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We studied the effects of the aspheric transition zone on the optical wavefront aberrations, corneal surface displacement, and stress induced by the biomechanical properties of the cornea after conventional laser in situ keratomileusis (LASIK) refractive surgery. The findings in this study can help improve visual quality after refractive surgery. Hyperopia correction in 1-5D was simulated using five types of aspheric transition zones with finite element modeling. The algorithm for the simulations was designed according to the optical path difference. Wavefront aberrations were calculated from the displacements on the anterior and posterior corneal surfaces. The vertex displacements and stress on the corneal surface were also evaluated. The results showed that the aspheric transition zone has an effect on the postoperative visual quality. The main wavefront aberrations on the anterior corneal surface are defocus, y-primary astigmatism, x-coma, and spherical aberrations. The wavefront aberrations on the corneal posterior surface were relatively small and vertex displacements on the posterior corneal surface were not significantly affected by the aspheric transition zone. Stress analysis revealed that the stress on the cutting edge of the anterior corneal surface decreased with the number of aspheric transition zone increased, and profile #1 resulted in the maximum stress. The stress on the posterior surface of the cornea was more concentrated in the central region and was less than that on the anterior corneal surface overall. The results showed that the aspheric transition zone has an effect on postoperative aberrations, but wavefront aberrations cannot be eliminated. In addition, the aspheric transition zone influences the postoperative biomechanical properties of the cornea, which significantly affect the postoperative visual quality.

Fine-scale population gridded datasets are of great significance in emergency response, resource allocation, and traffic planning. Many studies have developed fine-scale population spatialization m...

Knee osteoarthritis (KOA) is a degenerative joint disease leading to pain and disability for which no curative treatment exists. Intra-articular (IA) therapies are part of this multimodal approach and are approved by the Food and Drug Administration (FDA) and European Medicines Agency (EMA). Platelet-rich plasma (PRP), hyaluronic acid (HA), and corticosteroids (CS) have been increasingly used in recent years to treat KOA.To determine whether IA-PRP was superior to IA-HA or IA-CS administration routes in these patients.In this trial the patients were randomized to IA-HA (2 ml/week, for 3 weeks), IA-CS (1 ml) or IA-PRP (3 times, 4 ml, every 3 weeks) groups. The outcome was assessed using the Western Ontario and McMaster Universities (WOMAC) score prior to the first injection and then at 3, 6, 9 and 12 months. Pain was evaluated by a visual analogue scale (VAS) prior to treatment and after 12 months.In this study 120 patients were randomized into 3 groups. There was a significant improvement in all scores (WOMAC, VAS) in each group compared to the pretreatment values (P 0.05). The mean WOMAC scores for the IA-HA group from pretreatment to 3, 6, 9, and 12 months were 47.23 ± 5.37, 25.02 ± 4.98, 26.38 ± 5.20, 27.86 ± 4.34, and 30.64 ± 8.36, respectively. Similar improvements were noted in the IA-CS and IA-PRP groups. There were no significant differences in the WOMAC scores between the 3 groups 3 months after treatment (P 0.05) but IA-PRP showed significantly lower scores 6, 9 and 12 months after treatment (P 0.05).Intra-articular PRP injections into the knee for symptomatic early stages of KOA are a valid treatment option. The clinical efficacy of IA-PRP is comparable to that of the IA-HA and IA-CS forms after 3 months and the long-term efficacy of IA PRP is superior to IA-HA and IA-CS.

For distributed fiber optical sensing based on Sagnac effect, the intrusion is usually located by notch frequency. However, the notch spectrum is the comprehensive result of the intrusion, so when multiple disturbances simultaneously intrude from different positions of the sensing fiber, it is impossible to establish a mathematical expression between the intrusion position and the notch frequency, this leads to the problem of multi-point intrusion localization. Therefore, in this paper, deep learning technology is used to locate multiple disturbing points in Sagnac distributed optical fiber sensing system, and the related specific technologies of deep learning applying to sagnac distributed optical fiber sensing are studied. First, according to the characteristics of the system, a network structure based on the regression probability distribution is proposed, second, a loss function is constructed. The results show that the trained model can realize the positioning of multiple and single intrusion points.

With the rapid development of information technology, the sharing economy based on “Internet plus” cloud platforms has become a new collaborative innovation mode and a hot topic in recent years. Considering that government regulation restricts green innovation cooperation among cloud manufacturing enterprises, an evolutionary game model involving the government and cloud manufacturing enterprises A and B with potential differences in their technology knowledge is established using evolutionary game theory. A replication dynamic equation is established, the evolutionarily stable equilibrium strategy of the three parties is analysed, and the key factors affecting the cooperative selection strategy of the government and cloud manufacturing enterprises are discussed through a MATLAB-based numerical simulation. This research shows that when governmental incentives and punishments, the platform load capacity, the trust between enterprises, the technology loss coefficient, and the informatization degree are increased, the government will tend to choose supervision, and cloud manufacturing enterprises A and B will tend to choose the “collaborative innovation” strategy. These results provide a scientific basis suggesting that the government should not only formulate rules and regulations for cloud manufacturing enterprises but also promote green collaborative innovation among such enterprises and enhance their core competitiveness.

Tourism development activities affect the structure and functions of ecosystems directly triggering changes in the thermal environment of tourism destinations and raising a need for sustainable development of the tourism industry. Using the 2005–2015 moderate resolution imaging spectroradiometer (MODIS) data on the land surface temperature combined with the land use data, the urban thermal environment contribution index (CI) of prefecture-level cities and ecosystem types corresponding to the study area in Sichuan-Chongqing region were quantitatively calculated under various seasonal and diurnal conditions in terms of the scales of administrative divisions and ecosystem types. The characteristics of the roles played by different cities and ecosystem types to contribute to the thermal environment of the metropolitan region were summarized, and the differences and changes in the corresponding contribution intensity of various ecosystem types were measured. The results indicate the following: (1) Different cities play different roles as the sources and sinks with respect to the thermal environment in the daytime and nighttime. Based on the diurnal differences of the contribution indices, cities can be divided into three types: the day-night heat source type, the day-sink and night-source type, and the day-night heat sink type. (2) The farmland and the grassland ecosystems are the most important source and sink landscapes in the thermal environment of the Sichuan-Chongqing Region, respectively. (3) The region is affected by the spatial arrangement of the internal ecosystems and its own development conditions, and, consequently, there are significant temporal-spatial variations and role transitions between heat source and heat sink regarding the contribution of different ecosystem types to the thermal environment of individual cities. It is important to scientifically regulate the thermal environment effect on tourism destinations and maintain the comfort and sustainable development through identifying the source and sink ecosystems of the thermal environment, controlling the quantity and spatial arrangement of the heat source ecosystems, and fully enabling the cooling effect of the heat sink ecosystems.

Population migration and urban traffic are two important aspects of the socioeconomic system. We analyze the trends of social production and resumption of life after the coronavirus disease 2019 (COVID-19)-influenced Spring Festival in 2020 with statistics on reported cases of COVID-19 from China’s National Health Commission and big data from Baidu Migration (a platform collecting population migration data). We find that (1) the distribution of COVID-19 cases throughout mainland China has a specific spatial pattern. Provinces in eastern China have more reported cases than those in western China, and provinces adjacent to Hubei have more confirmed COVID-19 cases than nonadjacent provinces. Densely populated regions with well-developed economies and transportation are more likely to have cluster infection incidents. (2) The COVID-19 epidemic severely impacts the return of the migrant population in the Spring Festival travel rush, as demonstrated by the significant reduction in the return scale, along with the extended timespan and uncertainty regarding the end of the travel rush. Among 33 provinces, special administrative regions, autonomous regions and municipalities, 23 of them (approximately 70%) have a return rate below 60%. Hubei, Hong Kong, Xinjiang, and Inner Mongolia have the lowest return rates (below 5%), whereas the return rates in Hainan and Shandong, 272.72% and 97.35%, respectively, indicate the best trend of resumption. Due to government regulations, the population return in densely populated and well-developed regions shows a positive trend. (3) The resumption of urban traffic is slow and varies greatly in different regions. The urban traffic conditions in 22 provinces and municipalities have a more than 60% level of resumption. Guizhou and Yunnan have the highest level of resumption of urban traffic, whereas Xinjiang, Hubei, and Heilongjiang have the lowest (29.37%, 35.76%, and 37.90%, respectively). However, provinces and municipalities with well-developed intercity traffic have a lower level of resumption, mainly because of regulatory methods such as lockdowns and traffic restrictions. The increased public awareness of epidemic prevention and the decreased frequency of outdoor activities are also two positive factors slowing the spread of the epidemic. (4) Time will be necessary to fully resume social production and life throughout China. Xining and Jinan have the highest levels of resumption, 82.14% and 71.51%, respectively. Urumqi and Wuhan are the cities with the lowest levels of resumption, only 0.11% and 0.61%, respectively. Currently, 12 of 33 provinces and municipalities have levels of resumption of more than 80%; among them, Guizhou, Yunnan, and Gansu have with the highest levels of resumption and have nearly resumed the 2019 levels of work and life, whereas Xinjiang and Hubei have the lowest resumption rates, only 0.09% and 7.57%, respectively. Thus, relevant government departments should focus more on densely populated and well-developed provinces and cities when applying epidemic prevention and work resumption methods. We reveal the general conditions of the epidemic and the population return scale across China, along with urban traffic conditions and the resumption of social production and life under COVID-19, providing a scientific basis for local governments to make further decisions on work resumption.

Currently, most regional thermal environment (RTE) studies in urban agglomerations focus on developing countries, especially China. However, there is still a lack of comparative studies on the RTEs of urban agglomerations between China and other developed countries, such as the United States. This paper used the Beijing-Tianjin-Hebei (BTH) agglomeration in China and Boswash (the highly urbanized area extending from Boston to Washington) in the United States as examples to investigate the differences in land development patterns, RTEs and their relationship between the agglomerations of China and America. The results showed that the land development patterns of BTH and Boswash were different, as evidenced by the spatial pattern of land development intensity (LDI) and impervious surface configuration. In terms of the RTE, the sub-high land surface temperature (LST) zones were aggregated in a large and compact patch in central and northern BTH. However, the sub-high zones of the cities in Boswash were relatively separate. Moreover, the land development pattern of Boswash showed a stronger relationship with the RTE than that of BTH did. Global Moran's I between the LDI and LST in Boswash was higher than that in BTH. In addition, the correlation between impervious surface configuration and LST in Boswash was stronger than that in BTH, and this correlation was more controlled by LDI in Boswash. This study also indicated that BTH should change the land development pattern to prevent the further expansion of aggregated sub-high LST zones and control the proximity of high LST zones in cities in central and southern BTH, however, Boswash should adopt some local heat management approaches (installing cool and green roofs and creating more green space) in the core areas to help reduce the very high temperatures in the already highly developed areas where the largest fraction of people live.

Rapeseed is one of the major oil crops in China and it is very sensitive to climate change. The Yangtze River Basin is the main rapeseed production area in China. Therefore, a better understanding of the impact of climate change on rapeseed production in the basin is of both scientific and practical importance to Chinese oil industry and food security. In this study, based on climate data from 5 General Circulation Models (GCMs) with 4 representative concentration pathways (RCPs) in 2011–2040 (2020s), 2041–2070 (2050s) and 2071–2100 (2080s), we assessed the changes in rapeseed production potential between the baseline climatology of 1981–2010 and the future climatology of the 2020s, 2050s, and 2080s, respectively. The key modelling tool – the AEZ model – was updated and validated based on the observation records of 10 representative sites in the basin. Our simulations revealed that: (1) the uncertainty of the impact of climate change on rapeseed production increases with time; (2) in the middle of this century (2050s), total rapeseed production would increase significantly; (3) the average production potential increase in the 2050s for the upper, middle and lower reaches of the Yangtze River Basin is 0.939, 1.639 and 0.339 million tons respectively; (4) areas showing most significant increases in production include southern Shaanxi, central and eastern Hubei, northern Hunan, central Anhui and eastern Jiangsu.

The impact of changes in cultivated land on the production potential of food crops in China during the period of 1990–2010 was studied using land use data and the Global Agro-ecological Zones (GAEZ) model. The contribution of crop production potential per unit cultivated land area (PPCLA) to the total food-energy based production potential (TPP) of food crops was further investigated. From 1990 to 2010, China has experienced a net increase of cultivated land, resulting from a net increase in northern China and a smaller net decrease in the south. However, the TPP reduced by 9.64 × 1012 kcal despite an overall cultivated land increase for crops. This was attributed to the spatial heterogeneity of PPCLA in the cultivated land, whereby the average PPCLA of the newly cultivated land was much lower than that of the lost land. The PPCLA gap between the newly developed land and the lost cultivated land expanded from 3.16 × 106 kcal/ha in the first decade (1990–2000) to 6.49 × 106 kcal/ha in 2000–2010. Contributions of PPCLA to TPP varied among regions, and the regions with the largest contributions were consistent with those with the largest PPCLA gaps. Such regions included the Sichuan Basin and surrounding region in 1990–2000, and the Huang-Huai-Hai Plain during 2000–2010. Based on these research findings, key implications for land use policies in relation to major food crops in China are discussed.

Monitoring urban expansion dynamically using remote sensing technology is an essential method for obtaining and understanding urban spatial structure. However, the quality of traditional optical images in some areas is poor due to clouds and fog. Compared to optical images, synthetic aperture radar (SAR) can achieve earth observations without the limits of sunlight and weather conditions, but its speckle is too obvious. This paper combined the advantages of pixel-level optical image and SAR image time series and proposed a spatiotemporal fuzzy clustering (STFC) strategy for urban expansion monitoring. This strategy includes three parts: 1) the construction of optical-SAR image mixed time series; 2) a time-series fuzzy information granulation method to ascertain change nodes; and 3) STFC to determine the change types and range. In our study, 13 TM images and 25 SAR scenes taken from 2005 to 2011 were selected as raw data. We used the proposed method to monitor the urban expansion of Chengdu, China, and then, analyzed its main causes according to the monitoring results. The results suggested that: 1) the proposed methods could effectively extract the change nodes and change pixels, with the correctness of 85.20% and the completeness of 86.06%, outperforming the time series only (nonspatial) fuzzy clustering method, as well as traditional classification methods; and 2) the urban expansion of Chengdu is most apparent from 2005 to 2011, with the expansion direction shifting from the traditional ring structure expansion to point-axis expansion following the priority given to construction of new urban areas.

In the context of the popular development of the low-carbon economy, the “high energy consumption, high pollution, and high emissions” of the manufacturing industry have resulted in unprecedented difficulties in the development of this industry. To achieve nationally determined contribution targets, China has formulated a series of low carbon development plans for heavy industry to reduce carbon emissions. Among these, low-carbon technological innovation has been used a new means for manufacturing enterprises to achieve sustainable development, which is highly valued by management practice. Taking Chinese manufacturing companies as an example, the present study investigates the mediating effect of green core competence on the relationship between low-carbon technological innovation and enterprise performance and evaluates the moderating impact of firm size on this relationship. In this study, 438 valid data points were empirically analyzed, and the results indicate that low-carbon technological innovation significantly and positively affects enterprise performance of manufacturing. Green core competence plays a mediating role in the positive effect of low-carbon technological innovation on enterprise performance. Firm size has a positive moderating effect on the relationship between low-carbon technological innovation and enterprise performance. Meanwhile, firm size also moderates the relationship between low-carbon technological innovation and green core competence. Namely, a larger firm size correlates with a more positive effect on the cultivation of green core capabilities from the low-carbon technological innovation of manufacturing companies and in stronger enterprise performance. Finally, this work provides constructive guidance for Chinese manufacturing companies on how to practice low-carbon production and achieve sustainable development.

The first-stage of an ecological conservation and restoration project in the Three-River Source Region (TRSR), China, has been in progress for eight years. However, because the ecological effects of this project remain unknown, decision making for future project implementation is hindered. Thus, in this study, we developed an index system to evaluate the effects of the ecological restoration project, by integrating field observations, remote sensing, and process-based models. Effects were assessed using trend analyses of ecosystem structures and services. Results showed positive trends in the TRSR since the beginning of the project, but not yet a return to the optima of the 1970s. Specifically, while continued degradation in grassland has been initially contained, results are still far from the desired objective, ‘grassland coverage increasing by an average of 20%–40%’. In contrast, wetlands and water bodies have generally been restored, while the water conservation and water supply capacity of watersheds have increased. Indeed, the volume of water conservation achieved in the project meets the objective of a 1.32 billion m3 increase. The effects of ecological restoration inside project regions was more significant than outside, and, in addition to climate change projects, we concluded that the implementation of ecological conservation and restoration projects has substantially contributed to vegetation restoration. Nevertheless, the degradation of grasslands has not been fundamentally reversed, and to date the project has not prevented increasing soil erosion. In sum, the effects and challenges of this first-stage project highlight the necessity of continuous and long-term ecosystem conservation efforts in this region.

The combination model of cellular automata and multi-agent system were used in this paper for simulating spatio-temporal dynamics of urban expansion and its encroachment on other lands at the regional scale. The human system(contain authorities and residents) and their behavior, the landscape system and its behavior as well as the inter actions between them were all simulated in this paper. The behavior of human system is established based on multi-agent system, the authority agent and the resident agent were both regarded as abstract entities. The cellular automata is embedded into the model for simulating the spontaneous urban growth. The impact of neighbor cells were considered so that the expansion of urban lands can be limited near the existed urban lands. Moreover, the rural residential lands have higher probability to convert to urban lands if they were close to the cities or towns. Simulation of urban expansion is undertaken on the time series from 2000 to 2020 for Tianjin metropolitan region, the largest open coastal city in northern China. The results show that Tianjin’s urban lands focus on the epitaxial expansion around the central city accompanied with the growing exurb expansion distributing in multiple districts and counties. The croplands are taken the most area of the land-use types, 1764.03 km2 are converted to urban lands, and more than one fourth of the rural residential lands are changed to urban lands in 2000–2020. The urban development and the cropland protection should be both taken into account to minimize the threats on food security and ecological environment.

The ultralow angle (ULA) bevel-etched (BE) junction termination extension (JTE) for high voltage SiC power devices is proposed and investigated in this paper. The local bevel alleviates the electric field (E-field) crowding at each step corner and thus allows an increased breakdown voltage (BV) and a wide process tolerance. With a small bevel angle of 2°, the 1-step ULA-BE JTE reaches over 90% of the ideal BV of parallel plane junction and exhibits the BV 3kV higher than that of conventional (Con.) vertically-etched (VE) JTE. The 3-step ULABE JTE delivers 2.7X improvement in the etching depth window compared with Con. VE JTE. We have performed the experiment of 1-step etch of the 4H-SiC ULA-BE JTE. The etching depth of 1.67 µm with the lateral distance of 50.2 µm is obtained, demonstrating the corresponding bevel angle of 1.9°, which is a superior JTE solution for SiC high voltage power devices.

The impact of land use change on grain potential productivity is one of the most important topics in the research of land use/cover change and its effects. Western Jilin, located on the edge of an ecotone in northern China, and its land use have changed dramatically in recent decades, with significant impact on grain potential productivity. This study evaluated the grain potential productivity in different conditions and analyzed the response to land use change based on land use data, meteorological data and statistical data by using the Global Agro-ecological Zone model. Results showed that (1) grain potential productivity of Western Jilin in 2010 was 19.12 million tons, an increase of 34.8% over 1975 because of changes in land use and in climate, (2) due to land use change, grain potential productivity in the study area increased between 1975 and 2000, however, it decreased between 2000 and 2010, (3) conversion in type of land use and an increase in irrigation percentage caused grain potential productivity to increase by 0.70 million tons and 3.13 million tons respectively between 1975 and 2000, between 2000 and 2010, grain potential productivity had an increase of 0.17 million tons due to the increase in farmland area, but it decreased by 1.88 million tons because the irrigation percentage declined from 36.6% to 24.7%. Therefore, increasing investment in agriculture, improving land quality and increasing the conversion rate of grain potential productivity to actual production would be a better choice for ensuring national food security and achieving sustainable land use.

Rape is a non-grain feedstock with several characteristics that make it suitable for biofuel production, such as high oil yields and low environmental impact. Planting rape on winter fallow fields could allow for seasonal rotation between the bioenergy production and agricultural production. In the present study, the Global Agro-Ecological Zones model was used to estimate the production potential of rapeseed on winter fallow fields in the Yangtze River region from 2010 to 2015. Life cycle assessment was then conducted to calculate energy efficiency and greenhouse gas emissions from the entire energy-producing process and to estimate the number of bioenergy enterprises and their spatial distribution. The results indicated that the total area available of winter fallow fields in the Yangtze River region was 24.93 million ha, accounting for 34.2% of the total cultivated land area. The total yield of winter rapeseed was up to 46.41 million tons (an average yield of 1.86 tons/ha). Thus, the study area could potentially produce net energy of up to 3564 million MJ with energy return on energy investment (EROEI) as high as 1.52–1.84. The total reduction of greenhouse gas emissions may be up to 23.28 million tons, and the total number of bioenergy enterprises could be 589, from which the total biodiesel output could be 167.5 million tons. Hubei, Henan, Anhui and Jiangxi should be prioritized for generating biofuels from rapeseed planted on winter fallow fields.

Terrain, an important limiting factor in land use change, strongly influences agricultural productivity. This study investigated the topographical characteristics of agricultural potential productivity of cropland transformations in China during the first decade of the 21st century, and explored the impacts of cropland transformations with different terrains on agricultural potential productivity as it relates to China’s national food supply. The results showed the production potential of cropland loss was much greater than that of cropland gain in most regions, and topographical characteristics of croplands losses and gains actually impacted the agricultural potential productivity in China. The losses in agricultural potential productivity was serious in regions with good terrain conditions, where the slope is lower than 5°, and the elevation is below 100 m, especially in the middle and lower Yangtze region and the Huang-Huai-Hai region. The situation for cropland loss with better quality, and expanded the worse was severe in China, and this is expected to negatively influence sustainable agricultural development in the future. This study suggests that researchers focus not only on the total area of expanded cropland but also on cropland quality, such as the different terrain conditions of the croplands, to avoid a loss in national agricultural productivity caused by the process of cropland transformation.

China has become increasingly dependent on the international energy market owing to the rapid growth of demand for energy. To develop renewable energy and thus strengthen energy security for the future, it is important to consider the potential of crop residues. This paper contributes to this topic by mobilizing up-to-date statistical and remote-sensing data and by carrying out a geographic and economic analysis. Its assessment shows that China's total output of crop residues in 2010 amounted to 729 million tons, and the quantity could be used for commercial energy production is between 147 and 334 million tons, depending on the competition power of the commercial energy production relative to the traditional uses of crop residues. The analysis also shows that the distribution of crop residues in China is highly uneven. By taking into account the densities of crop residues available for energy production at the grid-cell level, the transportation cost constraints, and the economy-of-scale requirements of energy plants, this study further assesses the geographic distribution of the suitability for establishing crop residue based power plants and bioenergy plants in China.

For urban climatic environments, the urban heat island (UHI) effect resulting from land use and land cover change (LUCC) caused by human activities is rapidly becoming one of the most notable characteristics of urban climate change due to urban expansion. UHI effects have become a significant barrier to the process of urbanization and sustainable development of the urban ecological environment. Predicting the spatial and temporal patterns of the urban heat environment from the spatial relationship between land use and land surface temperature (LST) is key to predicting urban heat environment risk. This study established an Urban Heat Environment Risk Model (UHERM) as follows. First, the urban LST was normalized and classified during three different periods. Second, a Markov model was constructed based on spatio-temporal change in the urban heat environment between the initial year (2005) and middle year (2010), and then a cellular automata (CA) model was used to reveal spatial relationships between the urban heat environments of the two periods and land use in the initial year. The spatio-temporal pattern in a future year (2015) was predicted and the accuracy of the simulation was verified. Finally, the spatio-temporal pattern of urban heat environment risk was quantitatively forecasted based on the decision rule for the urban heat environment risk considering both the present and future status of the spatial characteristics of the urban heat environment. The MODIS LST product and LUCC dataset retrieved from remote sensing images were used to verify the accuracy of UHERM and to forecast the spatio-temporal pattern of urban heat environment risk during the period of 2015&ndash, 2020. The results showed that the risk of urban heat environment is increasing in the Chongqing metropolitan area. This method for quantitatively evaluating the spatio-temporal pattern of urban heat environment risk could guide sustainable growth and provide effective theoretical and technical support for the regulation of urban spatial structure to minimize urban heat environment risk.

China possesses substantial biomass resources, and the cultivation of energy plants on marginal land and the advancement of bioenergy may prove beneficial in easing fossil-fuel energy demands and promoting sustainable development of the economy and the environment. Taking into account the availability of marginal land and the distribution of environments suitable for the cultivation of energy crops, this study provides estimates of the potential bioenergy production for each of five species (Pistacia chinensis, Jatropha curcas, Manihot esculenta, Vernicia fordii and Helianthus tuberosus) and a geographic analysis of bioenergy enterprises in China. The results support the following conclusions: (1) the geographic distributions of potential bioenergy output of various energy crops have significant differences; (2) the central regions of China between Yunnan and Heilongjiang are suitable for the development of large- and medium-sized enterprises, whereas the area spanning northern Xinjiang, central Inner Mongolia, northern Yunnan, central Sichuan, eastern Guangdong and Hunan may support small-scale bioenergy enterprises; (3) the potential for development of bioenergy enterprises in China is enormous, the total number of bioenergy enterprises that are sustainable in China is 1788 (of which 490 are small-scale, 629 are medium-scale and 669 are large-scale operations); (4) the provinces with the greatest potential for the development of large-scale enterprises are Yunnan, Guizhou, Shaanxi, Hubei and Heilongjiang.

The Qin-Ba Ecological Functional Zone is a component of China’s ecological security pattern designed to protect the regional ecosystem and maintain biodiversity. However, due to the impact of mining and urban encroachment, the plight of a sustainable ecosystem in the Qin-Ba mountainous area is deteriorating. This paper has used a remote sensing and geographic information system (GIS) to examine the impacts of mining and urban encroachment on the environment in the Qin-Ba mountainous area. The results indicate that the total mined area in 2013 was 22 km2 and is predicted to escalate. Results also show that the ecosystems in Fengxian County, Shaanxi Province and Baokang County, Hubei Province were most severely affected by mining. Urbanization in the Qin-Ba mountainous area has seen an increase of 85.58 km2 in urban land use from 2010 to 2013. In addition, infrastructure development including airport construction, tourism resorts and real estate development in the Qin-Ba mountainous area has intensified environmental and biodiversity disturbances since large areas of forest have been cleared. Our results should provide insight and assistance to city planners and government officials in making informed decisions.

Jingjinji area (namely Beijing, Tianjin and He Bei Province) is one of the three largest regional economic communities in China. Urban expansion has sped up in the past 20 years in this area due to the rapid economic and population growth. Evaluating the land-use suitability for urban growth on a regional scale is an urgent need, because the most suitable areas and the most suitable scale of urban growth can thus be determined accordingly. In order to meet this requirement, remote sensing and geographic information system (GIS) techniques were adopted, and an integrated evaluating model was developed supported by AHP method. The integrated urban development suitability index (UDSI) was calculated using this model. According to the UDSI result, the spatial distribution of urban development suitability and its driving forces were analyzed. Urban boundaries in 1995, 2000 and 2005, which were derived from Landsat TM/ETM+ satellite data, were overlaid on the UDSI map, and the suitable urban develop tendency in this area were discussed. The result of this study indicated that integrated evaluation of urban development could be conducted in an operational way using remote sensing data, GIS spatial analysis technique and AHP modeling method.

The Three-Rivers Headwaters region (TRHR) is an ecological shelter located in the northeast of the Tibetan Plateau, China, that provides environmental protection and regional sustainable development. This region also provides ecosystem services including water supply and soil conservation and exerts major impacts on both its surroundings, as well as the whole of China. A number of ecological restoration projects have been initiated within the TRHR since 2000, including the creation of a natural reserve. Analyses of trends in land use/land cover (LULC), net primary productivity (NPP), water yield and soil conservation within the TRHR are presented based on regional climate and land use datasets and utilizing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model in tandem with the double mass curve (DMC) approach. The results of this study reveal a series of correlations between ecosystem services and lead to four distinct conclusions. First, the amount of variation between 2000 and 2012 in each LULC type within the TRHR was small. In particular, grassland substitution occurred in high-altitude areas and increased in central areas. Second, NPP, water yield, soil conservation amount and the volume of exported phosphorus (P) decreased along an east-west gradient with values of 64.44%, 38.81%, 7.37% and −49.98% recorded, respectively, between 2000 and 2012. The ecosystem services of the Yellow River basin to the east of the TRHR generally improved over the study period, while those of the Yangtze River and Lancang River basins where enhanced to a lesser extent, and obvious degradation was observed in some local areas. Third, the ecosystem services provided by forested land were highest, followed by grassland and cultivated land, respectively. Fourth, synergistic relationships were observed within the TRHR between NPP, water yield and soil conservation amount, indicating that increasing NPP simultaneously increased the values for these related factors. Synergistic relationships were also recorded between water yield and the amount of exported P, suggesting that increases in the former cause a reduction in water purity.

The multiple cropping practice is essential to agriculture because it has been shown to significantly increase the grain yield and promote agricultural economic development. In this study, potential multiple cropping systems in China are calculated based on meteorological observation data by using the Agricultural Ecology Zone (AEZ) model. Following this, the changes in the potential cropping systems in response to climate change between the 1960s and the 2010s were subsequently analyzed. The results indicate that the changes of potential multiple cropping systems show tremendous heterogeneity in respect to the spatial pattern in China. A key finding is that the magnitude of change of the potential cropping systems showed a pattern of increase both from northern China to southern China and from western China to eastern China. Furthermore, the area found to be suitable only for single cropping decreased, while the area suitable for triple cropping increased significantly from the 1960s to the 2000s. During the studied period, the potential multiple cropping index (PMCI) gap between rain-fed and irrigated scenarios increased from 18% to 24%, which indicated noticeable growth of water supply limitations under the rain-fed scenario. The most significant finding of this research was that from the 1960s to the 2000s climate change had led to a significant increase of PMCI by 13% under irrigated scenario and 7% under rain-fed scenario across the whole of China. Furthermore, the growth of the annual mean temperature is identified as the main reason underlying the increase of PMCI. It has also been noticed that across China the changes of potential multiple cropping systems under climate change were different from region to region.

climatic resource is a primary condition of determining agricultural development of area. This paper regards land use pattern as the unit of calculating, utilize the meteorological materials day by day of 1991-2000 year, and estimates the impact of recent climate fluctuation on potential productivity for crops in Northeast China. The result shows: because the climate has become warm in Northeast crop growing period in the past 10 years (The temperature has increased 2.19 degrees C and the annual precipitation decreased 305.76mm), the crop potential productivity generally reduced by 6.45%. Moreover, the change of the precipitation is the main reason causing the different trends of crop potential productivity in different area.

Northeast China is the national commercial grain base of China. It provides the critical food supply for other areas of the country every year. In this region dramatic changes, such as population increase, deforestation, grass land degeneration, wetland shrinking and so on, have taken place in recent several decades. The changes in resources and environment in this region have significant impacts on human living, social economy and many other aspects of the regional development. In this study uses Remote Sensing (RS), GIS and other information technology to reconstruct a digital Northeast China of the last 100 years from year 1900 to 2000. This paper first introduces the Digital Northeast China of this 100 years which includes the system targets, data foundation and design frame. Then as a case study, the woodland resource changes after 1980s based on the completed dataset are analyzed. This Digital Northeast China is based on satellite remote sensing images (Landsat TM and ETM) and topology maps and can help people solve problems related to population, natural resources and environment. On the other hand, the Digital Northeast China system can help farmers make wise use of land, increase production and preserve environment simultaneously. Furthermore, using data contained in the system, geographical scientists can analyze the resource and environment changes and make certain forecasts of the future development.

During the past 20 years, China's agro-ecosystems have great changes in response to changes in climate and agricultural management. Agricultural productivity is of vital importance to the national food security and sustainable development. So far, agricultural statistics are the only source of the data about changes in agricultural productivity in national scale, and there is little geo-spatial information on these changes. Remote sensing provides an important tool to monitor the spatial and temporal variations at high resolution, but it had yet to be used fully at regional and national scales to assess the interannual and long-term changes in agricultural productivity. This study estimated agricultural net primary productivity (ANPP) at the national level using a remote sensing-based production efficiency model, GLO-PEM. In the study, the arable area has been derived from TM data. ANPP was calculated from 8km, 10-day composite Advanced Very High Resolution Radiometers (AVHRR) data from 1981 to 2000 using GLO-PEM model. Using the data we analyzed the spatial variations in agricultural productivity in China between the 1980s and the 1990s. A 3-level hierarchy regionalization system is used in analyzing the spatial pattern and its changes in the agricultural productivity. China's average agricultural ANPP increased 59.8 million tons from the 1980s to the 1990s. The increment of ANPP mainly occurred in the major cereal-planting plains, especially HuangHuaiHai Plain. The characteristics of land resources are the dominating factors to cause the changes at 10 years scale. There were some decreases, which mainly caused by the degradation on fragile lands, the rapid expansion of rural industries, and the urban development from high-quality arable lands.

Land-Use/Land-Cover Change (LUCC) affects farmland productivity by changing the quality of land resource and pattern of land-use. Based on meteorological data and land-use/cover observation dataset obtained from the dynamic serving system of National Resources and Environment Database (NRED), this paper calculated the Photosynthetic Thermal Productivity (PTP) of farmland, and analyzed impact of recent LUCC and climate fluctuation on PTP. Results showed that under the influence of LUCC, PTP distribution had an extensive and unbalanced change. LUCC increased China's total PTP by 26.22 million tons, while climate fluctuation increased it by 169.92 million tons. The ratio between LUCC and climate fluctuation was 1:6.48. Due to the direct effect of LUCC, PTP increased in the following regions: Northeastern Plain, Inner Mongolia, and Xinjiang province. This increase was primarily driven by plantation reclamation. PTP decreased in the Huang-Huai-Hai Plain, the Yangtse Rive delta, the Zhujiang delta, the Southeastern coastal provinces, the southeastern Sichuan basin and the Xinjiang oasis. The decrease was mainly caused by urban expansion.

Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1) images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization) with convenience.

We found that formula (1) was incorrect in our paper published in Sensors in 2008 [1]. [...]