; Xia Wang; Zhicheng Zheng. 2020. "Influence of the built environment on urban residential low-carbon cognition in zhengzhou, China." Journal of Cleaner Production 271, no. : 122429.
Air pollution in the form of PM2.5 can destroy the residents’ health and cause heavy economic losses. How to determine the control target of PM2.5 concentration for each city according to their local conditions becomes the key to prevent and control PM2.5 pollution. Based on a series of index data selected from the aspect of land, industry, energy, population, technology and economic factors in 2016, this study determines allocation schemes of control targets for PM2.5 concentration in 28 cities of atmospheric pollution transmission channel in the Beijing-Tianjin-Hebei district under the IT-1 (35 μg/m³), IT-2 (25 μg/m³), IT-3 (15 μg/m³) and AQG (10 μg/m³) scenarios using various methods. The results show that: (1) The combination of the Super-slacks based measure (Super-SBM) model with undesirable outputs, Gini coefficient method, contribution coefficient method and Gini coefficient minimization model can inified evaluation indexes and increase the ability to systematize and compare the allocation schemes formulated based on different regulation principles. (2) The economic development performance level under the constraint condition of PM2.5 pollution and the fairness of PM2.5 emissions corresponding to different factors exhibit significant differences among all the cities. Although the allocation scheme determined based on the equity principle can improve the fairness of PM2.5 emissions compared with the base year, the unfairness characteristic of PM2.5 emissions do not fundamentally change. (3) Regional allocation schemes of control target for PM2.5 concentration under the IT-1 scenario based on the efficiency principle or equity principle are feasible while the scheme determined based on the principle of efficiency and equity is not. The allocation schemes determined under the IT-2, IT-3 and AQG scenarios based on the equity principle are feasible while the schemes determined based on other principles are not. More attention should be paid at allocating the control target of PM2.5 concentration based on the equity principle, rather than fousing other principles in the future.
Zhixiang Xie; Yang Li; Yaochen Qin. Allocation of control targets for PM2.5 concentration: An empirical study from cities of atmospheric pollution transmission channel in the Beijing-Tianjin-Hebei district. Journal of Cleaner Production 2020, 270, 122545 .
AMA StyleZhixiang Xie, Yang Li, Yaochen Qin. Allocation of control targets for PM2.5 concentration: An empirical study from cities of atmospheric pollution transmission channel in the Beijing-Tianjin-Hebei district. Journal of Cleaner Production. 2020; 270 ():122545.
Chicago/Turabian StyleZhixiang Xie; Yang Li; Yaochen Qin. 2020. "Allocation of control targets for PM2.5 concentration: An empirical study from cities of atmospheric pollution transmission channel in the Beijing-Tianjin-Hebei district." Journal of Cleaner Production 270, no. : 122545.
By introducing an improved potential model and using the Internet map navigation service and GIS spatial analysis technology platform, this paper studies the spatial accessibility and equity of the medical treatment of residential buildings in the main urban area of Zhengzhou. The findings show that, overall, the spatial accessibility of medical treatment in the study area extends in the northeast and southwest directions, and presents a zonal spreading trend. There exist certain differences and imbalances in the medical facilities and services in each ring, reflect in a gradual deterioration from the first ring to the third ring. According to residents' demand for medical treatment and the distribution of medical resources, the medical spaces themselves can be roughly divided into three regions: “high enjoyment type” (ample resources and sparse population), “general type” (average amount of resources and concentrated population), and “lagging type” (few resources and sparse population). With regard to equity, and based on the Gini coefficient and Lorenz curve, the number of beds in medical facilities was found to be positively correlated with the population, and the total supply of resources to be balanced with population demand, whereas medical resources were seen to be scarce in the outskirts of Zhengzhou and far from the central area. The location entropy index suggests that accessibility to medical facilities in most residential areas is below the average level. While the total amount of hospital resources across the population was found to be relatively equitable, much room for improvement can be said to remain in terms of residents' accessibility when they arrive at hospitals for medical treatment. These research results provide new insights into equity evaluations of urban resource accessibility, as well as a scientific basis for the Chinese government to plan the distribution of medical resources.
Peijun Rong; Zhicheng Zheng; Mei-Po Kwan; Yaochen Qin. Evaluation of the spatial equity of medical facilities based on improved potential model and map service API: A case study in Zhengzhou, China. Applied Geography 2020, 119, 102192 .
AMA StylePeijun Rong, Zhicheng Zheng, Mei-Po Kwan, Yaochen Qin. Evaluation of the spatial equity of medical facilities based on improved potential model and map service API: A case study in Zhengzhou, China. Applied Geography. 2020; 119 ():102192.
Chicago/Turabian StylePeijun Rong; Zhicheng Zheng; Mei-Po Kwan; Yaochen Qin. 2020. "Evaluation of the spatial equity of medical facilities based on improved potential model and map service API: A case study in Zhengzhou, China." Applied Geography 119, no. : 102192.
There are industry lock-in and regional lock-in phenomena in China’s manufacturing industry carbon emissions. However, the existing researches often focus on global carbon emissions, which is not adverse to finding the main problems of manufacturing industry carbon emissions. The biggest contributions of this study are the identification of the industry lock-in and regional lock-in of China’s manufacturing industry and the finding of the regional factors that affect the carbon lock-in of the manufacturing industry, which points out the direction for the low-carbon transformation of the local manufacturing industry. This paper is based on the IPCC (Intergovernmental Panel on Climate Change) carbon emissions coefficient method and energy consumption data from 2000 to 2016 to count the manufacturing industry carbon emissions of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). On this basis, the paper uses a spatial–temporal geographical weighted regression (GTWR) model to analysis the regional influencing factors of the high-carbon manufacturing industry. Results demonstrate that China’s high-carbon manufacturing industry mainly concentrates on the ferrous metal processing industry, non-metallic mineral manufacturing industry and other sectors. In addition, the carbon emissions of high-carbon manufacturing industries are mainly concentrated in Bohai Bay and the North China Plain. The industrial structure and economic scale are the main reasons for the regional carbon lock-in of the high-carbon manufacturing industry, and the strength of the lock-in has continued to increase. Resource endowment is a stable factor of carbon lock-in in high-carbon regions. Technological progress helps to unlock carbon, while foreign direct investment results in the enhancement of carbon regional lock-in. This study focuses on the regional factors of carbon lock-in in the manufacturing industry, hoping to provide decision support for the green development of China’s manufacturing industry.
Xia Wang; Lijun Zhang; Yaochen Qin; Jingfei Zhang. Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors. Sustainability 2020, 12, 1502 .
AMA StyleXia Wang, Lijun Zhang, Yaochen Qin, Jingfei Zhang. Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors. Sustainability. 2020; 12 (4):1502.
Chicago/Turabian StyleXia Wang; Lijun Zhang; Yaochen Qin; Jingfei Zhang. 2020. "Analysis of China’s Manufacturing Industry Carbon Lock-In and Its Influencing Factors." Sustainability 12, no. 4: 1502.
Current resident lifestyles pose a significant threat to urban sustainable development. Therefore, low-carbon behavior is receiving increasing attention from scholars and policy makers. Ascertaining residential self-selection is essential in order to study the relationship between the built environment and travel behavior. While several studies have explored the relationship between the urban form, socioeconomic factors, and travel behavior, only a few of them have studied the impact of self-selection on household energy consumption and other forms of consumption, which are also contribute to household carbon emissions. Using large-scale field surveys of 1,485 households and high-resolution images, sourced from Google Maps in 2018, of Zhengzhou city, the present study estimated the low-carbon level of three kinds of behavior: daily energy use at home, daily travel, and daily consumption. The study investigated the influence factors on low-carbon behavior using the hierarchical linear model. We found that residential self-selection impacts both energy use and daily travel. Residents in some built environments consumed less energy at home and contributed less CO2 emissions through daily travel than others. In particular, individual-level variables significantly affected the low-carbon energy use behavior. The female, elderly, highly educated, married, and working-class residents with children had higher levels of low-carbon energy use. Community-level variables significantly affected the level of low-carbon travel and low-carbon consumption. If residents lived in areas with high density, mixed land use, and high accessibility, their travel mode and consumption behavior would entail low carbon emissions. There is a relationship between individual variables and community variables. Different individual attributes living in the same built environment have different impacts on low-carbon behaviors.
Jingfei Zhang; Lijun Zhang; Yaochen Qin; Xia Wang; Zhicheng Zheng. Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China. Sustainability 2019, 11, 6871 .
AMA StyleJingfei Zhang, Lijun Zhang, Yaochen Qin, Xia Wang, Zhicheng Zheng. Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China. Sustainability. 2019; 11 (23):6871.
Chicago/Turabian StyleJingfei Zhang; Lijun Zhang; Yaochen Qin; Xia Wang; Zhicheng Zheng. 2019. "Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China." Sustainability 11, no. 23: 6871.
Forest ecosystems in an ecotone and their dynamics to climate change are growing ecological and environmental concerns. Phenology is one of the most critical biological indicators of climate change impacts on forest dynamics. In this study, we estimated and visualized the spatiotemporal patterns of forest phenology from 2001 to 2017 in the Qinling Mountains (QMs) based on the enhanced vegetation index (EVI) from MODerate-resolution Imaging Spectroradiometer (MODIS). We further analyzed this data to reveal the impacts of climate change and topography on the start of the growing season (SOS), end of the growing season (EOS), and the length of growing season (LOS). Our results showed that forest phenology metrics were very sensitive to changes in elevation, with a 2.4 days delayed SOS, 1.4 days advanced EOS, and 3.8 days shortened LOS for every 100 m increase in altitude. During the study period, on average, SOS advanced by 0.13 days year−1, EOS was delayed by 0.22 days year−1, and LOS increased by 0.35 day year−1. The phenological advanced and delayed speed across different elevation is not consistent. The speed of elevation-induced advanced SOS increased slightly with elevation, and the speed of elevation-induced delayed EOS shift reached a maximum value of 1500 m from 2001 to 2017. The sensitivity of SOS and EOS to preseason temperature displays that an increase of 1 °C in the regionally averaged preseason temperature would advance the average SOS by 1.23 days and delay the average EOS by 0.72 days, respectively. This study improved our understanding of the recent variability of forest phenology in mountain ecotones and explored the correlation between forest phenology and climate variables in the context of the ongoing climate warming.
Haoming Xia; Yaochen Qin; Gary Feng; Qingmin Meng; Yaoping Cui; Hongquan Song; Ying Ouyang; Gangjun Liu. Forest Phenology Dynamics to Climate Change and Topography in a Geographic and Climate Transition Zone: The Qinling Mountains in Central China. Forests 2019, 10, 1007 .
AMA StyleHaoming Xia, Yaochen Qin, Gary Feng, Qingmin Meng, Yaoping Cui, Hongquan Song, Ying Ouyang, Gangjun Liu. Forest Phenology Dynamics to Climate Change and Topography in a Geographic and Climate Transition Zone: The Qinling Mountains in Central China. Forests. 2019; 10 (11):1007.
Chicago/Turabian StyleHaoming Xia; Yaochen Qin; Gary Feng; Qingmin Meng; Yaoping Cui; Hongquan Song; Ying Ouyang; Gangjun Liu. 2019. "Forest Phenology Dynamics to Climate Change and Topography in a Geographic and Climate Transition Zone: The Qinling Mountains in Central China." Forests 10, no. 11: 1007.
The dynamics of surface water play a crucial role in the hydrological cycle and are sensitive to climate change and anthropogenic activities, especially for the agricultural zone. As one of the most populous areas in China’s river basins, the surface water in the Huai River Basin has significant impacts on agricultural plants, ecological balance, and socioeconomic development. However, it is unclear how water areas responded to climate change and anthropogenic water exploitation in the past decades. To understand the changes in water surface areas in the Huai River Basin, this study used the available 16,760 scenes Landsat TM, ETM+, and OLI images in this region from 1989 to 2017 and processed the data on the Google Earth Engine (GEE) platform. The vegetation index and water index were used to quantify the spatiotemporal variability of the surface water area changes over the years. The major results include: (1) The maximum area, the average area, and the seasonal variation of surface water in the Huai River Basin showed a downward trend in the past 29 years, and the year-long surface water areas showed a slight upward trend; (2) the surface water area was positively correlated with precipitation (p < 0.05), but was negatively correlated with the temperature and evapotranspiration; (3) the changes of the total area of water bodies were mainly determined by the 216 larger water bodies (>10 km2). Understanding the variations in water body areas and the controlling factors could support the designation and implementation of sustainable water management practices in agricultural, industrial, and domestic usages.
Haoming Xia; Jinyu Zhao; Yaochen Qin; Jia Yang; Yaoping Cui; Hongquan Song; Liqun Ma; Ning Jin; Qingmin Meng. Changes in Water Surface Area during 1989–2017 in the Huai River Basin using Landsat Data and Google Earth Engine. Remote Sensing 2019, 11, 1824 .
AMA StyleHaoming Xia, Jinyu Zhao, Yaochen Qin, Jia Yang, Yaoping Cui, Hongquan Song, Liqun Ma, Ning Jin, Qingmin Meng. Changes in Water Surface Area during 1989–2017 in the Huai River Basin using Landsat Data and Google Earth Engine. Remote Sensing. 2019; 11 (15):1824.
Chicago/Turabian StyleHaoming Xia; Jinyu Zhao; Yaochen Qin; Jia Yang; Yaoping Cui; Hongquan Song; Liqun Ma; Ning Jin; Qingmin Meng. 2019. "Changes in Water Surface Area during 1989–2017 in the Huai River Basin using Landsat Data and Google Earth Engine." Remote Sensing 11, no. 15: 1824.
Quantitatively evaluating the spatial characteristics of regional e-retailing economy linkages is of great significance for clarifying the spatial organization of regional e-retailing economies, and promoting regional coordinated development. However, due to the lack of study data, it is difficult toconduct quantitative research on these regional e-retailing economic linkages. Taking advantage of emerging new data sources, the depth and breadth of related research cannow be improved. This paper considers 64 county-level economic areas in Zhejiang Province as network nodes.A revised gravity model was used to measure the intensity of the e-retailing economic linkage in 2016,based upon the e-retailing data provided by the Department of Commerce of Zhejiang Province, China. On this basis, the geographic information system (GIS) tool, a model-potential method and a social network, were used to analyze the spatial features of the e-retail economic linkages at the countylevel in Zhejiang Province. The results showed that the spatial polarization of the economic linkage pattern emerged as prominent, with the overall difference and east-west gradient difference between counties proving significant. In addition, the major linking partners of most regions were relatively singular, and a problem of vulnerability in e-retail economic development was shown.Secondly, the southwest region of Zhejiang Province was an important obstacle in the integration process of regional e-retail economy, through analyzing the connection scope of e-retailing economics. Thirdly, the central Zhejiang subgroupwas a key plate connecting east and west, which plays an importantlinking role in the development of regional equalizationwhen we analyzethe cohesive subgroup pattern. Inspired by this, we hypothesized that a microscopic analysis results of Zhejiang Province could provide some enlightenment for the balanced and integrated development of China’s regional e-retailing economy.
Wei Shen; Yaochen Qin; Zhixiang Xie. Research on the Spatial Features of the E-RetailingEconomic Linkages at County Level: A Case Study for Zhejiang Province, China. ISPRS International Journal of Geo-Information 2019, 8, 324 .
AMA StyleWei Shen, Yaochen Qin, Zhixiang Xie. Research on the Spatial Features of the E-RetailingEconomic Linkages at County Level: A Case Study for Zhejiang Province, China. ISPRS International Journal of Geo-Information. 2019; 8 (8):324.
Chicago/Turabian StyleWei Shen; Yaochen Qin; Zhixiang Xie. 2019. "Research on the Spatial Features of the E-RetailingEconomic Linkages at County Level: A Case Study for Zhejiang Province, China." ISPRS International Journal of Geo-Information 8, no. 8: 324.
Both cropland and climate change over time, but the potential effects of climate change on cropland is currently not well understood. Here, we combined temporally and spatially explicit dynamics of cropland with air temperature, precipitation, and solar radiation datasets. China’s cropland showed a clear northward-shifting trend from 1990 to 2015. The cropland decreased south of the break line at 38° N, whereas it increased from the break line to northern regions. Correspondingly, the temperature showed a significant warming trend in the early part of the study period, which slowed down in later years. During the whole study period, both precipitation and solar radiation decreased over time, showed no significant linear characteristics, and the annual fluctuations were very large. The cropland areas in China showed a displacement characteristic with the increasing temperature, precipitation, and radiation. Overall, the cropland was shifting towards the high-temperature, low-precipitation, and low-radiation areas. The cropland dynamics indicate that they are likely to face severe drought and radiation pressure. Our findings imply that more resources such as irrigation may be needed for cropland, which will undoubtedly aggravate the agricultural water use in most northern regions, and the potential impacts on food security will further emerge in the future.
Yiming Fu; Yaoping Cui; Yaochen Qin; Nan Li; Liangyu Chen; Haoming Xia. Continued Hydrothermal and Radiative Pressure on Changed Cropland in China. Sustainability 2019, 11, 3762 .
AMA StyleYiming Fu, Yaoping Cui, Yaochen Qin, Nan Li, Liangyu Chen, Haoming Xia. Continued Hydrothermal and Radiative Pressure on Changed Cropland in China. Sustainability. 2019; 11 (14):3762.
Chicago/Turabian StyleYiming Fu; Yaoping Cui; Yaochen Qin; Nan Li; Liangyu Chen; Haoming Xia. 2019. "Continued Hydrothermal and Radiative Pressure on Changed Cropland in China." Sustainability 11, no. 14: 3762.