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Knowledge about the spatial-temporal pattern of cropland abandonment is the premise for the management of abandoned croplands. Traditional mapping approaches of abandoned croplands usually utilize a multi-date classification-based land cover change trajectory. It requires quality training samples for land cover classification at each epoch, which is challenging in regions of smallholder agriculture in the absence of high-resolution imagery. Facing these challenges, a theoretical model is proposed to recognize abandoned croplands based on post-abandonment secondary succession. It applies the continuous change detection and classification (CCDC) temporal segmentation algorithm to Landsat time series (1986~2021) to obtain disjoint segments, representing croplands' status. The post-abandonment secondary succession showing a greening trend is recognized using NDVI-based harmonic analysis, so as to capture its preceding abandonment. This algorithm is applied to a mountainous area in southwest China, where cropland abandonments are widespread. Validation based on stratified random samples referenced by a vegetation index time series and satellite images shows that the detected abandoned croplands have user accuracy, producer accuracy and an F1 score ranging from 43% to 71%, with variation among abandonment year. The study area has a potential cropland extent of 22,294 km2, within which 9252 km2 of the cropland was abandoned. The three peak years of abandonment were 1994, 2000, and 2011. The algorithm is suitable to be applied to large-scale mapping due to its automatic manner. [ABSTRACT FROM AUTHOR]

Incorporating three-dimensional (3D) spatial measurement into the urban expansion measurement system plays an important role in understanding the degree of urban expansion and regulating and governing it. This article proposes an urban concrete forest and constructs an Urban Volume Sprawl Index to quantitatively study the spatiotemporal characteristics of the three-dimensional expansion of Chinese prefecture-level cities. Furthermore, geographic detectors are used to study its influencing factors. The following conclusions are drawn: (1) Between 1990 and 2018, the volume of Chinese cities has increased from 414.67 to 1,406.29 km3, with a growth rate of 239.13%. (2) The overall growth rate of urban volume shows a gradual slowing trend during the research period, from 55.99% to 40.83%. (3) Between 1990 and 2018, the Urban Volume Sprawl Index nationwide gradually slowed down (from 5.18% to 3.90%), with the largest rate reported in the western region (4.1%), the middle in the eastern region (3.46%), and the smallest in the central region (3.28%). (4) Government and economic factors have the greatest impact on the three-dimensional expansion of Chinese cities (over 69%), with social factors in the middle, and natural factors having the weakest explanatory power (less than 15%). (5) There are differences in the degree of urban expansion between two-dimensional and three-dimensional perspectives. A total of 38.1% of cities have a greater degree of urban expansion from a two-dimensional (2D) analysis perspective, which are mainly small cities located in the western and eastern regions. A total of 5.4% of cities (mainly located in the Yangtze River Delta and Pearl River Delta regions) have a greater degree of urban expansion from a 3D perspective. The remaining cities (56.5%) go through the same level of urban expansion in both analysis dimensions. A 3D urban expansion analysis can better explain and reveal the actual production and living space provided by urban expansion than 2D analysis. It can provide temporal data for urban land efficiency evaluation, ghost city identification, etc., and it has good application and promotion prospects. [ABSTRACT FROM AUTHOR]

Frequent spontaneous combustion activities restrict ecological restoration of coal waste dumps after reclamation. Effective monitoring of vegetation restoration is important for ensuring land reclamation success and preserving the ecological environment in mining areas. Development of unmanned aerial vehicle (UAV) technology has enabled fine-scale vegetation monitoring. In this study, we focused on Medicago sativa L. (alfalfa), a representative herbaceous vegetation type, in a coal waste dump after reclamation in Shanxi province, China. The alfalfa aboveground biomass (AGB) was used as an indicator for assessing vegetation restoration. The objective of this study was to evaluate the capacity of UAV-based fusion of RGB, multispectral, and thermal infrared information for estimating alfalfa AGB using various regression models, including random forest regression (RFR), gradient boosting decision tree (GBDT), K-nearest neighbor (KNN), support vector regression (SVR), and stacking models. The main results are as follows: (i) UAV multi-source data fusion improved alfalfa AGB estimation accuracy, although the enhancement diminished with the increasing number of sensor types. (ii) The stacking model consistently outperformed RFR, GBDT, KNN, and SVR regression models across all feature fusion combinations. It achieved high accuracy with R2 of 0.86–0.88, RMSE of 80.06–86.87 g/m2, and MAE of 60.24–62.69 g/m2. Notably, the stacking model based on only RGB imagery features mitigated the accuracy loss from limited types of features, potentially reducing equipment costs. This study demonstrated the potential of UAV in improving vegetation restoration management of coal waste dumps after reclamation. [ABSTRACT FROM AUTHOR]

This study aims to determine the important selection attributes of instant noodles that significantly affect consumer satisfaction in Korea and China. Several factors such as taste, price, quality, design, and brand were tested, and the relationships between satisfaction and repurchase intention were analyzed. Based on previous studies, it was found that the importance of selection attributes for instant noodle is taste, price, quality, design, and brand. Using structural equation modeling, 1,027 questionnaires were surveyed for a statistical method of examining the proposed hypotheses in China and Korea. Results of the study reveal that the importance of selection attributes affected satisfaction significantly. Furthermore, the path coefficient of satisfaction that leads to repurchase was found to be significant. However, consumers' perceived importance of selection attributes of instant noodles varied according to the countries. The path coefficients from taste to satisfaction were more significant for Korean consumers (β = 0.542) than for Chinese consumers (β = 0.359). Meanwhile, the path coefficient from corporate brand to satisfaction was more significant for Chinese consumers (β = 0. 305) than Korean consumers (β = 0.218). This study analyzes the significant selection attributes of instant noodles, the results provide meaningful implications for instant noodle companies in each country regarding the specific attributes they need to prioritize. [ABSTRACT FROM AUTHOR]

China is a major coal producing country, and also one of the countries which has the most serious coal mine accidents around the world. As a result of geological conditions, underground mining is the main way that coal is exploited in China; serious underground disasters and the corresponding fatality rate are much higher than is the case for surface mining. Although safer modern underground mining methods have been introduced across China, accidents still lead to fatalities and the loss of revenue in some mines. It is important to establish a georeferenced coal mine disasters (CMD) database to aid researchers and decision makers in better understanding the spatio-temporal distribution of such accidents across in China. This study has proposed a method to develop a georeferenced spatio-temporal CMD database via a geographic information system (GIS) platform based on statistical data released by the State Administration of Coal Mine Safety (SACMS) for the period between 2000 and 2015. The different levels and spatio-temporal characteristics of coal mining accidents were analyzed, and the space-time scan statistic permutation (STSSP) model was carried out to detect the CMD clusters; and finally, a spatio-temporal cluster analysis of Chinese coal mining accidents in 2000 and 2015 was conducted. [ABSTRACT FROM AUTHOR]

• Multi-source data are integrated to effectively construct RSEI in successive years. • The characteristics of ecological quality variation have been revealed. • The weak positive trend delayed by mining has been proved. • The extent and area of the better or worse trend have been identified. Coal-based industries are critical to the contemporary world's growth, while the environmental degradation associated with the industry is also increasing. In this study, we develop the Remote Sensing Ecological Index (RSEI) and map its distribution from 2000 to 2020 using the Muli coalfield near Qinghai Lake as the research object. This index is obtained by fitting four components that are critically related to the quality of the ecological environment, including greenness, humidity, heat and dryness, to finally obtain a desirable evaluation. The results illustrate that: (1) The RSEI displayed an overall increasing trend on the time scale, but it also went through three lengthier phases of trend changes. In space view, the RSEI of the unaltered areas has greatly improved, while the damaged areas are clearly concentrated in the study area's northwestern region, where mining is common. (2) In the trend test, the overall variation of RSEI was found to be around 3%. RSEI significantly increased in 69.57% of the study region, whereas RSEI decreased dramatically in 30.43% of the study area. (3) In opencast mining disturbed areas and undisturbed areas, a different quality structure can be discovered, with Moderate and Good levels predominating in disturbed areas and Good and Excellent levels predominating in undisturbed areas. The ecological decline in damaged areas significantly hampered the overall upward trend of RSEI. (4) The Globalmoran's I value was 0.558, 0.546, 0.409, 0.574, and 0.680 in 2000, 2005, 2010, 2015, and 2020, respectively, showing a positive association between regional distribution of ecological environment quality and that opencast mining does really degrade that quality. It has been demonstrated that our evaluation accurately classify the local environment as affected by opencast mining, making it crucial for studying the relationship between coal mining and ecological quality. This index can also be utilized in the future when conducting surveys of other regions of intense human disturbance. [ABSTRACT FROM AUTHOR]

Background: Perimenopausal insomnia is one of the core symptoms of the menopausal transition. Acupuncture is considered to exert a positive effect on restoring the normal sleep-wake cycle. However, there is little intuitive evidence besides evaluation using clinical effectiveness scales. We therefore designed this study, aiming to use more intuitive and reliable detection techniques such as functional magnetic resonance imaging before and after applying acupuncture to provide neuroimaging evidence, as well as to verify the effectiveness with other curative effect indicators.Methods/design: This study is a randomized, assessor-statistician-blinded, positive medicine controlled trial involving 40 participants. A total of 40 eligible patients with perimenopausal insomnia will be randomly assigned to two groups in a 1:1 ratio as an intervention group using acupuncture and a control group taking estazolam. Participants in the intervention group will receive six acupuncture treatment sessions per week for 4 consecutive weeks, for a total of 24 sessions during the study. Meanwhile, the medicine control group will be prescribed estazolam 1-2 mg/day to be taken 30 minutes before sleep for 4 weeks. The primary outcome is the Pittsburgh Sleep Quality Index. Secondary outcomes are the micro-movement sensitive mattress-type sleep monitoring system, the Hamilton Depression Scale, and the Hamilton Anxiety Scale. All outcomes will be evaluated before and after treatment. The safety of interventions will be assessed at every visit.Discussion: The results of this trial, which will be available in 2018, will investigate the impact of acupuncture treating perimenopausal insomnia from assessment of the sleep architecture, hormone level, and emotional-circuit neurological function, and will uncover the effective mechanism of acupuncture regulating the emotional center integrated effect.Trial Registration: Chinese Clinical Trials Register, ChCTR-IPC-16007832 . Registered on 26 January 2016. [ABSTRACT FROM AUTHOR]

The development of coal resources is necessary, but it has a huge negative impact on land, ecology, and the environment. With the increasing awareness of environmental protection and the requirements of related regulations, the design and practice of reclamation projects run through the mining life cycle and continue for a long time after the coal production. High-precision monitoring of mining disturbance and reclamation, quantifying the degree and time of vegetation disturbance and restoration, is of great significance to minimize the environmental effect of mining. Remote sensing, widely used as efficient monitoring tool, but there is not enough research on disturbance and reclamation monitoring taking into account large-scale areas and high temporal and spatial accuracy. Especially when mining sites remain unknown, how to distinguish the disturbance of coal mining and other human activities affecting the surface land cover has become a challenge. Therefore, this paper proposed a method to reconstruct the time series of mining disturbance and reclamation in a large area by using the POI (point of interest) and Landsat time series images using multiple buffer analysis methods. The process includes: (1) Retrieval of POI in the study area based on the public mining list using Python crawler, and buffering 100 km for preliminary extraction of potential mining areas; (2) Using spectral index mask and random forest algorithm to accurately extract the exposed coal on the Google Earth Engine (GEE) platform; (3) Buffering 10 km to identify the occurrence of disturbance and reclamation, using pixel-based temporal trajectory identification of LandTrendr algorithm under GEE. The method successful detect the change points of surface coal mining disturbance and reclamation in eastern Inner Mongolia of China. The results show that: (1) The method can effectively identify the extent of surface coal mining disturbance and reclamation, and the overall extraction accuracy is 81%. (2) Surface coal mining disturbance in eastern Inner Mongolia was concentrated in 2006–2011. By 2020, the total disturbed area is 627.8 km2, with an average annual disturbance of 18.5 km2, and the annual maximum disturbance to the ground reached 64.6 km2 in 2008. With the total reclaimed area being 236.3 km2, the reclamation rate is about 37.6%. This study provides a systematic solution and process for monitoring the disturbance and reclamation of surface coal mining in a large range with little known about the mines' location. It can effectively identify the mining disturbance and reclamation process which can also be extended to other areas, providing a quantitative assessment of mining disturbance and reclamation, which can support further ecological restoration decision-making. [Display omitted] • A remote sensing procedure of surface coal mine classification, disturbance and reclamation monitoring is developed. • Landsat, random forest, web scraping, and Google Earth Engine has been used to detect 73 surface coal mining sites. • 0.94% of the total study area has been disturbed by surface mining. • The developed procedure is able to reveal the surface coal mine reclamation pattern. [ABSTRACT FROM AUTHOR]

[Display omitted] • The framework coupling mining intensity and socioecological resilience was constructed. • The resilience and mining intensity were analyzed for 547 counties in China. • 12 socioecological indicators were used to evaluate resilience in spatial scale. • The zoning results enhanced our understanding of sustainable development in mining areas. Coal is an important global energy resource. However, the negative impacts of mining are important factors restricting the sustainable development of mining areas. Under the superimposed influences of different mining intensities, different natural ground conditions, and social-economic development, there are large differences in the restoration characteristics and response strategies for mining. To guide the development and utilization of coal resources and ecological restoration, the spatial distribution should be appropriately analyzed at the macroscale. Based on the web-crawler technology and multi-source remote sensing data, this paper attempted to estimate the mining intensity and the social-ecological resilience respectively at the county level, to divide the mining areas into nine regions in China. Based on the zoning results, differentiated strategies were proposed for ecological restoration and resource development and utilization in the various coal mining regions. The valuation results suggested that coal mines are widely distributed and abundant in China, mainly concentrated in the central, southwest and northwest regions. However, nearly half of the coal mining regions are with low resilience. Especially, high mining intensity-low resilience areas are concentrated in north China which account for 10.83%. These areas should receive special attention to prevent possible ecological risks and minimize economic effects. Social-ecological resilience measures system adaptation to coal mining disturbances, which can be regarded as the standard of mining intensity adjustment. In the future, local governments can try to combine ecological restoration and resource development strategies to provide support for the sustainable development of coal mining areas in China. [ABSTRACT FROM AUTHOR]

Eco-city construction is a powerful method which can advance a city from traditional industrial civilisation to ecological civilisation. The city of Huaibei, with 50 years of coal mining history, has been listed as a national resource-exhausted city. The city's sustainable development and ecological restoration work face severe challenges. This study presents a time-space evolution analysis of mining subsidence to show the evolution and the distribution of the subsidence area in Huaibei. Intensive use was made of land evaluation to formulate land use measures. According to this analysis, and based on the popular eco-reconstruction movement, suggestions for land reclamation and eco-reconstruction are proposed for the city of Huaibei. The paper aims to make strategic recommendations to help Huaibei city transform from a resource-exhausted city to an eco-city. [ABSTRACT FROM AUTHOR]

In tropical/subtropical monsoon regions, accurate rice mapping is hampered by the following factors: (1) The frequent occurrence of clouds in such areas during the rice-growing season interferes strongly with optical remote sensing observations; (2) The agro-landscape in such regions is fragmented and scattered. Rice maps produced using low spatial resolution data cannot well delineate the detailed distribution of rice, while pixel-based mapping using medium and high resolutions has significant salt-and-pepper noise. (3) The cropping system is complex, and rice has a rotation schedule with other crops. Therefore, the Phenology-, Object- and Double Source-based (PODS) paddy rice mapping algorithm is implemented, which consists of three steps: (1) object extraction from multi-temporal 10-m Sentinel-2 images where the extracted objects (fields) are the basic classification units; (2) specifying the phenological stage of transplanting from Savitzky–Golay filtered enhanced vegetation index (EVI) time series using the PhenoRice algorithm; and (3) the identification of rice objects based on flood signal detection from time-series microwave and optical signals of the Sentinel-1/2. This study evaluated the potential of the combined use of the Sentinel-1/2 mission on paddy rice mapping in monsoon regions with the Hangzhou-Jiaxin-Huzhou (HJH) plain in China as the case study. A cloud computing approach was used to process the available Sentinel-1/2 imagery from 2019 and MODIS images from 2018 to 2020 in the HJH plain on the Google Earth Engine (GEE) platform. An accuracy assessment showed that the resultant object-based paddy rice map has a high accuracy with a producer (user) accuracy of 0.937 (0.926). The resultant 10-m paddy rice map is expected to provide unprecedented detail, spatial distribution, and landscape patterns for paddy rice fields in monsoon regions. [ABSTRACT FROM AUTHOR]

Surface mining has been subject to increased criticism and pressure due to its potential to cause environmental damage. China accounts for more than half of world coal consumption, and this continued demand for coal, combined with low costs, has accelerated surface coal mining worldwide. However, it isn't easy to understand the impact of surface mining in China. Therefore, combined with POI, the Exposed Coal Frequency Index (ECFI) was constructed without any mining information in China. A LandTrendr algorithm was used to identify past mining disturbances and reclamation events (1986–2021). While examining these events, surface destruction due to coal mining in China was revealed. Based on the results, (1) the detection accuracy of statistical surface mining sites by province reaches 91.8%, while the detection accuracy of disturbance and reclamation events exceeds 72.59 %. Also, by comparing the mine data, our results provide more accurate information regarding both time and spatial consistency. (2) 253.61 km2 of surface mining sites were identified in 14 provinces or autonomous regions during 1986–2021. Of these, Inner Mongolia, Ningxia, Shanxi and Xinjiang ranked in the top four occupying 89.0% of the total mining site. (3) China has cumulatively disturbed 545.84 km2 and reclaimed 169.41 km2 including more comprehensive human activities. In the last 12 years, large-scale mining and reclamation have accounted for 51.63% and 75.17% of the cumulative area, respectively. (4) Generally, reclamation in China can be completed within four years. In contrast, reclamation time intervals and the proportion of reclamation varied widely between mining areas. Clearly, this study provides the most accurate data on surface coal mining disturbances in China, which will be beneficial for future studies in spatial geography related to mining. It also includes more policies and management creation for mines. [Display omitted] [ABSTRACT FROM AUTHOR]

The eastern plain of China is one of the most important grain production areas in China. Meanwhile, the plain is also an important coal production area with a large number of "coal-grain composite regions". Coal mining causes land subsidence and waterlogging, which destroys a significant amount of cultivated land. However, there is no dataset for the spatio-temporal distribution of subsidence water to assist related decision-making on a regional scale. Accurate monitoring of subsidence water is still a challenge, especially distinguishing among subsidence water, natural water and artificially excavated water by only using remote sensing data. Here, A new method to generate a dynamic map for the subsidence ponding year and the restoration year using the Google Earth Engine platform with 33-year-old Landsat imagery was created. The time segmentation method was used to first extract the change water pixels corresponding to subsidence water and artificially excavated water with similar trajectory features. Then, the morphological characteristics of the two types of change water at the beginning year of water accumulation are used to construct 13 landscape indexes. This approach utilizes the Random Forest algorithm to distinguish between subsidence water and artificially excavated water. The Huang-Huai-Hai plain area in eastern China was selected as the study area and extracted the subsidence water areas from 1986 to 2018. The identification accuracies for subsidence ponding year and restoration year are 88% and 85%. 79% of the subsidence water areas are located in cultivated land, which shows significant impacts to agricultural activities. The method proposed could be applied to other similar areas, the results could provide reference and data for decision-making and related land reclamation planning. • A novel methodology was developed for mapping mining subsidence water. • Map of the subsidence ponding year and restoration year. • Random forest algorithm can effectively extract the patch of subsidence water. • Contribute to monitor annual subsidence water at a regional scale. • This paper belongs to change detection using Landsat time series. [ABSTRACT FROM AUTHOR]

Coal resources play an important role in socioeconomic development around the world. Yet the development driven by coal mining is accompanied by ecological damage, social instability, and economic vulnerability, which seriously hinder the sustainable development of coal mining cities. It is, thus, urgent to realize the sustainable development of coal mining cities, premised on comprehensive and scientific analysis of these cities' vulnerability characteristics. In this study, based on the analysis of the social-economic-natural compound ecosystem (SENCE), we constructed a vulnerability evaluation indicator system (28 indicators) for coal mining cities. Took cities producing more than ten million ton of coal in China in 2015 as examples, the weight of every indicator was obtained using entropy weight method. In addition, cities were ranked and classified based on vulnerability characteristics of three subsystems. The reasons for subsystem vulnerability in different regions were analyzed. The results showed that industrial smoke and dust emissions, elevation, proportion of the area containing coal are the main reason for natural vulnerability. Unemployment rate of urban employees, and mining workers as a proportion of the secondary industry workforce are the main cause to social vulnerability. Self-sufficiency rate of local finance, and value of secondary industries as a proportion of GDP are the main indicators leading to economic vulnerability. Our findings suggest that preventing soil erosion, accelerating the resolution of historical problems, promoting green mining, and encouraging renewable energy should be adopted to reduce natural vulnerability; resettling the unemployed and adjusting employment structure are effective in enhancing the sustainability of social subsystems; changing industrial structure, encouraging self-employment, as well as implementing scientific and technological innovation should be considered to realize economic sustainability. Image 1 • A vulnerability evaluation indicator system for coal mining cities was constructed based on SENCE. • The vulnerability score of each subsystem was obtained by Entropy weight method. • Reasons for vulnerability of each subsystem are analyzed to provide reference for decision-making. [ABSTRACT FROM AUTHOR]

Underground coal mining with high groundwater levels causes many environmental problems, one of the main ones being subsidence waterlogging. After the subsidence waterlogging, the land faces many problems, such as insufficient land development and difficult and costly land restoration. Therefore, it is necessary to monitor the spatial range and temporal trajectory pattern of surface subsidence in a timely manner. When information about underground mining is lacking, it is difficult by using remote sensing alone to identify and distinguish (i) natural water, (ii) engineering water, and (iii) subsidence waterlogging. In this study, we used the Google Earth Engine platform to develop a method to detect subsidence waterlogging area and the disturbance year. The method includes pixel-based trajectory extraction and object-based water type recognition. First, LandTrendr is used to extract the change water (engineering water and subsidence waterlogging) pixels and its disturbance year. Then, the morphological method to further eliminate engineering water patches, so as to extract subsidence waterlogging. We selected the Panxie mining area in Huainan, China as the study area. Using 33 years of Landsat time-series data to generate values of the annual water frequency index, maps of the year of water accumulation caused by underground coal mining and the year of restoration during 1989–2016 are drawn with accuracies of 86.5% and 80.7%, respectively. The results show that from 1989 to 2016, the accumulated area of subsidence waterlogging was 7715.25 ha, accounting for 14.5% of the total area of the study area, of which 75.8% occurred from 2008 to 2016. Furthermore, the accumulated area of restoration was 207.18 ha, which occurred after 2007 and accounts for 2.7% of the total area of subsidence waterlogging. Based on the analysis results of the changes of waterlogging types, the best time window for restoration of the waterlogging area is 3y after water accumulation. The main innovation of this paper is to make use of the temporal heterogeneity (Number of year in patches, Y_num) and morphological index (Landscape shape index in patches, LSI) of the change water to distinguish engineering water and subsidence waterlogging. • Map of subsidence waterlogging caused by mining coal using Landsat time-series. • The annual water frequency index is capable to capture the water variability. • A spatial-temporal algorithm identifies the timing of subsidence waterlogging • The algorithm identifies the timing of backfill after subsidence waterlogging. • The algorithm is applicable to other mining areas too. [ABSTRACT FROM AUTHOR]

The development and utilization of mining resources are basic requirements for social and economic development. Both open-pit mining and underground mining have impacts on land, ecology, and the environment. Of these, open-pit mining is considered to have the greatest impact due to the drastic changes wrought on the original landform and the disturbance to vegetation. As awareness of environmental protection has grown, land reclamation has been included in the mining process. In this study, we used the Shengli Coalfield in the eastern steppe region of Inner Mongolia to demonstrate a mining and reclamation monitoring process. We combined the Google Earth Engine platform with time series Landsat images and the LandTrendr algorithm to identify and monitor mining disturbances to grassland and land reclamation in open-pit mining areas of the coalfield between 2003 and 2019. Pixel-based trajectories were used to reconstruct the temporal evolution of vegetation, and sequential Landsat archive data were used to achieve accurate measures of disturbances to vegetation. The results show that: (1) the proposed method can be used to determine the years in which vegetation disturbance and recovery occurred with accuracies of 86.53% and 78.57%, respectively; (2) mining in the Shengli mining area resulted in the conversion of 89.98 km2 of land from grassland, water, etc., to barren earth, and only 23.54 km2 was reclaimed, for a reclamation rate of 26.16%; and (3) the method proposed in this paper can achieve fast, efficient identification of surface mining land disturbances and reclamation, and has the potential to be applied to other similar areas. [ABSTRACT FROM AUTHOR]

High-intensity coal mining has resulted in numerous ecological and environmental problems, and seriously threatens ecological security in China. The identification and optimization of the ecological security pattern (ESP) can facilitate sustainable development while preserving the integrity and stability of ecosystems, which is important for improving ecological security in fragile ecosystems and areas of intensive coal mining. This paper presents an integrated framework for identifying, analyzing, and optimizing ESP in consideration of the core area extracted based on morphological spatial pattern analysis (MSPA), ecosystem services importance, and ecological risk index. The innovative method combines the model of linking different ecological source grades to multi-process minimum cumulative resistance (multi-process MCRE model) and kernel density analysis and includes the following steps: (1) ecological patches are delimited by assessing ecosystem services importance based on the contributions of water resources supply, soil conservation, gas regulation, and habitat maintenance; (2) ecological sources are identified by considering landscape connectivity along with the number and area of important ecological patches; (3) ecological resistance coefficient is determined based on the ecological risk index, which is constructed by coupling the surface drought index, landscape ecological risk index, and mine disaster risk index; (4) ecological corridors are extracted using the multi-process MCRE model, which is based on minimum cumulative resistance (MCR) theory, and the ecological potentials of ecological sources; and (5) the ESP is optimized via kernel density analysis, and regulation zones are defined based on the optimized ESP. Results demonstrate that the optimized ESP in study area included 3326 km2 of ecological sources that primarily dominated by grassland, 58 ecological nodes, 827.92 km of group corridors and 308.21 km of landscape corridors; which distribution pattern was "three horizontal, two vertical, and two circles" to ensure continuity of ecological process within study area. The restrictive, protective and key development areas accounted for 17.36%, 59.81%, and 22.83%, respectively; and corresponding planning recommendations were raised. This study not only provides an effective framework to identify, construct, and optimize ESPs in ecologically fragile coal-mining areas, but also purposes the multi-process MCRE model and ecological sources quantification that suitable for global region to achieve the sustainability between resource exploitation, urban development, and ecological protection. [ABSTRACT FROM AUTHOR]

• Ecological resilience assessment model was built integrating Over-Underground features. • Entropy and linear weighting method are used to quantify ecological resilience in 10 m grid scale. • Influencing factors of each partition are analyzed to provide reference for decision-making. The exploitation of coal resources will bring about a series of environmental problems, which will not only affect the surface ecological environment of the region, seriously threatening underground resources, but will also affect the normal production and living activities of human beings. The impacted ecological system is combined by both overground and underground features. In this paper, Shendong coal field, one of the high-strength coal mining areas in western China is used as a research area. An O-U (Overground-Underground) analysis framework and model was established to quantitatively assess the degree of mining impact on the eco-system and its resilience. The entropy method is used to calculate the weight of each index, and the comprehensive value of each grid is calculated by the linear weighted method. The comprehensive value of each grid's indicators is divided into four ecological resilience (ER) partitions by natural breakpoint method. Finally, Pearson coefficients is used to analyze the main influencing factors of the four sub-areas, and reasonable suggestions are given. By zoning the ER of the study area, it can provide reference for the mining method selection and land reclamation measures, and also provide direction for the ecological environment management in other similar areas. [ABSTRACT FROM AUTHOR]

• Ecological vulnerability index was used to evaluate ecological condition in intensive coal mining area. • The driving factors affecting EV was calculated by stepwise regression. • Coal mining activities didn't show significant negative impact on EV in study area. Ecological integrity of coal mining areas is subject to intense disruption due to the large scale and intensity of operations and the intensification of associated human activity. Negative impacts of coal mining include soil erosion, decline in soil fertility, water pollution, and structural changes to land use. Impacts of coal mining are acute in western China which has been defined as an ecologically fragile zone on account of the arid soils and low rainfall climate that render ecosystem restoration problematic. Here, we studied drivers of ecological vulnerability (EV) in an ecologically fragile area of Shaanxi province and Inner Mongolia that is one of the most globally active and intensive coal mining regions. An evaluation model, using eight indicators of EV such as slope (SL), relief amplitude (RA), rainfall erosion factor (RE), average temperature (AT), land use type (LUT), soil erosion factor (SE), net primary productivity of vegetation (NPP) and coverage of vegetation (CV), was constructed based on a Pressure-State-Response model. An Ecological Vulnerablity Index (EVI) was calculated within the region for 2005, 2010, and 2015 by using the model of EVI and spatio-temporal changes in EV were analyzed. Mechanisms and drivers of EV were assessed using the stepwise regression. The results showed that the area of industrial and mining land increased by 912.96% between 2005 and 2015, where the greatest increase occurred between 2010 and 2015 by 620.00%. The EVI fluctuated insignificantly from 2.69 to 2.78 during the study period and was little related to changes in somewhat areas of urban land use and coal mining intensity. We concluded that the EV of the region slightly increased, despite the extent and intensity of coal mining actives. The main drivers of EV were temperature, precipitation, and land use change. This research will help inform environmental protection policies and environmental planning for coal mining operations in the study area. [ABSTRACT FROM AUTHOR]

The process of urbanization and infrastructure construction has resulted in the occupation and loss of high-quality cropland. Complemented cropland with higher altitudes and slopes from either development or reclamation has become an important component of cropland resources and plays a vital role in ensuring food security. However, existing research mainly focuses on the dynamic balance of quantity, quality, productivity, and impact on the environment, and not enough attention is paid to whether the newly added cropland is efficiently used in the long term. Based on a cropping intensity dataset from 2001–2019, this study applied the sliding window and change detection methods to assess the use continuity and efficiency of complemented cropland from the perspective of cropland abandonment and explored the impact of the abandonment on food production. The results showed the following: (1) The total area of complemented cropland in 2002–2019 reached 279,416.4 km2, accounting for 13.1% of total cropland in the base year (2001). (2) 45.1% of the complemented cropland was abandoned at least once during the past 20 years, making only 65.6% of that land efficiently used, and this percentage was higher in the middle plains and downstream of the Yangtze River. (3) Abandonment had significant impact on the food production of complemented cropland—with a trend of increasing and then decreasing—leading to a food production reduction of 24.3% per year on average, which was more severe in the middle plains and downstream of the Yangtze River. Higher slope and a migrated population promoted the abandonment of complemented cropland. Therefore, the government should strengthen the monitoring of long-term utilization of complemented cropland and strategic reserves to maintain stable utilization. [Display omitted] • The continuity and efficiency of complemented cropland use need to receive additional attention. • Sliding window and change detection were used to extract abandoned complemented cropland. • 45.07% of the complemented cropland was abandoned at least once making that efficiently used only 65.64%. • The abandonment reduced the food production of complemented cropland by 24.27% per year on average. • It is significant for food security to promote effective use of complemented cropland by policy reinforcement. [ABSTRACT FROM AUTHOR]

Inspired by 'Hufu' in ancient China, we manufactured semiflexible micro crystallizer with two aspectant sessile platforms by 3D-printing technique that can construct a series of heteromorphic droplets (HDs) via stretching droplet height. By coordinating the gas–liquid interface and flow intensity (i.e., Ra/Ma), central-converging micro-flows were generated, which dominated solute and particle motion towards droplet center. Efficient harvest of single cubic NaCl crystal was achieved at platform center under wide volume and concentration ranges. [Display omitted] Droplet crystallization behavior held great potential in crystal preparation, micromaterial engineering, and molecular assembly. However, restricted by natural surface tension, the intrinsic crystallization regulation and efficient harvest of high quality crystal in diverse droplet features were still a great challenge. Herein, we developed a 3D printed semiflexible micro crystallizer with two aspectant sessile platforms that could simultaneously construct a series of heteromorphic droplets (HDs) and controllable HD shape. By shaping HD on the interface of the platform, central-converging micro-flows were generated by coordinating the gas–liquid interface and flow intensity (i.e., Ra/Ma) during HD crystallization from 'barrel', 'can', to 'sand clock' shape, which was validated via simulative and experimental research. Therefore, HDs, constructed in semiflexible micro crystallizer, exhibited efficient screening (>70 %) of single cubic crystal just at the center zone of platform, even under wide ranges of concentration and volume, manifesting excellent repeatability on high quality crystal harvest and relevant interfacial science research. [ABSTRACT FROM AUTHOR]

Currently, it is a great challenge for remote sensing technology to accurately map mangrove forests owing to periodic inundation. A submerged mangrove recognition index (SMRI) using two high- and low-tide images was recently proposed to remove the influence of tides and identify mangrove forests. However, when the tidal height of the selected low-tide image is not at the lowest tidal level, the corresponding SMRI does not function well, which results in mangrove forests below the low tidal height being undetected. Furthermore, Spartina alterniflora Loisel (S. alterniflora) was introduced to China in 1979 and rapidly spread to become the most serious invasive plant along the Chinese coastline. The current SMRI has failed to distinguish S. alterniflora from submerged mangrove forests because of their similar spectral signatures. In this study, an SMRI-based mangrove forest mapping method was developed using the time series of Sentinel-2 images to mitigate the two aforementioned issues. In the proposed method, quantile synthesis was applied to the time series of Sentinel-2 images to generate a lowest-tide synthetic image for creating SMRI to identify submerged mangrove forests. Unsubmerged mangrove forests were classified using a support vector machine, and a preliminary mangrove forest map was created by merging them. In addition, S. alterniflora was distinguished from the mangrove forests by analyzing their phenological differences. Finally, mangrove forest mapping was performed by masking S. alterniflora. The proposed method was applied to the entire coastline of the Guangxi Province, China. The results showed that it can reliably and accurately identify submerged mangrove forests derived from SMRI by synthesizing low- and high-tide images using quantile synthesis, and the differentiation of S. alterniflora using phenological differences results in more accurate mangrove mapping. This work helps to improve the accuracy of mangrove forest mapping using SMRI and its feasibility for coastal wetland monitoring. It also provides data for sustainable management, ecological protection, and restoration of vegetation in coastal zones. [ABSTRACT FROM AUTHOR]

Spontaneous combustion of coal waste dumps is a serious threat to the ecological environment and the safety of mining areas. Even after land reclamation and ecological restoration, such spontaneous combustion activities are still active. Achieving early warning of spontaneous combustion is necessary to protect the reclaimed ecosystem and reduce environmental pollution, but it has not yet been well studied. To this end, this study proposed a spatial analysis method to achieve early warning spontaneous combustion of coal waste dump after reclamation by integrating unmanned aerial vehicle (UAV) and vegetation (Medicago sativa/alfalfa) growth status. The experiment was implemented in two slope areas (Areas I and II) of a coal waste dump after reclamation in Shanxi province, China, which were under threat of spontaneous combustion. Three alfalfa growth parameters, aboveground biomass (AGB), plant water content (PWC), and plant height (PH) of the study area, were estimated from UAV imagery features and used to assess the spontaneous combustion risk. Then, soil deep temperature points (25 cm depth) distributed evenly in the study area were collected to determine the underground temperature situation. It was found that the UAV-derived rededge Chlorophyll index (CIrededge), canopy temperature depression (CTD), and canopy height model (CHM) achieved a better estimation of alfalfa AGB (R2 = 0.81, RMSE = 99.2 g/m2, and MAE = 74.9 g/m2), PWC (R2 = 0.68, RMSE = 3.9%, and MAE = 3.2%), and PH (R2 = 0.77, RMSE = 9.79 cm, and MAE = 7.68 cm) of the study area, respectively. We also observed that three alfalfa parameters were highly correlated with the soil deep temperature, but differed in degree (R2 = 0.46–0.81). Furthermore, they were consistent with the soil deep temperature in spatial distribution and could reveal the change direction of underground temperature, which will help us to detect those potential spontaneous combustion areas. These results indicated that vegetation is a prior indicator to the changes in underground temperature of coal waste dump. We believed that UAV can be an effective environmental management tool for the initial assessment of spontaneous combustion risk of coal waste dump after reclamation. • A UAV remote sensing approach to assess the spontaneous combustion risk of coal waste dump after reclamation. • Spontaneous combustion process caused damage and degradation to vegetation. • Vegetation growth parameters can be used to assess the severity and change direction of spontaneous combustion risk. • Surface temperature does not play a role in the detection of potential spontaneous combustion areas. • UAV is an effective management tool in spontaneous combustion monitoring of coal waste dump. [ABSTRACT FROM AUTHOR]

Background: To provide a comprehensive overview of temporal trends in cancer incidence during 1973-2010 in urban Shanghai.Methods: The estimated annual percent changes (EAPCs) for the whole period and for the time segments in age-standardized incidence rates (ASR) were evaluated with Joinpoint analysis. Age-period-cohort (APC) models were modeled to examine the effects of age, period and birth cohort on cancer incidence.Results: The overall ASR decreased slightly and significantly in males (EAPC of -0.41) but increased significantly in females (EAPC of 0.57) during 1973-2010 in urban Shanghai. The incidence trend was not linear and varied by time segments. During the most recent 10 years (2001-2010), the ASR in males decreased by 1.65% per year and stabilized in females. Incidence rates continued to decline during 1973-2010 for esophagus, stomach, and liver cancer in both sexes, as well as male lung cancer and cervix cancer. It should be noted that it was the first time to document a significant decline in lung cancer incidence among males during 1973-2010 with EAPC of -0.58%, and a notable upward for cervix cancer since 1996 with EAPC of 8.94%. Unfavorable trends in incidence were observed for the most common cancer sites in the 38 years period: colorectum, gallbladder & biliary tract, pancreas, kidney, bladder, brain & central nervous system (CNS), thyroid, non-Hodgkin's lymphoma (NHL), prostate, female breast, corpus uteri, and ovary. APC analysis showed age, period and birth cohort yielded different effects by cancer sites.Conclusions: The observed trends primarily reflect dramatic changes in socioeconomic development and lifestyles in urban Shanghai over the past four decades. [ABSTRACT FROM AUTHOR]

Eastern China has a long history of coal mining and a large number of coal mine sites have been abandoned in this region leaving a legacy of mining-related land subsidence, coal waste piles and brownfield sites. Furthermore, as a result of the historical planning approach in the region, many cities were built around coal mines. Therefore, the ecological restoration of abandoned mine land has become vital to the sustainable development in these cities. This paper uses the Datong coal mine site in Huainan as a case study to develop a detailed ecological restoration plan and functional division for an abandoned underground coal mine land by considering the local conditions and mining history, site assessment and integrated monitoring tools. [ABSTRACT FROM AUTHOR]

Intensive anthropogenic activities have led to drastic changes in land use/land cover (LULC) and impacted the carbon storage in high-groundwater coal basins. In this paper, we conduct a case study on the Yanzhou Coalfield in Shandong Province of China. We further classify waterbodies by using the Google Earth Engine (GEE) to better investigate the process of LULC transformation and the forces driving it in four periods from 1985 to 2020 (i.e., 1985–1995, 1995–2005, 2005–2015, and 2015–2020). We modeled the spatiotemporal dynamics of carbon storage by using InVEST based on the transformation in LULC and its drivers, including mining (M), reclamation (R), urbanization and village relocation (U), and ecological restoration (E). The results indicate that carbon storage had depleted by 19.69 % (321099.06 Mg) owing to intensive transformations in LULC. The area of cropland shrank with the expansion of built-up land and waterbodies, and 56.31 % of the study area underwent transitions in land use in the study period. U was the primary driver of carbon loss while E was the leading driver of carbon gain. While the direct impact of M on carbon loss accounted for only 5.23 % of the total, it affected urbanization and led to village relocation. R led to the recovery of cropland and the reclamation of water for aquaculture, which in turn improved the efficiency of land use. However, it contributed only 2.09 % to the total increase in carbon storage. Numerous complicated and intertwined processes (211) drove the changes in carbon storage in the study area. The work here provides valuable information for decision-makers as well as people involved in reclamation and ecological restoration to better understand the link between carbon storage and the forces influencing it. The results can be used to integrate the goals of carbon sequestration into measures for land management. [Display omitted] • The carbon storage impacted by LULC driving processes in high groundwater coal basins was investigated. • 56.31 % of the study area has undergone land use transition during 1985–2020. • The carbon storage decreased by19.69 % during the study years. • Urbanization and village relocation was the primary driver of carbon loss, ecological restoration was the leading driver of carbon gain. [ABSTRACT FROM AUTHOR]

[Display omitted] • The ecosystem "function-dynamics-structure" conceptual framework was constructed to quantify ecological sources. • Disaster disturbance risk index was introduced as revising factor to construct ecological resistance surface. • Potential ecological corridors were extracted using MCRS model constructed with considering ecosystem services importance index. • Gravity model was used to optimize ecological security pattern. Large-scale mining activities have induced numerous non-negligible eco-geological environmental issues that seriously threaten regional ecological security. Construction and optimization of an ecological security pattern (ESP) can aid coordination of mineral resource development and ecological protection. An innovative method was proposed to construct and optimize ESP, which used ecosystem "function-dynamics-structure" conceptual framework, disaster disturbance risk index, incorporating ecosystem services importance index into minimum cumulative resistance (MCR) theory (MCRS) model, and gravity model. Specifically, ecological sources are quantitatively cataloged using ecosystem "function-dynamics-structure" conceptual framework. Ecological resistance surface is revised using the disaster disturbance risk index. Ecological corridors are extracted using the MCRS model. Regulation zones are defined by combining the optimized ESP with gravity model. The optimized ESP in Shuozhou city, China includes 67 ecological nodes, 625.97 km2 of primary ecological sources, 83.87 km2 of secondary ecological sources, 534.18 km of primary ecological corridors, and 282.28 km of secondary ecological corridors. These form the spatial pattern of "two horizontal, four vertical and four circles", which will be used to maintain ecological process continuity and ecological flow within the study area. Corresponding suggestions are proposed to guide the planning of each regulation zone. The restrictive, protective, and suitable development zone areas are 1131.72 km2, 4255.47 km2 and 5238.93 km2, respectively. This methodology is not only suitable for determination of ESPs in coal mining areas, but also provides an approach, i.e., ecosystem "function-dynamics-structure" conceptual framework and MCRS model, that can be used to coordinate sustainable resource exploitation and ecological protection worldwide. [ABSTRACT FROM AUTHOR]

Land use change has an important influence on the spatial and temporal distribution of PM2.5 concentration. Therefore, based on the particulate matter (PM2.5) data from remote sensing instruments and land use change data in long time series, the Getis-Ord Gi* statistic and SP-SDM are employed to analyze the spatial distribution pattern of PM2.5 and its response to land use change in China. It is found that the average PM2.5 increased from 25.49 μg/m3 to 31.23 μg/m3 during 2000-2016, showing an annual average growth rate of 0.97%. It is still greater than 35 μg/m3 in nearly half of all cities. The spatial distribution pattern of PM2.5 presents the characteristics of concentrated regional convergence. PM2.5 is positively correlated with urban land and farmland, negatively correlated with forest land, grassland, and unused land. Furthermore, the average PM2.5 concentrations show the highest values for urban land and decrease in the order of farmland > unused land > water body > forest > grassland. The impact of land use change on PM2.5 is a non-linear process, and there are obvious differences and spillover effects for different land types. Thus, reasonably controlling the scale of urban land and farmland, optimizing the spatial distribution pattern and development intensity, and expanding forest land and grassland are conducive to curbing PM2.5 pollution. The research conclusions provide a theoretical basis for the management of PM2.5 pollution from the perspective of optimizing land use. [ABSTRACT FROM AUTHOR]

Grasping cropland abandonment patterns in China can help protect croplands, thereby ensuring the perpetuation of nationwide food security. However, the pattern of long-term cropland abandonment at the national scale remains limited. Here, we investigate the spatiotemporal patterns and drivers of cropland abandonment across China during 1990–2019 by integrating continuous long-term series of land cover, natural factors, and socioeconomic data. We find that the mean abandoned cropland area is 2.34 × 104 km2 per year. The spatial pattern of cropland and natural factors are prime drivers of cropland abandonment, but there is a substantial variation across agricultural regions. Further analysis suggests that annual food loss due to cropland abandonment is about 7.94 billion kilograms, which could feed 19.85 million people. These findings allow for a better understanding of the spatial heterogeneity and driving forces of cropland abandonment patterns, and inspire to govern global cropland abandonment and formulate relevant policies. [Display omitted] • The average annual cropland abandonment in China is 2.34 × 104 km2 (1.21%). • Cropland abandonment is mostly concentrated near the Hu line. • Driving forces vary significantly across agricultural regions. • Food loss is approximately 7.94 billion kilograms per year. • About 7.92 billion kilograms of food will still be lost by 2030. [ABSTRACT FROM AUTHOR]

• A new index was proposed to monitor surface mining disturbance. • The new index enhance the sensitivity to improve the detection accuracy. • Compared with five products, the detection accuracy is superior. • Mine Landscape Damage/Reclamation Index can be widely used in the detection of open-pit mining. The exploitation and utilization of mineral resources have significantly contributed to economic and social development; however, the procession has also negatively impacted the ecological environment. Thus, it is necessary to effectively monitor coalfields, an important basis for reasonable development and utilization of coalfields and following ecological reclamation. Based on MODIS Global Damage Index, We couple the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI), and proposal the Mine Landscape Damage Index (MLDI) and Mine Landscape Reclamation Index (MLRI) to supervise the disturbed vegetation of mines. Huolinhe coalfield, one of the largest mines in China, is monitored in this research. 3675 Landsat imageries from 1990 to 2020 are analyzed using the LandTrendr algorithm with MLDI and MLRI time series data on Google Earth Engine. The results demonstrate that this method could distinguish the region and disturbing process of damage and reclamation due to its effectiveness proved by visual interpretation of high-resolution imageries and verification of field investigation. The total detected area of vegetation damage was 16505.10 ha, and the vegetation damage in the mining was active from 2006 to 2011, with average annual damage of more than 1000 ha. The total area of vegetation restoration in the mine is 8640.81 ha, accounting for 52.35% of the vegetation damage. Vegetation restoration has increased gradually since 2010. In the past three years, vegetation restoration accounted for 47.61% of the total reclamation area. A novel index for monitoring the effects of surface damage in multi-open-pit mining areas is provided to us, and the detection is reliable. It can give the government an effective practical data reference in the sustainable development of utilization management and ecological reclamation in coalfield. [ABSTRACT FROM AUTHOR]

Land use efficiency (LUE) is considered a significant yardstick for guiding the practice toward sustainable urban development for metropolitan areas. However, existing evaluation methods on LUE ignore the urban function carrying capacity of the urban construction land. This study proposes a theoretical approach for measuring LUE from a vacancy-and-utilization perspective. Accordingly, the land use efficiency index (LUEI) measurement is built up by incorporating nighttime light intensity, population density, and facility density of built-up land. Furthermore, the spatial pattern of the peri-urban areas' LUEI of 36 metropolitan areas in China is investigated. There are three significant findings. First, the LUEIs of the peri-urban area in eastern and western areas are 0.102 and 0.116, respectively, which are almost twice higher than that of the central area, which is only 0.067. Second, the balance between the contributions of LUEI's indicators is conducive to promoting LUE, indicating a bucket effect for achieving high LUE. Third, the average LUEI of county units with fewer facilities is 1.27 and 2.65 times lower than county units with less population and human activities. This new method not only provides a practical way to monitor LUE but would also be an essential basis for land use management. • A new method for evaluating land use efficiency (LUE) is proposed. • The new method is proven applicable in 36 metropolitan areas in China. • A buckets effect for LUE indicators exists for achieving high LUE. • An organized urban function spatial layout is conducive to LUE. [ABSTRACT FROM AUTHOR]

Socioeconomic development is often dependent on the production of mining resources, but both opencast and underground mining harm vegetation and the eco-environment. Under the requirements of the construction for ecological civilization in China, more attention has been paid to the reclamation of mines and mining management. Thus, it is the basement of formulating policies related to mining management and implementing reclamation that detection of mining disturbance rapidly and accurately. This research carries on an empirical study in the Dexing copper mine, Jiangxi, China, aiming at exploring the process of distance and reclamation. Based on the dense time-series stack derived from the Landsat archive on Google Earth Engine (GEE), the disturbance of surface mining in the 1986–2020 period has been detected using the continuous change detection and classification (CCDC) algorithm. The results are that: (1) the overall accuracy of damage and recovery is 92% and 88%, respectively, and the Kappa coefficient is 85% and 84% respectively. This means that we obtained an ideal detection effect; (2) the surface-mining area was increasing from 1986–2020 in the Dexing copper mine, and the accumulation of mining damage is approximately 2865.96 ha with an annual area of 81.88 ha. We also found that the area was fluctuating with the increase. The detected natural restoration was appraised at a total of 544.95 ha in the 1988–2020 period with an average restoration of 16.03 ha. This means that it just restores less in general; (3) it has always been the case that the Dexing mine is damaged by mining and reclamation in the whole year (it is most frequently damaged month is July). All imageries in the mine are detected by the CCDC algorithm, and they are classified as four types by disturbing number in pixel scale (i.e., 0, 1, 2, more than 2 times). Based on that, we found that the only once disturbed pixels account for 64.75% of the whole disturbed pixels, which is the majority in the four classes; (4) this method provides an innovative perspective for obtaining the mining disturbed dynamic information timely and accurately and ensures that the time and number of surface mining disturbed areas are identified accurately. This method is also valuable in other applications including the detection of other similar regions. [ABSTRACT FROM AUTHOR]

Abstract: We analyzed the polychlorinated biphenyls (PCBs) in human hair collected from an electronic waste (e-waste) recycling area in southern China and compared their composition profiles and chiral signatures to those of workplace and domestic dust. The PCB concentrations showed significant age dependence in dismantling workers'' hair but not in residents'' hair. Among residents, PCB concentrations decreased in the following order: elderly people>students>pre-school children>adults. The PCB homologue and congener profiles of the workers'' hair were similar to those of the workplace dust. However, the PCB homologue profile of the residents'' hair was clearly different from that of the domestic dust. The chiral congener CB95 generally exhibited a racemic or near-racemic composition in both hair and dust, with enantiomer fractions (EFs) ranging from 0.485 to 0.525 in hair and from 0.479 to 0.504 in dust. The EFs of CB132 in dust (0.477–0.513) were closer to a racemic chiral signature than those in hair (0.378–0.521), but this difference was not significant. Our results suggest that the chiral signature of PCBs may be a better tool than the PCB composition profile for identifying the external and internal sources of organic contaminants in human hair. Further measurements of chiral PCB signatures in hair and blood from the same individuals are needed to identify the external and internal sources of PCBs in human hair. [Copyright &y& Elsevier]

Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is one of the most common congenital malformations and a susceptibility locus on chromosome 8q24 has been replicated as a genetic risk factor for NSCL/P in patients of European and Asian descent. However, given considerable variations in allele frequencies across geographical regions studied, the aim of this study was to investigate the association of rs987525 located at 8q24 with NSCL/P only among the southern Han Chinese population from Guangdong province. We recruited 216 NSCL/P cases, their parents, and 200 controls to conduct case-control analysis and family-based association studies. Genotyping of rs987525 was carried out by the matrix assisted laser desorption ionization-time of flight mass spectrometry method. Case-control analysis showed allele and genotype distributions for rs987525 were not significantly associated with the risk of NSCL/P in our study population. Similar results were found when all cases were stratified into cleft lip only and cleft lip with cleft palate. A transmission disequilibrium test showed no statistically significant transmission of A nor C alleles and family-based association test (FBAT) analysis provided no evidence of NSCL/P risk with single markers. These results do not provide evidence for an association between rs987525 at 8q24 and the risk of NSCL/P in the southern Han Chinese population from Guangdong province. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the distribution pattern of the strabismus surgery undertaken at an eye centre in Beijing, China. Methods: A retrospective analysis was conducted including the data of all strabismus surgeries performed in Beijing Tongren hospital for the 4 year period from 2003 to 2006. The proportions of different surgery types and their association with patients’ age and gender were analyzed. Result: During the study period, 8997 strabismus surgeries were performed. The number of the surgeries increased progressively each year from 1507 in 2003 to 2769 in 2006 ( p < 0.05). Intermittent exotropia was the most common of all strabismus surgeries (27.9%). Superior oblique palsy was the most common type among the paralytic strabismus surgeries. The proportions of different types of strabismus showed no significant change between successive years. Among the patients, the number of surgeries performed in the population aged 0–12 years was significantly higher than other age groups and increased from 35.37% in 2003 to 42.80% in 2006 ( p < 0.05). Conclusion: There has been a continuous increase in the number of strabismus operations in our eye centre in Beijing, and this pattern is especially obvious in children. The distribution of surgery type remained relatively constant each year. Surgery for intermittent exotropia is the most common type of procedure. [ABSTRACT FROM AUTHOR]

Chinese cabbage ( Brassica rapa L. ssp. pekinensis) is one of the most important vegetables in China. Genetic dissection of leaf mineral accumulation and tolerance to Zn stress is important for the improvement of the nutritional quality of Chinese cabbage by breeding. A mapping population with 183 doubled haploid (DH) lines was used to study the genetics of mineral accumulation and the growth response to Zn. The genetic map was constructed based on 203 AFLPs, 58 SSRs, 22 SRAPs and four ESTPs. The concentration of 11 minerals was determined in leaves for 142 DH lines grown in an open field. In addition shoot dry biomass (SDB) under normal, deficient and excessive Zn nutritional conditions were investigated in hydroponics experiments. Ten QTLs, each explaining 11.1–17.1% of the Na, Mg, P, Al, Fe, Mn, Zn and Sr concentration variance, were identified by multiple-QTL model (MQM) mapping. One common QTL was found affecting SDB under normal, deficient and excessive Zn nutritional conditions. An additional QTL was detected for SDB under Zn excess stress only. These results offer insights into the genetic basis of leaf mineral accumulation and plant growth under Zn stress conditions in Chinese cabbage. [ABSTRACT FROM AUTHOR]

Improving industrial land use efficiency is of great significance for sustainable industrial development. This paper measures the industrial land use efficiency (ILUE) in China, and explores its spatial-temporal characteristics and influencing factors by using a stochastic frontier analysis (SFA) method. A translog SFA model that characterizes the relationship between industrial land productivity and land input level is established to estimate the efficiency. The estimation results of the SFA model and related tests both show that the stochastic frontier method for ILUE measurement is suitable, and the contribution rate of technical inefficiency term to the mixed error reaches 66.9%. ILUE levels in China show an increasing trend from 2004 to 2017. The average efficiency in the east is the highest. ILUE in the west gradually surpassed that in the northeast in recent years. Reduction of the inter-group difference greatly contributed to the decrease in overall difference, but it is still the main source of overall difference. Results of the inefficiency function show that enterprise ownership structure produces negative impact on ILUE. The specialization of high-tech manufacturing industry, urbanization level and transportation condition have positive influence on ILUE, while the specialization of the chemical and rubber industry and the local financial pressure exert negative effects. Based on these, some policy recommendations for ILUE improvement are further proposed. • A stochastic frontier method is adopted to measure industrial land use efficiency (ILUE). • Theil index is used to reveal the regional disparities. • Technical inefficiency accounts for 66.9% of the mixed error. • There is significant heterogeneity of ILUE among different regions. • Policy suggestions that help to improve ILUE are further proposed. [ABSTRACT FROM AUTHOR]