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The Chinese economy is moving from rapid growth to high-quality development, with the goal of striving for coordinated socioeconomic and eco-environmental development. Ensuring that ecosystem functions are not damaged by economic development is a primary goal of ecological civilization construction. Therefore, it is necessary to reveal the dependence relationships between humans and ecosystems, as well as the flow and appropriation of ecological resources between different regions. In this paper, Net Primary Productivity, as a measurable indicator of ecological resources, was used to analyze the supply-consumption relationship of ecological resources in China. The results showed that ecological resources are completely self-sufficient in China. However, the self-sufficiency of ecological resources decreased from 202% to 144%, while the ecosystem pressure increased by 10.12% with the growth of the population and living consumption level. Although the living demands for ecological resources in urbanized regions was increasing, the ecosystem pressure is decreasing by occupying the remote ecological resources, which leads to ecological consumption shifting to other functional regions. Meanwhile, driven by increasing local and remote living demands, the ecosystem pressure has obviously increased in main agricultural production regions, while slowly increased or even decreased in key ecological functional regions due to the guidance of ecological civilization construction. This study proved the effects of ecological civilization construction on harmonizing development in urbanized regions, while the growing ecological pressure also reminds us of the implementation of an inter-regional ecological payment transfer policy to ensure sustainable development in main agricultural production regions and key ecological functional regions.
Wenpeng Du; Huimin Yan; Zhiming Feng; Yanzhao Yang; Fang Liu. The supply-consumption relationship of ecological resources under ecological civilization construction in China. Resources, Conservation and Recycling 2021, 172, 105679 .
AMA StyleWenpeng Du, Huimin Yan, Zhiming Feng, Yanzhao Yang, Fang Liu. The supply-consumption relationship of ecological resources under ecological civilization construction in China. Resources, Conservation and Recycling. 2021; 172 ():105679.
Chicago/Turabian StyleWenpeng Du; Huimin Yan; Zhiming Feng; Yanzhao Yang; Fang Liu. 2021. "The supply-consumption relationship of ecological resources under ecological civilization construction in China." Resources, Conservation and Recycling 172, no. : 105679.
Improving the urban livability status has become the core goal of urban development, and reasonable assessment of the urban livability status and impact is crucial. By combining an objective environment with residents’ subjective cognition, an artificial society (urban livability change artificial society; ULC-AS) is constructed. The ULC-AS includes four types of agents, namely, government, family, resident and safety facility management agency agents, and recognizes dynamic interaction among various agents and between agents and the environment. Taking the Futian District of Shenzhen as an example, this paper examines factors such as migrants, birth policies, and government investment. We simulate the interactions among resident satisfaction changes, relocation decision-making behavior and urban safety livability and analyze the change processes and development trends of urban safety livability under multiple scenarios. Our main result indicates that population change and investment construction are important factors affecting urban safety livability. At present, the population of the Futian District is saturated. Therefore, the government must assess the urban safety livability and increase investment in high-demand areas. Through this method, the goals of urban resource allocation optimization and coordinated urban development can be achieved.
Lihu Pan; Le Zhang; Shipeng Qin; Huimin Yan; Rui Peng; Fen Li. Study on an Artificial Society of Urban Safety Livability Change. ISPRS International Journal of Geo-Information 2021, 10, 70 .
AMA StyleLihu Pan, Le Zhang, Shipeng Qin, Huimin Yan, Rui Peng, Fen Li. Study on an Artificial Society of Urban Safety Livability Change. ISPRS International Journal of Geo-Information. 2021; 10 (2):70.
Chicago/Turabian StyleLihu Pan; Le Zhang; Shipeng Qin; Huimin Yan; Rui Peng; Fen Li. 2021. "Study on an Artificial Society of Urban Safety Livability Change." ISPRS International Journal of Geo-Information 10, no. 2: 70.
As the country with the highest food consumption in the world, China’s food security has been drawing global attention. The inter-annual variability of agricultural productivity and its predominant driving factors play important roles in food security and sustainable agricultural development. Here, we used gross primary productivity (GPP), which was simulated using the vegetation photosynthesis model (VPM), to quantify the spatial-temporal heterogeneity of cropland productivity from 2000 to 2015. The results showed that the cropland GPP significantly increased in northern China and markedly decreased in southern China. Socioeconomic and climatic factors jointly promoted a rise in GPP in the Northeast region, Inner Mongolia and Great Wall region, Huang-Huai-Hai region, and Loess Plateau region, with contribution rates of 93.6%, 67.9%, 73.8%, and 78.1%, respectively. The negative GPP trend in southern China was mainly attributed to the decreasing cropping intensity, with direct contributions of 54.1%, 53.9%, and 48.7% for the Yangtze River region, Southwest region, and South China region, respectively. Despite the decline in cropping intensity, the policies of Cang-liang-yu-di and Cang-liang-yu-ji can help in ensuring food security in China.
Zhongen Niu; Huimin Yan; Fang Liu. Decreasing Cropping Intensity Dominated the Negative Trend of Cropland Productivity in Southern China in 2000–2015. Sustainability 2020, 12, 10070 .
AMA StyleZhongen Niu, Huimin Yan, Fang Liu. Decreasing Cropping Intensity Dominated the Negative Trend of Cropland Productivity in Southern China in 2000–2015. Sustainability. 2020; 12 (23):10070.
Chicago/Turabian StyleZhongen Niu; Huimin Yan; Fang Liu. 2020. "Decreasing Cropping Intensity Dominated the Negative Trend of Cropland Productivity in Southern China in 2000–2015." Sustainability 12, no. 23: 10070.
Spatial data of regional populations are indispensable in studying the impact of human activities on resource utilization and the ecological environment. Because the differences between datasets and their spatial distribution are still unclear, this has become a puzzle in data selection and application. This study is based on four mainstream spatialized population datasets: the History Database of the Global Environment version 3.2.000 (HYDE), Gridded Population of the World version 4 (GPWv4), Global Human Settlement Layer (GHSL), and WorldPop. In view of possible influences of geographical factors, this study analyzes the differences in accuracy of population estimation by computing relative errors and population spatial distribution consistency in different regions by comparing datasets pixel by pixel. The results demonstrate the following: (1) Source data, spatialization methods, and case area features affect the precision of datasets. As the main data source is statistical data and the spatialization method maintains the population in the administrative region, the populations of GPWv4 and GHSL are closest to the statistical data value. (2) The application of remote sensing, mobile communication, and other geospatial data makes the datasets more accurate in the United Kingdom, with rich information, and the absolute value of relative errors is less than 4%. In the Tibet Autonomous Region of China, where data are hard to obtain, the four datasets have larger relative errors. However, the area where the four datasets are completely consistent is as high as 84.73% in Tibet, while in the UK it is only 66.76%. (3) The areas where the spatial patterns of the four datasets are completely consistent are mainly distributed in areas with low population density, or with developed urbanization and concentrated population distribution. Areas where the datasets have poor consistency are mainly distributed in medium population density areas with high urbanization levels. Therefore, in such areas, a more careful assessment should be made during the data application process, and more emphasis should be placed on improving data accuracy when using spatialization methods.
Ruxia Chen; Huimin Yan; Fang Liu; Wenpeng Du; Yanzhao Yang. Multiple Global Population Datasets: Differences and Spatial Distribution Characteristics. ISPRS International Journal of Geo-Information 2020, 9, 637 .
AMA StyleRuxia Chen, Huimin Yan, Fang Liu, Wenpeng Du, Yanzhao Yang. Multiple Global Population Datasets: Differences and Spatial Distribution Characteristics. ISPRS International Journal of Geo-Information. 2020; 9 (11):637.
Chicago/Turabian StyleRuxia Chen; Huimin Yan; Fang Liu; Wenpeng Du; Yanzhao Yang. 2020. "Multiple Global Population Datasets: Differences and Spatial Distribution Characteristics." ISPRS International Journal of Geo-Information 9, no. 11: 637.
Recently, the increasing shrub-encroached grassland in the Mongolian Plateau partly indicates grassland quality decline and degradation. Accurate shrub identification and regional difference analysis in shrub-encroached grassland are significant for ecological degradation research. Object-oriented filter (OOF) and digital surface model (DSM)-digital terrain model (DTM) analyses were combined to establish a high-accuracy automatic shrub identification algorithm (CODA), which made full use of remote sensing products by unmanned aircraft systems (UASs). The results show that: (1) The overall accuracy of CODA in the Grain for Green test area is 89.96%, which is higher than that of OOF (84.52%) and DSM-DTM (78.44%), mainly due to the effective elimination of interference factors (such as shrub-like highland, well-grown grassland in terrain-depression area, etc.) by CODA. (2) The accuracy (87.5%) of CODA in the typical steppe test area is lower than that (92.5%) in the desert steppe test area, which may be related to the higher community structure complexity of typical steppe. Besides, the shrub density is smaller, and the regional difference is more massive in the typical steppe test area. (3) The ground sampling distance for best CODA accuracy in the Grain for Green test area is about 15 cm, while it is below 3 cm in the typical and desert steppe test area.
Yu Dong; Huimin Yan; Na Wang; Mei Huang; Yunfeng Hu. Automatic Identification of Shrub-Encroached Grassland in the Mongolian Plateau Based on UAS Remote Sensing. Remote Sensing 2019, 11, 1623 .
AMA StyleYu Dong, Huimin Yan, Na Wang, Mei Huang, Yunfeng Hu. Automatic Identification of Shrub-Encroached Grassland in the Mongolian Plateau Based on UAS Remote Sensing. Remote Sensing. 2019; 11 (13):1623.
Chicago/Turabian StyleYu Dong; Huimin Yan; Na Wang; Mei Huang; Yunfeng Hu. 2019. "Automatic Identification of Shrub-Encroached Grassland in the Mongolian Plateau Based on UAS Remote Sensing." Remote Sensing 11, no. 13: 1623.
Sustainable ecosystem services consumption is of vital importance to the survival and development of human society. How to balance the conflicts between ecosystem protection and ecosystem services consumption by local residents has been a serious challenge, especially in ecologically vulnerable areas. To explore the reasonable ecosystem services consumption approaches of grassland ecosystems for sustainable land system management, this study takes Hulun Buir of the Inner Mongolia Autonomous Region as a case study region and develops an EcoC-G (ecological consumption of grassland) model based on herders’ livelihood behaviors using the agent-based model technique to simulate the dynamics of ecosystem pressure, livestock production, and living quality of herders under different grassland management scenarios over the next 30 years. The EcoC-G model links the supply and consumption of grassland ecosystem services by calculating the ecosystem net primary productivity (NPP) supply and household NPP consumption. The model includes three sub-models, namely, the individual status transferring sub-model, the households’ grassland-use decision sub-model, and the ecosystem pressure sub-model. In accordance with multi-objective grassland management practices, the following four land management scenarios were simulated: (1) baseline scenario, (2) increasing household’s living standard, (3) ecosystem protection, and (4) balancing living standard improvement with the protection of the ecosystem. The result indicates that by focusing on the NPP supply and consumption of the grassland ecosystem, the EcoC-G is capable of simulating the impacts of herders’ livelihood behaviors on grassland ecosystems. If timely grassland management strategies are implemented, it is possible to relieve the ecosystem pressure and improve the livelihood of local herders. The specific scenario simulation results are: (1) Under the current grassland management mode, the pasture could never be overgrazed, and herders could achieve the basic living standard, but the accumulated wealth decreased due to the decline of livestock. (2) With grazing control, herders can accumulate wealth by increasing the breeding amount and reducing the marketing rate, but the ecosystem consumption pressure can reach a maximum of 2.3 times. (3) With strict restrictions on the livestock number, the pressure on the ecosystem decreases; however, herders might not achieve basic living standards. (4) Modest regulation leads to rational ecological consumption intervals, meaning the ecosystem pressure will become stable and herders can gradually accumulate wealth with the achievement of basic living standards in advance.
Huimin Yan; Lihu Pan; Zhichao Xue; Lin Zhen; Xuehong Bai; Yunfeng Hu; He-Qing Huang. Agent-Based Modeling of Sustainable Ecological Consumption for Grasslands: A Case Study of Inner Mongolia, China. Sustainability 2019, 11, 2261 .
AMA StyleHuimin Yan, Lihu Pan, Zhichao Xue, Lin Zhen, Xuehong Bai, Yunfeng Hu, He-Qing Huang. Agent-Based Modeling of Sustainable Ecological Consumption for Grasslands: A Case Study of Inner Mongolia, China. Sustainability. 2019; 11 (8):2261.
Chicago/Turabian StyleHuimin Yan; Lihu Pan; Zhichao Xue; Lin Zhen; Xuehong Bai; Yunfeng Hu; He-Qing Huang. 2019. "Agent-Based Modeling of Sustainable Ecological Consumption for Grasslands: A Case Study of Inner Mongolia, China." Sustainability 11, no. 8: 2261.
Phosphorus (P) is a fundamental component of plant organisms. Most of the Earth System Models (ESMs) project increases in future Net Primary Productivity (NPP) due to climate warming. However, large uncertainty exists in projected NPP due to future P limitation. Subtropical China is a region with high vegetation NPP, but its forests are mostly P limited. In this study, we used the simulations of Atmospheric-Vegetation Interaction Model 2 (AVIM2) to diagnose the P limitation in forests in this region, and found that climate warming in the period of 1951–2010 had enhanced P limitation. The P demand during 1981–2010 for Evergreen Broad-leaved Forest (EBF) and Evergreen Needle-leaved Forest (ENF) are 1.67 and 1.8 times than that during 1951–1980, respectively. The observed current Available Soil P (ASP) density in 4 representative forest sites in subtropical China varied between 940 mg · m − 2 and 2365 mg · m − 2 , and the P demands account for 0.86% to 25.5% of the ASP for the period of 1951–2010. Future P demands are estimated to account for 3.2% to 68.3% of the current ASP at the end of this century for RCP8.5. Therefore, forests, especially plantations, in subtropical China are facing high risks of P limitation.
Na Wang; Mei Huang; Fengxue Gu; Huimin Yan; Shaoqiang Wang; Honglin He; Zhaosheng Wang; Xiangyang Sun; Wenting Xu; Fengting Yang; Guowei Chu. Diagnosing Phosphorus Limitation in Subtropical Forests in China under Climate Warming. Sustainability 2019, 11, 2202 .
AMA StyleNa Wang, Mei Huang, Fengxue Gu, Huimin Yan, Shaoqiang Wang, Honglin He, Zhaosheng Wang, Xiangyang Sun, Wenting Xu, Fengting Yang, Guowei Chu. Diagnosing Phosphorus Limitation in Subtropical Forests in China under Climate Warming. Sustainability. 2019; 11 (8):2202.
Chicago/Turabian StyleNa Wang; Mei Huang; Fengxue Gu; Huimin Yan; Shaoqiang Wang; Honglin He; Zhaosheng Wang; Xiangyang Sun; Wenting Xu; Fengting Yang; Guowei Chu. 2019. "Diagnosing Phosphorus Limitation in Subtropical Forests in China under Climate Warming." Sustainability 11, no. 8: 2202.
Land cover and its dynamic information is the basis for characterizing surface conditions, supporting land resource management and optimization, and assessing the impacts of climate change and human activities. In land cover information extraction, the traditional convolutional neural network (CNN) method has several problems, such as the inability to be applied to multispectral and hyperspectral satellite imagery, the weak generalization ability of the model and the difficulty of automating the construction of a training database. To solve these problems, this study proposes a new type of deep convolutional neural network based on Landsat-8 Operational Land Imager (OLI) imagery. The network integrates cascaded cross-channel parametric pooling and average pooling layer, applies a hierarchical sampling strategy to realize the automatic construction of the training dataset, determines the technical scheme of model-related parameters, and finally performs the automatic classification of remote sensing images. This study used the new type of deep convolutional neural network to extract land cover information from Qinhuangdao City, Hebei Province, and compared the experimental results with those obtained by traditional methods. The results show that: (1) The proposed deep convolutional neural network (DCNN) model can automatically construct the training dataset and classify images. This model performs the classification of multispectral and hyperspectral satellite images using deep neural networks, which improves the generalization ability of the model and simplifies the application of the model. (2) The proposed DCNN model provides the best classification results in the Qinhuangdao area. The overall accuracy of the land cover data obtained is 82.0%, and the kappa coefficient is 0.76. The overall accuracy is improved by 5% and 14% compared to the support vector machine method and the maximum likelihood classification method, respectively.
Yunfeng Hu; Qianli Zhang; Yunzhi Zhang; Huimin Yan. A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China. Remote Sensing 2018, 10, 2053 .
AMA StyleYunfeng Hu, Qianli Zhang, Yunzhi Zhang, Huimin Yan. A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China. Remote Sensing. 2018; 10 (12):2053.
Chicago/Turabian StyleYunfeng Hu; Qianli Zhang; Yunzhi Zhang; Huimin Yan. 2018. "A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China." Remote Sensing 10, no. 12: 2053.
Fengxue Gu; Yuandong Zhang; Mei Huang; Bo Tao; Huimin Yan; Rui Guo; Jie Li. Reply to “Critical assessment of the current state of scientific knowledge, terminology, and research needs concerning the ecological effects of elevated atmospheric nitrogen deposition in China”. Atmospheric Environment 2017, 153, 18 -20.
AMA StyleFengxue Gu, Yuandong Zhang, Mei Huang, Bo Tao, Huimin Yan, Rui Guo, Jie Li. Reply to “Critical assessment of the current state of scientific knowledge, terminology, and research needs concerning the ecological effects of elevated atmospheric nitrogen deposition in China”. Atmospheric Environment. 2017; 153 ():18-20.
Chicago/Turabian StyleFengxue Gu; Yuandong Zhang; Mei Huang; Bo Tao; Huimin Yan; Rui Guo; Jie Li. 2017. "Reply to “Critical assessment of the current state of scientific knowledge, terminology, and research needs concerning the ecological effects of elevated atmospheric nitrogen deposition in China”." Atmospheric Environment 153, no. : 18-20.
Grassland degradation intensifies human-environment conflicts and adversely affects local residents’ livelihoods. To reduce grassland degradation in Inner Mongolia, China, the government has enforced (since 1998) a series of grassland conservation and management policies that restrict the use of grasslands. To ease the impact on the residents’ livelihoods, the national and regional governments have offered a series of top-down arrangements to stimulate sustainable use of the grasslands. Simultaneously, local households spontaneously developed bottom-up countermeasures. To determine the effects of these processes, we interviewed members of 135 households using a mix of qualitative and quantitative methods. We analyzed the effects on household dependence on local grasslands and on perceptions of the future of grassland use. Our findings show that the implementation of the grassland conservation policies significantly affected household livelihoods, which in turn affected household use of natural assets (primarily the land), their agricultural assets (farming and grazing activities) and their financial assets (income and consumption), resulting in fundamental transformation of their lifestyles. The households developed adaptation measures to account for the dependence of their livelihood on local ecosystems by initializing strategies, such as seeking off-farm work, leasing pasture land, increasing purchases of fodder for stall-fed animals and altering their diet and fuel consumption to compensate for their changing livelihoods.
Bingzhen Du; Lin Zhen; Huimin Yan; Rudolf De Groot. Effects of Government Grassland Conservation Policy on Household Livelihoods and Dependence on Local Grasslands: Evidence from Inner Mongolia, China. Sustainability 2016, 8, 1314 .
AMA StyleBingzhen Du, Lin Zhen, Huimin Yan, Rudolf De Groot. Effects of Government Grassland Conservation Policy on Household Livelihoods and Dependence on Local Grasslands: Evidence from Inner Mongolia, China. Sustainability. 2016; 8 (12):1314.
Chicago/Turabian StyleBingzhen Du; Lin Zhen; Huimin Yan; Rudolf De Groot. 2016. "Effects of Government Grassland Conservation Policy on Household Livelihoods and Dependence on Local Grasslands: Evidence from Inner Mongolia, China." Sustainability 8, no. 12: 1314.
Rice is an important food crop and a large producer of green-house relevant methane. Accurate and timely maps of paddy fields are most important in the context of food security and greenhouse gas emission modelling. During their life-cycle, rice plants undergo a phenological development that influences their interaction with waves in the visible light and infrared spectrum. Rice growth has a distinctive signature in time series of remotely-sensed data. We used time series of MODIS (Moderate Resolution Imaging Spectroradiometer) products MOD13Q1 and MYD13Q1 and a one-class support vector machine to detect these signatures and classify paddy rice areas in continental China. Based on these classifications, we present a novel product for continental China that shows rice areas for the years 2002, 2005, 2010 and 2014 at 250-m resolution. Our classification has an overall accuracy of 0.90 and a kappa coefficient of 0.77 compared to our own reference dataset for 2014 and correlates highly with rice area statistics from China’s Statistical Yearbooks (R2 of 0.92 for 2010, 0.92 for 2005 and 0.90 for 2002). Moderate resolution time series analysis allows accurate and timely mapping of rice paddies over large areas with diverse cropping schemes.
Kersten Clauss; Huimin Yan; Claudia Kuenzer. Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series. Remote Sensing 2016, 8, 434 .
AMA StyleKersten Clauss, Huimin Yan, Claudia Kuenzer. Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series. Remote Sensing. 2016; 8 (5):434.
Chicago/Turabian StyleKersten Clauss; Huimin Yan; Claudia Kuenzer. 2016. "Mapping Paddy Rice in China in 2002, 2005, 2010 and 2014 with MODIS Time Series." Remote Sensing 8, no. 5: 434.
With a continuously increasing population and better food consumption levels, improving the efficiency of arable land use and increasing its productivity have become fundamental strategies to meet the growing food security needs in China. A spatial distribution map of medium- and low-yield cropland is necessary to implement plans for cropland improvement. In this study, we developed a new method to identify high-, medium-, and low-yield cropland from Moderate Resolution Imaging Spectroradiometer (MODIS) data at a spatial resolution of 500 m. The method could be used to reflect the regional heterogeneity of cropland productivity because the classification standard was based on the regionalization of cropping systems in China. The results showed that the proportion of high-, medium-, and low-yield cropland in China was 21%, 39%, and 40%, respectively. About 75% of the low-yield cropland was located in hilly and mountainous areas, and about 53% of the high-yield cropland was located in plain areas. The five provinces with the largest area of high-yield cropland were all located in the Huang-Huai-Hai region, and the area amounted to 42% of the national high-yield cropland area. Meanwhile, the proportion of high-yield cropland was lower than 15% in Heilongjiang, Sichuan, and Inner Mongolia, which had the largest area allocated to cropland in China. If all the medium-yield cropland could be improved to the productive level of high-yield cropland and the low-yield cropland could be improved to the level of medium-yield cropland, the total productivity of the land would increase 19% and 24%, respectively.
Huimin Yan; Yongzan Ji; Jiyuan Liu; Fang Liu; Yunfeng Hu; Wenhui Kuang. Potential promoted productivity and spatial patterns of medium- and low-yield cropland land in China. Journal of Geographical Sciences 2016, 26, 259 -271.
AMA StyleHuimin Yan, Yongzan Ji, Jiyuan Liu, Fang Liu, Yunfeng Hu, Wenhui Kuang. Potential promoted productivity and spatial patterns of medium- and low-yield cropland land in China. Journal of Geographical Sciences. 2016; 26 (3):259-271.
Chicago/Turabian StyleHuimin Yan; Yongzan Ji; Jiyuan Liu; Fang Liu; Yunfeng Hu; Wenhui Kuang. 2016. "Potential promoted productivity and spatial patterns of medium- and low-yield cropland land in China." Journal of Geographical Sciences 26, no. 3: 259-271.
Farmland is the most basic material condition for guaranteeing rural livelihoods and national food security, and exploring management strategies that take both stable rural livelihoods and sustainable farmland use into account has vital significance in theory and practice. Farmland is a complex and self-adaptive system that couples human and natural systems, and natural and social factors that are related to its changing process need to be considered when modeling farmland changing processes. This paper uses Qianjingou Town in the Inner Mongolian farming–pastoral zone as a study area. From the perspective of the relationship between household livelihood and farmland use, this study establishes the process mechanism of farmland use change based on questionnaire data, and constructs a multi-agent simulation model of farmland use change using the Eclipse and Repast toolbox. Through simulating the relationship between natural factors (including geographical location) and household behavior, this paper systematically simulates household farmland abandonment and rent behaviors, and accurately describes the dynamic interactions between household livelihoods and the factors related to farmland use change. These factors include natural factors (net primary productivity, road accessibility, slope and relief amplitude) and social factors (household family structures, economic development and government policies). Ultimately, this study scientifically predicts the future farmland use change trend in the next 30 years. The simulation results show that the number of abandoned and sublet farmland plots has a gradually increasing trend, and the number of non-farming households and pure-outworking households has a remarkable increasing trend, whereas the number of part-farming households and pure-farming households has a decreasing trend. Household livelihood sustainability in the study area is confronted with increasing pressure, and household non-farm employment has an increasing trend, while regional appropriate-scale agricultural management is maintained. The research results establish the theoretical foundation and a basic method for developing sustainable farmland use management that can meet the willingness of households and guarantee grain and ecological security.
Xuehong Bai; Huimin Yan; Lihu Pan; He Qing Huang. Multi-Agent Modeling and Simulation of Farmland Use Change in a Farming–Pastoral Zone: A Case Study of Qianjingou Town in Inner Mongolia, China. Sustainability 2015, 7, 14802 -14833.
AMA StyleXuehong Bai, Huimin Yan, Lihu Pan, He Qing Huang. Multi-Agent Modeling and Simulation of Farmland Use Change in a Farming–Pastoral Zone: A Case Study of Qianjingou Town in Inner Mongolia, China. Sustainability. 2015; 7 (11):14802-14833.
Chicago/Turabian StyleXuehong Bai; Huimin Yan; Lihu Pan; He Qing Huang. 2015. "Multi-Agent Modeling and Simulation of Farmland Use Change in a Farming–Pastoral Zone: A Case Study of Qianjingou Town in Inner Mongolia, China." Sustainability 7, no. 11: 14802-14833.
While land serves numerous societal functions and contributes to sustainable development, it is often unclear how these functions are affected by political decisions and common drivers of land use change, such as economic development, climate change and demographic change. This study evaluates alternative land use scenarios in reference to a rural region of Inner Mongolia Autonomous Region (China), where various processes and decisions have historically triggered unsustainable development. The scientifically tested “Framework for Participatory Impact Assessment (FoPIA)” method is developed further to address specific features of the case study region, and its function as a knowledge-brokerage (KB) tool is evaluated. Three scenarios are developed and analysed in expert workshops. “Land intensification: Agriculture” and “Land intensification: Mining” scenarios are found to have mainly negative environmental and social effects and positive economic impacts, while the “Environmental conservation and tourism” scenario is found to more positively affect all three sustainability dimensions. Assessments of methodological phases show that the FoPIA primarily serves to establish the KB process and that the framework particularly benefits from early examinations of scientific results by policy makers.
Hannes J. König; Aranka Podhora; Lin Zhen; Katharina Helming; Huimin Yan; Bingzhen Du; Jost Wübbeke; Chao Wang; Julie Klinger; Cheng Chen; Sandra Uthes. Knowledge Brokerage for Impact Assessment of Land Use Scenarios in Inner Mongolia, China: Extending and Testing the FoPIA Approach. Sustainability 2015, 7, 5027 -5049.
AMA StyleHannes J. König, Aranka Podhora, Lin Zhen, Katharina Helming, Huimin Yan, Bingzhen Du, Jost Wübbeke, Chao Wang, Julie Klinger, Cheng Chen, Sandra Uthes. Knowledge Brokerage for Impact Assessment of Land Use Scenarios in Inner Mongolia, China: Extending and Testing the FoPIA Approach. Sustainability. 2015; 7 (5):5027-5049.
Chicago/Turabian StyleHannes J. König; Aranka Podhora; Lin Zhen; Katharina Helming; Huimin Yan; Bingzhen Du; Jost Wübbeke; Chao Wang; Julie Klinger; Cheng Chen; Sandra Uthes. 2015. "Knowledge Brokerage for Impact Assessment of Land Use Scenarios in Inner Mongolia, China: Extending and Testing the FoPIA Approach." Sustainability 7, no. 5: 5027-5049.
Developments in hyperspectral remote sensing techniques during the last decade have enabled the use of narrowband indices to evaluate the role of forest ecosystem variables in estimating carbon (C) fluxes. In this study, narrowband bio-indicators derived from EO-1 Hyperion data were investigated to determine whether they could capture the temporal variation and estimate the spatial variability of forest C fluxes derived from eddy covariance tower data. Nineteen indices were divided into four categories of optical indices: broadband, chlorophyll, red edge, and light use efficiency. Correlation tests were performed between the selected vegetation indices, gross primary production (GPP), and ecosystem respiration (Re). Among the 19 indices, five narrowband indices (Chlorophyll Index RedEdge 710, scaled photochemical reflectance index (SPRI)*enhanced vegetation index (EVI), SPRI*normalized difference vegetation index (NDVI), MCARI/OSAVI[705, 750] and the Vogelmann Index), and one broad band index (EVI) had R-squared values with a good fit for GPP and Re. The SPRI*NDVI has the highest significant coefficients of determination with GPP and Re (R2 = 0.86 and 0.89, p < 0.0001, respectively). SPRI*NDVI was used in atmospheric inverse modeling at regional scales for the estimation of C fluxes. We compared the GPP spatial patterns inversed from our model with corresponding results from the Vegetation Photosynthesis Model (VPM), the Boreal Ecosystems Productivity Simulator model, and MODIS MOD17A2 products. The inversed GPP spatial patterns from our model of SPRI*NDVI had good agreement with the output from the VPM model. The normalized difference nitrogen index was well correlated with measured C net ecosystem exchange. Our findings indicated that narrowband bio-indicators based on EO-1 Hyperion images could be used to predict regional C flux variations for Northeastern China’s temperate broad-leaved Korean pine forest ecosystems.
Quanzhou Yu; Shaoqiang Wang; Robert A. Mickler; Kun Huang; Lei Zhou; Huimin Yan; Diecong Chen; Shijie Han. Narrowband Bio-Indicator Monitoring of Temperate Forest Carbon Fluxes in Northeastern China. Remote Sensing 2014, 6, 8986 -9013.
AMA StyleQuanzhou Yu, Shaoqiang Wang, Robert A. Mickler, Kun Huang, Lei Zhou, Huimin Yan, Diecong Chen, Shijie Han. Narrowband Bio-Indicator Monitoring of Temperate Forest Carbon Fluxes in Northeastern China. Remote Sensing. 2014; 6 (9):8986-9013.
Chicago/Turabian StyleQuanzhou Yu; Shaoqiang Wang; Robert A. Mickler; Kun Huang; Lei Zhou; Huimin Yan; Diecong Chen; Shijie Han. 2014. "Narrowband Bio-Indicator Monitoring of Temperate Forest Carbon Fluxes in Northeastern China." Remote Sensing 6, no. 9: 8986-9013.
Double- and triple-cropping in a year have played a very important role in meeting the rising need for food in China. However, the intensified agricultural practices have significantly altered biogeochemical cycles and soil quality. Understanding and mapping cropping intensity in China’s agricultural systems are therefore necessary to better estimate carbon, nitrogen and water fluxes within agro-ecosystems on the national scale. In this study, we investigated the spatial pattern of crop calendar and multiple cropping rotations in China using phenological records from 394 agro-meteorological stations (AMSs) across China. The results from the analysis of in situ field observations were used to develop a new algorithm that identifies the spatial distribution of multiple cropping in China from moderate resolution imaging spectroradiometer (MODIS) time series data with a 500 m spatial resolution and an 8-day temporal resolution. According to the MODIS-derived multiple cropping distribution in 2002, the proportion of cropland cultivated with multiple crops reached 34% in China. Double-cropping accounted for approximately 94.6% and triple-cropping for 5.4%. The results demonstrat that MODIS EVI (Enhanced Vegetation Index) time series data have the capability and potential to delineate the dynamics of double- and triple-cropping practices. The resultant multiple cropping map could be used to evaluate the impacts of agricultural intensification on biogeochemical cycles.
Huimin Yan; Xiangming Xiao; Heqing Huang; Jiyuan Liu; Jingqing Chen; Xuehong Bai. Multiple cropping intensity in China derived from agro-meteorological observations and MODIS data. Chinese Geographical Science 2013, 24, 205 -219.
AMA StyleHuimin Yan, Xiangming Xiao, Heqing Huang, Jiyuan Liu, Jingqing Chen, Xuehong Bai. Multiple cropping intensity in China derived from agro-meteorological observations and MODIS data. Chinese Geographical Science. 2013; 24 (2):205-219.
Chicago/Turabian StyleHuimin Yan; Xiangming Xiao; Heqing Huang; Jiyuan Liu; Jingqing Chen; Xuehong Bai. 2013. "Multiple cropping intensity in China derived from agro-meteorological observations and MODIS data." Chinese Geographical Science 24, no. 2: 205-219.
As they are products of glacier movement, the water body composition and water quality attributes of glacial lakes have distinct characteristics compared with inland lakes. Although satellite remote sensing provides an effective approach to monitor water quality, lack of in-situ measurement data on the status and environment surrounding glacial lakes presents a major constraint in relating satellite data to water quality indicators. This study presents findings of a preliminary investigation into water quality attributes of 3 glacial lakes in the Mount Qomolangma region. Suspended particulate matter (SPM), light absorption attributes of phytoplankton, nonalgal particles (NAP), and colored dissolved organic matter (CDOM) were measured. The suspended substance concentration varies markedly from 0–320 mg/L. This is considered to reflect differing stages of lake development. The chlorophyll concentration is much lower than that found for inland lakes, as landscapes that surround these high altitude lakes have almost no vegetation growth. The phytoplankton and CDOM concentration depend on long-term stability of lake slopes. Given the lack of exogenous and endogenous inputs in the Qomolangma region, CDOM in glacial lakes is significantly lower than in inland lakes. These preliminary findings could support efforts to appraise estimates of water quality parameters using remotely sensed images.
Huimin Yan; Zhijun Yao; Heqing Huang; Dong Jiang; Xiaohui Dong; Rui Duan; Yili Zhang. Water quality and light absorption attributes of glacial lakes in Mount Qomolangma region. Journal of Geographical Sciences 2013, 23, 860 -870.
AMA StyleHuimin Yan, Zhijun Yao, Heqing Huang, Dong Jiang, Xiaohui Dong, Rui Duan, Yili Zhang. Water quality and light absorption attributes of glacial lakes in Mount Qomolangma region. Journal of Geographical Sciences. 2013; 23 (5):860-870.
Chicago/Turabian StyleHuimin Yan; Zhijun Yao; Heqing Huang; Dong Jiang; Xiaohui Dong; Rui Duan; Yili Zhang. 2013. "Water quality and light absorption attributes of glacial lakes in Mount Qomolangma region." Journal of Geographical Sciences 23, no. 5: 860-870.
Accurate and spatially explicit monitoring of gross primary productivity of agricultural ecosystems at a large scale is of great significance to assessment of crop conditions and agricultural production, and is necessary for understanding the carbon balance of the terrestrial biosphere. Identifying crop intensity (including multiple cropping and crop calendar) dynamics and assigning appropriate light use efficiency to C3 and C4 crops could substantially improve our ability to model and evaluate the seasonal dynamics of carbon flux in intensified agricultural ecosystems. In this paper, we have analyzed temporal dynamics of vegetation indices and phenological characteristics in the winter-wheat and maize double cropping system using multi-year satellite images from the moderate resolution imaging spectral radiometer (MODIS) and in situ observation of key crop phenological transition dates. The multiple cropping and crop calendar information were incorporated into simulations of the satellite-based vegetation photosynthesis model (VPM). Canopy-level maximum light use efficiency, a key parameter in the satellite-based VPM model, was estimated for both winter wheat (C3) and maize (C4) based on the observed CO2 flux data from an eddy flux tower site in a winter wheat-maize double cropping agro-ecosystem in the Huang-Huai-Hai plain, China. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux tower data. These results demonstrate the potential of the satellite-driven VPM model for scaling-up GPP estimation of intensified agricultural ecosystems, which is relevant to food production and security.
Huimin Yan; Yuling Fu; Xiangming Xiao; He Qing Huang; Honglin He; Laura Ediger. Modeling gross primary productivity for winter wheat–maize double cropping system using MODIS time series and CO2 eddy flux tower data. Agriculture, Ecosystems & Environment 2009, 129, 391 -400.
AMA StyleHuimin Yan, Yuling Fu, Xiangming Xiao, He Qing Huang, Honglin He, Laura Ediger. Modeling gross primary productivity for winter wheat–maize double cropping system using MODIS time series and CO2 eddy flux tower data. Agriculture, Ecosystems & Environment. 2009; 129 (4):391-400.
Chicago/Turabian StyleHuimin Yan; Yuling Fu; Xiangming Xiao; He Qing Huang; Honglin He; Laura Ediger. 2009. "Modeling gross primary productivity for winter wheat–maize double cropping system using MODIS time series and CO2 eddy flux tower data." Agriculture, Ecosystems & Environment 129, no. 4: 391-400.