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Dr. Yunfeng Hu
Institute of geographic sciences and natural resources research, chinese academy of sciences

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0 Physical Geography
0 Regional Planning
0 Sustainable Development
0 ecosystem assessment
0 Remote sensing & GIS applications

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Journal article
Published: 29 July 2021 in Science of The Total Environment
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The forest root-shoot ratio (R/S), i.e., the ratio of belowground to aboveground biomass at the stand level, is widely used in global and regional forest carbon stock estimation and in modeling of the forest carbon cycle. Despite recent advances in understanding forest R/S variations at the individual-tree level, spatial patterns of stand-level forest R/S ratio across the globe and their driving factors remain relatively unknown. Here, we compiled and analyzed an extensive dataset from 873 forest sites worldwide, analyzed and quantified the effects of major environmental and forest growth-related variables on the stand-level R/S ratio. Based on this analysis, we further mapped the spatial pattern of the global forest R/S ratio. Our results show that, globally, variations on the stand-level forest R/S ratio are largely affected by canopy height, latitude, climatic water deficit, forest type and regeneration method, which collectively explain 37% of the variations in R/S ratio. In addition, our results suggest significant intercontinental and national variations in forest R/S ratio. At the continental scale, forest R/S ratio is highest in Oceania and lowest in South America. At the national scale, Australia has the highest forest R/S ratio while Russia has the lowest values. The forest R/S ratio is generally lower in moist tropical regions, but increases when moving to the extra-tropics when seasonality in precipitation increases. The R/S ratio in temperate and boreal regions shows prominent spatial features regulated by forest species composition and regeneration method. We conclude that future changes in environmental, biotic and anthropogenic factors, such as increased climatic water deficit and forest management, might influence the forest R/S ratio, with implications for the global and regional land carbon cycle.

ACS Style

Junzhi Ye; Chao Yue; Yunfeng Hu; Hui Ma. Spatial patterns of global-scale forest root-shoot ratio and their controlling factors. Science of The Total Environment 2021, 800, 149251 .

AMA Style

Junzhi Ye, Chao Yue, Yunfeng Hu, Hui Ma. Spatial patterns of global-scale forest root-shoot ratio and their controlling factors. Science of The Total Environment. 2021; 800 ():149251.

Chicago/Turabian Style

Junzhi Ye; Chao Yue; Yunfeng Hu; Hui Ma. 2021. "Spatial patterns of global-scale forest root-shoot ratio and their controlling factors." Science of The Total Environment 800, no. : 149251.

Journal article
Published: 28 July 2021 in ISPRS International Journal of Geo-Information
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Point of interest (POI) data can provide a clear spatial location and accurate attributes for geoscience research. The traditional assessment of Beautiful China construction (BCC) has relied on statistical materials, which have shortcomings in terms of timeliness, authenticity, efficiency, and accuracy. Referring to the theoretical framework of the Zhongke Beauty Index, we built an evaluation index system and technical process based on POI data. In terms of the Inner Mongolia Autonomous Region (IMAR), 5.09 million POIs were collected using the web crawler technique, and the Beautiful Inner Mongolia construction evaluation and analysis were performed. The results show the following: (1) POI data can be used to establish an evaluation index system for the construction of Beautiful Inner Mongolia on the county scale; in the dimensions of industrial development, social harmony, and institutional improvement, it shows especially good application prospects. (2) The Beautiful Inner Mongolia index in 2020 was 0.22. Among the five dimensions, the industrial development index was the highest, while the cultural heritage index was the lowest. We found significant spatial differences in the dimensions of cultural heritage as well as social harmony. (3) The areas in the IMAR with a low-level construction were mostly industrial and mining areas, agricultural counties, and other economically developing areas, among which the Baiyunebo mining area and Xianghuangqi and Shiguai areas had the lowest comprehensive beauty index values. (4) We also found large numerical disparities in the level of Beautiful Inner Mongolia construction between municipal districts and banners/counties, and the ranking of each region was affected by the population and coverage areas of administrative units. After verification, we found an overall good consistency between the evaluation indexes proposed in this paper and a previous study. Therefore, this paper provides a new perspective and an effective method for the application of Internet big data in economic and social evaluation work.

ACS Style

Yuting Liang; Yunfeng Hu. Beautiful China Construction Evaluation Method Based on POIs: Case Study of the Inner Mongolia Autonomous Region. ISPRS International Journal of Geo-Information 2021, 10, 508 .

AMA Style

Yuting Liang, Yunfeng Hu. Beautiful China Construction Evaluation Method Based on POIs: Case Study of the Inner Mongolia Autonomous Region. ISPRS International Journal of Geo-Information. 2021; 10 (8):508.

Chicago/Turabian Style

Yuting Liang; Yunfeng Hu. 2021. "Beautiful China Construction Evaluation Method Based on POIs: Case Study of the Inner Mongolia Autonomous Region." ISPRS International Journal of Geo-Information 10, no. 8: 508.

Journal article
Published: 15 July 2021 in Environmental and Sustainability Indicators
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Biocapacity stability is an important foundation for regional ecosystem stability, ecological service security, and development sustainability. This paper aimed to study the spatial pattern, evolution characteristics, and future trend of biocapacity in Xilingol. Based on GlobeLand30 data in 2000, 2010, and 2020, combined with logistic regression method, CA-Markov model, and biocapacity model, the authors simulated the land use scenario and distribution of biocapacity in 2030. The spatial distribution pattern and spatiotemporal evolution process of regional biocapacity were analyzed in detail. The results showed that: (1) Biocapacity was jointly restricted by land use type, yield, and equivalence factor. The high values were mainly distributed in the farmland areas of the south, and the meadow grasslands, hills, mountains, hidden forests of the east; the median values were mainly distributed in the typical grasslands of the east, the central and the south; the low values were mainly distributed in the desert grasslands of the central and the west; the zero values were mainly distributed in the Gobi and the deserts of the northwest. (2) From 2000 to 2020, the regional biocapacity increased from 9.137 × 106 gha to 9.289 × 106 gha, with an increase of 1.67%. It was expected that from 2020 to 2030, with the continued reduction of farmland, the increase of forest and grassland, and the improvement of grassland coverage, the regional biocapacity will continue to increase by 0.70%, reaching 9.354 × 106 gha.

ACS Style

Hao Wang; Yunfeng Hu; Yuting Liang. Simulation and spatiotemporal evolution analysis of biocapacity in Xilingol based on CA-Markov land simulation. Environmental and Sustainability Indicators 2021, 11, 100136 .

AMA Style

Hao Wang, Yunfeng Hu, Yuting Liang. Simulation and spatiotemporal evolution analysis of biocapacity in Xilingol based on CA-Markov land simulation. Environmental and Sustainability Indicators. 2021; 11 ():100136.

Chicago/Turabian Style

Hao Wang; Yunfeng Hu; Yuting Liang. 2021. "Simulation and spatiotemporal evolution analysis of biocapacity in Xilingol based on CA-Markov land simulation." Environmental and Sustainability Indicators 11, no. : 100136.

Journal article
Published: 24 May 2021 in Sustainability
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Biocapacity evaluation is an important part of sustainable development research, but quantitative and spatial evaluation and future scenario analysis still have model and methodological difficulties. Based on the high-resolution Globeland30 dataset, the authors analyzed the characteristics of land use/cover changes of the Loess Plateau in Northern Shaanxi from 2000 to 2020. Then, comprehensively considering the driving factors of social development, topography, climatic conditions, and spatial distance, the logistic regression method and the CA–Markov model were used to simulate the land use scenario in 2030. Finally, the biocapacity model was used to describe the spatial distribution and spatial-temporal evolution of the regional biocapacity in detail. The results showed the following: (1) Biocapacity was jointly restricted by land use types, yield factors, and equivalence factors. The high values were mainly distributed in the riparian areas of the central and eastern regions, the ridges and valleys of the central and western regions, and the farmland patches of the southern valleys; the median values were mainly distributed in the forest of the southern mountains; the low values were mainly distributed in the grassland and unused land in the hilly and gully areas of the central and northern regions. (2) The biocapacity of Loess Plateau in Northern Shaanxi increased by 9.98% from 2000 to 2010, and decreased by 4.14% from 2010 to 2020, and the total amount remained stable. It is predicted that by 2030, the regional biocapacity will continue to increase by 0.03%, reaching 16.52 × 106 gha.

ACS Style

Hao Wang; Yunfeng Hu. Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model. Sustainability 2021, 13, 5901 .

AMA Style

Hao Wang, Yunfeng Hu. Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model. Sustainability. 2021; 13 (11):5901.

Chicago/Turabian Style

Hao Wang; Yunfeng Hu. 2021. "Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model." Sustainability 13, no. 11: 5901.

Journal article
Published: 12 October 2020 in Sustainability
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Soil erosion and restoration affect the structure and function of ecosystems and society, and have attracted worldwide attention. Changes in runoff and sediment transport after restoration practices in China’s Loess Plateau have been widely studied and many valuable results have been reported. However, this research was mainly conducted in large watersheds, and quantified the effects of restoration practices through the restoration period. In this study, we compared two adjacent watersheds (one restored and the other natural) in a hill and gully region of China’s Loess Plateau to reveal the impacts of restoration practices. We collected annual rainfall, runoff, and sediment transport data from 1988 to 2018, then investigated temporal variation of runoff and sediment transport to examine their relationships with rainfall. We also calculated the retention rate of soil and water under the restoration practices. The restored watershed showed a significantly decreased sediment modulus (the amount per unit area); the natural watershed showed no significant change. In addition, the restored watershed had lower runoff and sediment modulus values than the natural watershed, with greater effectiveness as rainfall increased. Revegetation and terrace construction contributed more to the retention of soil and water (65.6 and 69.7%, respectively) than check dams (<10%). These results improve our understanding of the effects of restoration practices, and provide guidance on ways to preserve soil and water through restoration in a small watershed in the Loess Plateau.

ACS Style

Qi Luo; Lin Zhen; Yunfeng Hu. The Effects of Restoration Practices on a Small Watershed in China’s Loess Plateau: A Case Study of the Qiaozigou Watershed. Sustainability 2020, 12, 8376 .

AMA Style

Qi Luo, Lin Zhen, Yunfeng Hu. The Effects of Restoration Practices on a Small Watershed in China’s Loess Plateau: A Case Study of the Qiaozigou Watershed. Sustainability. 2020; 12 (20):8376.

Chicago/Turabian Style

Qi Luo; Lin Zhen; Yunfeng Hu. 2020. "The Effects of Restoration Practices on a Small Watershed in China’s Loess Plateau: A Case Study of the Qiaozigou Watershed." Sustainability 12, no. 20: 8376.

Journal article
Published: 30 September 2020 in Scientific Reports
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Ecological land is a type of land that has considerable ecological value. Understanding the evolution of urban ecological land in Zhuhai, China, holds great significance for revealing the evolution of ecological land in the Dawan District of southern China. We explored the temporal and spatial variation in urban ecological land in Zhuhai using the transformation matrix, equivalent ecological land, landscape index and ecological land center of gravity migration methods. Multivariate logistic regression was used to analyze the mechanism of ecological land change, and a transition probability map of the ecological land in the study area was drawn. The results showed the following. (1) From 1991 to 2018, the area of ecological land in Zhuhai city continuously decreased, with a reduction in area of 274.8 km2, or 32.3%. Sharp changes mainly occurred from 1991 to 2000. (2) The ecological land in the study area has gradually become fragmented, and the degree of landscape heterogeneity has increased. Affected by the expansion of the outer edge of the city to the southwest and the construction of ecological land within the city, the center of gravity of the ecological land has shifted to the northeast by 1346 m. (3) The elevation, slope, distance from built-up land and growth rate of built-up land are important factors influencing the transformation of ecological land. In the future, rivers and shallow coastal waters, tidal flats, and grasslands in the study area have the highest probability of transformation. The Jinwan District and Xiangzhou District will face severe ecological land protection pressure. The method of spatial–temporal analysis of urban ecological land developed in this paper can be applied in similar studies on other cities, and the results obtained for Zhuhai, China, have reference value for future urban planning and ecological protection work.

ACS Style

Yunfeng Hu; Yunzhi Zhang. Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China. Scientific Reports 2020, 10, 1 -15.

AMA Style

Yunfeng Hu, Yunzhi Zhang. Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China. Scientific Reports. 2020; 10 (1):1-15.

Chicago/Turabian Style

Yunfeng Hu; Yunzhi Zhang. 2020. "Spatial–temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China." Scientific Reports 10, no. 1: 1-15.

Journal article
Published: 16 June 2020 in Sustainability
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Nighttime light images record the brightness of the Earth surface, indicating the scope and intensity of human activities. However, there are few studies on the long-term changes in global nighttime lights. In this paper, the authors constructed a long time series (1992~2017) nighttime light dataset combining the Defense Meteorological Satellites Program/Operational Linescan System (DMSP-OLS) and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data sources and observed the following: (1) Global nighttime lights have become brighter. The global nighttime brightness in 2017 was 2.2 times that of 1992. Approximately 40.3% of the lighted area was significantly brightened, and an area of 1.3 × 107 km2 transitioned from an unlighted area to a lighted area. (2) Approximately 85.7% of the nighttime light increase occurred in the low-brightness zone (LBZ). Therefore, global brightness has become more uniform than before. (3) China, India, and the United States have led the global lighting trend. The increase in Chinese nighttime lights is the largest, with an average annual growth of 6.48%, followed by the light growth in India, while the United States has the largest brightened area. (4) The changes in nighttime lights in developing countries (e.g., China and India) are closely and positively related to their electricity consumption, industrial added value and gross domestic product (GDP). The shift of the LBZ center from Asia to Africa indicates the intercontinental transition of poverty.

ACS Style

Yunfeng Hu; Yunzhi Zhang. Global Nighttime Light Change from 1992 to 2017: Brighter and More Uniform. Sustainability 2020, 12, 4905 .

AMA Style

Yunfeng Hu, Yunzhi Zhang. Global Nighttime Light Change from 1992 to 2017: Brighter and More Uniform. Sustainability. 2020; 12 (12):4905.

Chicago/Turabian Style

Yunfeng Hu; Yunzhi Zhang. 2020. "Global Nighttime Light Change from 1992 to 2017: Brighter and More Uniform." Sustainability 12, no. 12: 4905.

Journal article
Published: 22 May 2020 in Journal of Arid Environments
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Desertification in Kazakhstan affects the country's environment, agriculture and animal husbandry. It is critical to quickly and accurately identify the locations of desertification land and grasp the main causes of desertification in different states in Kazakhstan. This paper builds a new technical framework for desertification identification. Through a comprehensive analysis of desertification sensitivity, long-term trends and stability of net primary productivity (NPP), the authors determined the spatial distribution of land desertification in Kazakhstan and further analyzed the possible driving factors of desertification. The results showed that (1) approximately 76.1% of Kazakhstan land is considered desertification sensitive areas with moderate and higher sensitivity; (2) the area of desertification land in Kazakhstan is approximately 1.04 × 105 km2, accounting for 3.8% of the total land area, which is mainly distributed across seven states in western, northwestern and southwestern Kazakhstan; and (3) in the four main desertification states (West Kazakhstan, Aktobe, Mangystau and Atyrau), the climate warming and drying trends are significant. Large-scale and intensive human activities in agriculture and animal husbandry in the two main desertification regions in northern Kazakhstan have promoted land desertification to some extent. Targeted agricultural and industrial regulatory actions should be taken to prevent and control land desertification. The desertification mapping technical framework established in this paper can be used in other parts of the world. The conclusions about the driving factors have reference value for the government authorities of the states of Kazakhstan.

ACS Style

Yunfeng Hu; Yueqi Han; Yunzhi Zhang. Land desertification and its influencing factors in Kazakhstan. Journal of Arid Environments 2020, 180, 104203 .

AMA Style

Yunfeng Hu, Yueqi Han, Yunzhi Zhang. Land desertification and its influencing factors in Kazakhstan. Journal of Arid Environments. 2020; 180 ():104203.

Chicago/Turabian Style

Yunfeng Hu; Yueqi Han; Yunzhi Zhang. 2020. "Land desertification and its influencing factors in Kazakhstan." Journal of Arid Environments 180, no. : 104203.

Journal article
Published: 21 May 2020 in Journal of Cleaner Production
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The analysis of historical changes, exploration of driving forces, and understanding of future changes in ecological land can provide a scientific basis for sustainable development in rapidly urbanizing areas. In this paper, with the support of GIS spatial analysis, the landscape index, the Moran’s index and multiple logistic regression models, we constructed an integrated ecological land analysis framework, which included historical trajectories, driving factors and future simulation projections. A comprehensive analysis was carried out in the case city of Guangzhou, China, and the results showed the following: (1) In the past 25 years, the ecological land of Guangzhou has shown a decreasing trend, with its area decreasing by 59.7 km2. Dramatic changes occurred between 2000 and 2010. (2) The quality of the urban ecological environment has two opposite trends at the same time: improvement and degeneration. The agglomeration of ecological land is weakened, heterogeneity is enhanced, and the diversity and uniformity of landscape are slightly reduced. (3) Altitude, GDP per unit area, and distance to the nearest road were the main driving factors for ecological land changes. To alleviate the pressure of urban expansion on ecological land, the downtown, Huangpu and Nansha districts must pay more attention to improving the level of intensive land use in the future. The study results have reference value for the Department of Guangzhou Urban Planning and offer an analysis framework for similar studies.

ACS Style

Yunzhi Zhang; Yunfeng Hu; Dafang Zhuang. A highly integrated, expansible, and comprehensive analytical framework for urban ecological land: A case study in Guangzhou, China. Journal of Cleaner Production 2020, 268, 122360 .

AMA Style

Yunzhi Zhang, Yunfeng Hu, Dafang Zhuang. A highly integrated, expansible, and comprehensive analytical framework for urban ecological land: A case study in Guangzhou, China. Journal of Cleaner Production. 2020; 268 ():122360.

Chicago/Turabian Style

Yunzhi Zhang; Yunfeng Hu; Dafang Zhuang. 2020. "A highly integrated, expansible, and comprehensive analytical framework for urban ecological land: A case study in Guangzhou, China." Journal of Cleaner Production 268, no. : 122360.

Journal article
Published: 29 April 2020 in Journal of Environmental Management
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Understanding how complex urban factors affect the Urban Heat Island (UHI) is crucial for assessing the impacts of urban planning and environmental management on the thermal environment. This paper investigates the relationships between two-dimensional (2D) and three-dimensional (3D) factors and land surface temperatures (LST) within the Olympic Area of Beijing in different seasons, using the boosted regression tree (BRT) model. The BRT model captures the specific contributions of each urban factor to LST in each season and across a continuum of magnitudes for this factor. The results show that these relationships are complex and highly nonlinear. The four most common dominant factors are the Normalized Difference Built-up Index (NDBI), the Normalized Difference Vegetation Index (NDVI), a gravity index for parks (GPI), and average building height (BH). The most important factor in spring is NDBI, with a 45.5% contribution rate. In the other seasons, NDVI is the dominant factor, with contributions of 40% in summer, 21% in autumn, and 19% in winter. NDVI has an overall negative impact on LST in spring and summer, with a quadratic nonlinear decreasing curve, but a positive one in autumn and winter. The 2D land-use variables are most strongly related to LST in summer and spring, but 3D building-related variables have stronger impacts in colder weather. The Sky View Factor (SVF), a 3D measure of urban morphology, has also strong impacts in summer and winter. Both a building-based and a DSM-based SVFs are computed. The latter accounts for buildings, bridges, and trees. In contrast to a building-based SVF, the DSM-based SVF reduces LST when it varies between 0 and 0.75, reflecting the effects of high-density tree canopies that increase shades and evapotranspiration while blocking sky view. The marginal effect curves produced by the BRT are often characterized by thresholds. For instance, the maximal NDVI effect in summer takes place when NDVI = 0.7, suggesting that a very intense green coverage is not necessary to achieve maximal thermal results. Implications for urban planning and environmental management are outlined, including the increased use of evergreen trees that provide thermal benefits in both summer and winter.

ACS Style

Yunfeng Hu; Zhaoxin Dai; Jean-Michel Guldmann. Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach. Journal of Environmental Management 2020, 266, 110424 .

AMA Style

Yunfeng Hu, Zhaoxin Dai, Jean-Michel Guldmann. Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach. Journal of Environmental Management. 2020; 266 ():110424.

Chicago/Turabian Style

Yunfeng Hu; Zhaoxin Dai; Jean-Michel Guldmann. 2020. "Modeling the impact of 2D/3D urban indicators on the urban heat island over different seasons: A boosted regression tree approach." Journal of Environmental Management 266, no. : 110424.

Journal article
Published: 13 March 2020 in Sustainability
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Urban blue and green space is a key element supporting the normal operation of urban landscape ecosystems and guaranteeing and improving people's lives. In this paper, 97.1k photos of Beijing were captured by using web crawler technology, and the blue sky and green vegetation objects in the photos were extracted by using the Image Cascade Network (ICNet) neural network model. We analyzed the distribution characteristics of the blue–green space area proportion index and its relationships with the background economic and social factors. The results showed the following. (1) The spatial distribution of Beijing's blue–green space area proportion index showed a pattern of being higher in the west and lower in the middle and east. (2) There was a positive correlation between the satellite remote sensing normalized difference vegetation index (NDVI) and the proportion index of green space area, but the fitting degree of geospatial weighted regression decreased with an increasing analysis scale. (3) There were differences in the relationship between the housing prices in different regions and the proportion index of blue–green space, but the spatial fitting degree of the two increased with the increase of study scale. (4) There was a negative correlation between the proportion index of blue–green space and population density, and the low-population areas per unit blue–green space were mainly distributed in the south of the city and the urban fringe areas beyond the Third Ring Road. The urban blue–green space analysis that was constructed by this study provides new aspect for urban landscape ecology study, and the results proposed here also provide support for government decision-makers to optimize urban ecological layouts.

ACS Style

Haoying Wang; Yunfeng Hu; Li Tang; Qi Zhuo. Distribution of Urban Blue and Green Space in Beijing and Its Influence Factors. Sustainability 2020, 12, 2252 .

AMA Style

Haoying Wang, Yunfeng Hu, Li Tang, Qi Zhuo. Distribution of Urban Blue and Green Space in Beijing and Its Influence Factors. Sustainability. 2020; 12 (6):2252.

Chicago/Turabian Style

Haoying Wang; Yunfeng Hu; Li Tang; Qi Zhuo. 2020. "Distribution of Urban Blue and Green Space in Beijing and Its Influence Factors." Sustainability 12, no. 6: 2252.

Journal article
Published: 01 January 2020 in Remote Sensing
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The spatial distribution and dynamic changes of the forests in Primorsky Krai, Russia, are of great significance for regional ecological security and sustainable economic and societal development. With the support of the Google Earth Engine cloud computing platform, we first synthesized yearly Landsat surface reflectance images of the best quality of the research area and then used the random forest method to calculate the forest classification probability of the study area year by year from 1998 to 2015. Furthermore, we used a time–series segmentation algorithm to perform temporal trajectory segmentation for forest classification probability estimation, and determined the spatial and temporal distribution characteristics and change laws of the forest. We extended the existing algorithms and parameters of forest classification probability trajectory analysis, achieving a high overall accuracy (86.2%) in forest change detection in the study area. The extended method can accurately capture the time node information of the changes. In the present research we observed: (1) that from 1998 to 2015, the forest area of the whole district showed a net loss state, with a loss area of 0.56 × 106 ha, of which the cumulative forest disturbance area reached 1.12 × 106 ha, and the cumulative forest recovery area reached 0.55 × 106 ha; and (2) that more than 90% of the forest change occurred in areas with a slope of less than 18°, at a distance of less than 20 km from settlements, and at a distance of less than 10 km from roads. The forest disturbance monitoring results are consistent with the changes in official statistical results over time, but there was a 20% overestimation. The technical method we extended in this study can be used as a reference for large–scale and high–precision dynamic monitoring of the forests in Russia’s Far East and other regions of the world; it also provides a basis for estimating illegal timber harvesting and determining the appropriate amount of forest harvested.

ACS Style

Yang Hu; Yunfeng Hu. Detecting Forest Disturbance and Recovery in Primorsky Krai, Russia, Using Annual Landsat Time Series and Multi–Source Land Cover Products. Remote Sensing 2020, 12, 129 .

AMA Style

Yang Hu, Yunfeng Hu. Detecting Forest Disturbance and Recovery in Primorsky Krai, Russia, Using Annual Landsat Time Series and Multi–Source Land Cover Products. Remote Sensing. 2020; 12 (1):129.

Chicago/Turabian Style

Yang Hu; Yunfeng Hu. 2020. "Detecting Forest Disturbance and Recovery in Primorsky Krai, Russia, Using Annual Landsat Time Series and Multi–Source Land Cover Products." Remote Sensing 12, no. 1: 129.

Journal article
Published: 07 December 2019 in Environmental Development
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More water yield and less soil erosion are crucial to the sustainable development of the Loess Plateau and Yellow River basin. Different land use policies and climate change scenarios may have great implications on water yield and soil erosion. In this paper, four land development scenarios and two climate change scenarios are designed and applied to the Shaanxi-Gansu Loess Plateau. The InVEST model is applied to quantitatively evaluate the water yield and soil erosion modulus in 2030. It showed: (1) Arable land and grassland is always the dominant land types in the Shaanxi-Gansu Loess Plateau and cover more than 76% of the area. The business-as-usual and ecological protection priority scenarios may lead to increases in the local food security risks, with 1.9% and 1.4% gaps in the total food requirements. (2) Under the RCP2.6 scenario, the annual water yield and annual soil erosion amount increased by more than 63% (2.84*109 m3) and 22% (96.0*106 t), respectively. Under the RCP4.5 scenario, the annual water yield and annual soil erosion decreased by more than 48% (2.17*109 m3) and 26% (114.3*106 t), respectively. (3) The influence of climate change on water yield and soil erosion is far greater than that of land use change. The contribution of climate change to the water yield changes is 92.8–99.6%, while the contribution of land use change is 0.4–7.2%. The contribution rate of climate change to soil erosion changes is 84.8–91.1%, while the contribution rate of land use change is 8.9–15.2%. The key ecological services, such as food production, water yield, soil and water conservation, should be carefully weighed and coordinated in the Loess Plateau and areas with limited land surfaces, such as small island development states.

ACS Style

Yunfeng Hu; Min Gao; Batunacun. Evaluations of water yield and soil erosion in the Shaanxi-Gansu Loess Plateau under different land use and climate change scenarios. Environmental Development 2019, 34, 100488 .

AMA Style

Yunfeng Hu, Min Gao, Batunacun. Evaluations of water yield and soil erosion in the Shaanxi-Gansu Loess Plateau under different land use and climate change scenarios. Environmental Development. 2019; 34 ():100488.

Chicago/Turabian Style

Yunfeng Hu; Min Gao; Batunacun. 2019. "Evaluations of water yield and soil erosion in the Shaanxi-Gansu Loess Plateau under different land use and climate change scenarios." Environmental Development 34, no. : 100488.

Journal article
Published: 01 November 2019 in Journal of Resources and Ecology
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Since the 1970s, resource crisis, environmental pollution and ecological degradation have become prominent globally, and the limits to growth have always been an important theoretical and policy issue. The technological system of early warning and regulation based on carrying capacity evaluation has great potential in natural resource utilization, environmental management and ecosystem conservation. In this paper, the evolution of carrying capacity research and the concept of ecological carrying capacity are summarized, and the existing evaluation methods of ecological carrying capacity are classified into ecological footprint method, comprehensive index system method, ecosystem service analysis method and human appropriation of net primary productivity method. The current problems in ecological carrying capacity study were analyzed and the trend was outlooked. Combined with the special issue, the recent proceeding of ecological carrying capacity study in the Belt and Road Initiative (BRI) region was narrated, from the aspects of ecological carrying capacity evaluation method and application, the supply and consumption of ecosystem services, and the resources use and environment change. Some suggestions have been proposed to improve the accuracy and reliability of ecological carrying capacity evaluation: 1) the spatial heterogeneity and temporal dynamic change of ecological carrying capacity should be explored furtherly; 2) the interaction between ecological process and human activities should be simulated; 3) factors such as climate change, human activities and ecological products and ecological service flows should be integrated into the evaluation system of ecological carrying capacity.

ACS Style

Zhen Lin; Xu Zengrang; Zhao Yuan; Wang Jijun; Hu Yunfeng; Wang Juanle. Ecological Carrying Capacity and Green Development in the “Belt and Road” Initiative Region. Journal of Resources and Ecology 2019, 10, 569 -573.

AMA Style

Zhen Lin, Xu Zengrang, Zhao Yuan, Wang Jijun, Hu Yunfeng, Wang Juanle. Ecological Carrying Capacity and Green Development in the “Belt and Road” Initiative Region. Journal of Resources and Ecology. 2019; 10 (6):569-573.

Chicago/Turabian Style

Zhen Lin; Xu Zengrang; Zhao Yuan; Wang Jijun; Hu Yunfeng; Wang Juanle. 2019. "Ecological Carrying Capacity and Green Development in the “Belt and Road” Initiative Region." Journal of Resources and Ecology 10, no. 6: 569-573.

Journal article
Published: 01 November 2019 in Journal of Resources and Ecology
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Desertification research plays a key role in the survival and development of all mankind. The Normalized Comprehensive Hotspots Index (NCH) is a comprehensive index that reveals the spatial distribution of research hotspots in a given research field based on the number of relevant scientific papers. This study uses Web Crawler technology to retrieve the full text of all Chinese journal articles spanning the 1980s–2018 in the Chinese Academic Journal full-text database (CAJ) from CNKI. Based on the 253,055 articles on desertification that were retrieved, we have constructed a research hotspot extraction model for desertification in China by means of the NCH Index. This model can reveal the spatial distribution and dynamic changes of research hotspots for desertification in China. This analysis shows the following: 1) The spatial distribution of research hotspots on desertification in China can be effectively described by the NCH Index, although its application in other fields still needs to be verified and optimized. 2) According to the NCH Index, the research hotspots for desertification are mainly distributed in the Agro-Pastoral Ecotone and grassland in Inner Mongolia, the desertification areas of Qaidam Basin in the Western Alpine Zone and the Oasis-Desert Ecotone in Xinjiang (including the extension of the central Tarim Basin to the foothills of the Kunlun Mountains, the sporadic areas around the Tianshan Mountains and the former hilly belt of the southern foothills of the Altai Mountains). Among these three, the Agro-Pastoral Ecotone in the middle and eastern part of Inner Mongolia includes the most prominent hotspots in the study of desertification. 3) Since the 1980s, the research hotspots for desertification in China have shown a general downward trend, with a significant decline in 219 counties (10.37% of the study area). This trend is dominated by the projects carried out since 2002. The governance of desertification in the eastern part of the Inner Mongolia-Greater Khingan Range still needs to be strengthened. The distribution of desertification climate types reflects the distribution of desertification in a given region to some extent. The Normalized Comprehensive Hotspots Index provides a new approach for researchers in different fields to analyze research progress.

ACS Style

Liang Yuting; Hu Yunfeng; Han Yueqi. Spatial Distribution and Dynamic Changes in Research Hotspots for Desertification in China Based on Big Data from CNKI. Journal of Resources and Ecology 2019, 10, 692 -703.

AMA Style

Liang Yuting, Hu Yunfeng, Han Yueqi. Spatial Distribution and Dynamic Changes in Research Hotspots for Desertification in China Based on Big Data from CNKI. Journal of Resources and Ecology. 2019; 10 (6):692-703.

Chicago/Turabian Style

Liang Yuting; Hu Yunfeng; Han Yueqi. 2019. "Spatial Distribution and Dynamic Changes in Research Hotspots for Desertification in China Based on Big Data from CNKI." Journal of Resources and Ecology 10, no. 6: 692-703.

Article
Published: 23 August 2019 in Journal of Geographical Sciences
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Wind-driven soil erosion results in land degradation, desertification, atmospheric dust, and sandstorms. The Hunshandake Sandy Land, an important part of the Two Barriers and Three Belts project, plays important roles in preventing desert and sandy land expansion and in maintaining local sustainability. Hence, assessing soil erosion and soil accumulation moduli and analyzing the dynamic changes are valuable. In this paper, Zhenglan Banner, located on the southern margin of the Hunshandake Sandy Land, was selected as the study area. The soil erosion and accumulation moduli were estimated using the 137Cs and 210Pbex composite tracing technique, and the dynamics of soil erosion and soil accumulation were analyzed during two periods. The results are as follows: (1) the regional 137Cs reference inventory was 2123.5±163.94 Bq/m2, and the regional 210Pbex reference inventory was 8112±1787.62 Bq/m2. (2) Based on the 137Cs isotope tracing analysis, the erosion moduli ranged from –483.99 to 740.31 t·km−2·a−1. Based on the 210Pbex isotope tracing analysis, the erosion moduli ranged from –441.53 to 797.98 t·km−2·a−1. (3) Compared with the earliest 50 years, the subsequent 50 years exhibited lower soil erosion moduli and accumulation moduli. Therefore, the activities of local sand dunes weakened, and the quality of the local ecological environment improved. The multi-isotope composite tracing technique combining the tracers 137Cs and 210Pbex has potential for similar soil erosion studies in arid or semiarid regions around the world.

ACS Style

Yunfeng Hu; Yunzhi Zhang. Using 137Cs and 210Pbex to investigate the soil erosion and accumulation moduli on the southern margin of the Hunshandake Sandy Land in Inner Mongolia. Journal of Geographical Sciences 2019, 29, 1655 -1669.

AMA Style

Yunfeng Hu, Yunzhi Zhang. Using 137Cs and 210Pbex to investigate the soil erosion and accumulation moduli on the southern margin of the Hunshandake Sandy Land in Inner Mongolia. Journal of Geographical Sciences. 2019; 29 (10):1655-1669.

Chicago/Turabian Style

Yunfeng Hu; Yunzhi Zhang. 2019. "Using 137Cs and 210Pbex to investigate the soil erosion and accumulation moduli on the southern margin of the Hunshandake Sandy Land in Inner Mongolia." Journal of Geographical Sciences 29, no. 10: 1655-1669.

Journal article
Published: 15 April 2019 in Sustainability
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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.

ACS Style

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 Style

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 (8):2261.

Chicago/Turabian Style

Huimin 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.

Journal article
Published: 06 March 2019 in Remote Sensing
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Limited research has been published on land changes and their driving mechanisms in Central Asia, but this area is an important ecologically sensitive area. Supported by Google Earth Engine (GEE), this study used Landsat satellite imagery and selected the random forest algorithm to perform land classification and obtain the annual land cover datasets of Central Asia from 2001 to 2017. Based on the temporal datasets, the distributions and dynamic trends of land cover were summarized, and the key factors driving land changes were analyzed. The results show that (1) the obtained land datasets are reliable and highly accurate, with an overall accuracy of 0.90 ± 0.01. (2) Grassland and bareland are the two most prominent land cover types, with area proportions of 45.0% and 32.9% in 2017, respectively. Over the past 17 years, bareland has displayed an overall reduction, decreasing by 2.6% overall. Natural vegetation (grassland, forest, and shrubland), cultivated land, water bodies and wetlands have displayed increasing trends at different rates. (3) The amount of precipitation and degree of drought are the driving factors that affect natural vegetation. The changes in cultivated land are mainly affected by precipitation and anthropogenic drivers. The effects of increasing urban populations and expanding industrial development are the factors driving the expansion of urban regions. The advantages and uncertainties arising from the land mapping and change detection method and the complexity of the driving mechanisms are also discussed.

ACS Style

Yunfeng Hu; Yang Hu. Land Cover Changes and Their Driving Mechanisms in Central Asia from 2001 to 2017 Supported by Google Earth Engine. Remote Sensing 2019, 11, 554 .

AMA Style

Yunfeng Hu, Yang Hu. Land Cover Changes and Their Driving Mechanisms in Central Asia from 2001 to 2017 Supported by Google Earth Engine. Remote Sensing. 2019; 11 (5):554.

Chicago/Turabian Style

Yunfeng Hu; Yang Hu. 2019. "Land Cover Changes and Their Driving Mechanisms in Central Asia from 2001 to 2017 Supported by Google Earth Engine." Remote Sensing 11, no. 5: 554.

Journal article
Published: 06 March 2019 in Sustainability
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Functional areas are the basic spatial units in which cities or development zones implement urban plans and provide functions. Internet map big data technology provides a new method for the identification and spatial analysis of functional areas. Based on the POI (point of interest) data from AMap (a map application of AutoNavi) from 2017, this paper proposes an urban functional areas recognition and analysis method based on the frequency density and the ratio of POI function types. It takes the Guangzhou Economic and Technological Development Zone as a case study to analyze the main function and spatial distribution characteristics of the detailed functional areas. The research shows the following: (1) The POI frequency density index and the function type ratio can effectively distinguish the functions of the grid units and analyze the spatial distribution characteristics of a complex functional area. (2) The single functional area is the most common area type in the Guangzhou Economic and Technological Development Zone. The largest proportion of all areas is allocated to traditional manufacturing industry functional areas, followed by high-tech enterprises, catering and entertainment, real estate, and education and health care, in descending order. The smallest proportion is allocated to finance and insurance functional areas. (3) The current layout of the functional areas in the Guangzhou Economic and Technological Development Zone conforms to the overall requirements and planning objectives of the central and local government. The layout and agglomeration of different blocks within the economic development zone are consistent with local industry’s target orientation and development history.

ACS Style

Yunfeng Hu; Yueqi Han. Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone. Sustainability 2019, 11, 1385 .

AMA Style

Yunfeng Hu, Yueqi Han. Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone. Sustainability. 2019; 11 (5):1385.

Chicago/Turabian Style

Yunfeng Hu; Yueqi Han. 2019. "Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone." Sustainability 11, no. 5: 1385.

Journal article
Published: 02 March 2019 in Sustainability
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Judging vegetation change and analyzing the impacts of driving factors on vegetation change are important bases on which to evaluate the effects of ecological engineering constructions on the Loess Plateau and to support ecological construction planning decisions. The authors applied time-section difference analysis and trend analysis methods to analyze the temporal–spatial characteristics of vegetation change on the Loess Plateau from 2000 to 2015. Then, complex linear regression analysis and residual analysis methods were applied to estimate the contribution rates of driving factors to regional vegetation changes. The results showed the following: (1) From 2000 to 2015, most areas of the Loess Plateau became “greener”. These areas were mainly distributed in the southern part of Shanxi Province, the northern and central parts of Shaanxi Province, and the eastern part of Gansu Province. (2) In 2015, the overall contribution rate of meteorological factors (temperature and precipitation) to normalized difference vegetation index (NDVI) in the Loess Plateau was as high as 87.7%. The average contribution rate of non-meteorological factors (mainly referring to human activities) to vegetation NDVI was 6.4%.

ACS Style

Yunfeng Hu; Rina Dao; Yang Hu. Vegetation Change and Driving Factors: Contribution Analysis in the Loess Plateau of China during 2000–2015. Sustainability 2019, 11, 1320 .

AMA Style

Yunfeng Hu, Rina Dao, Yang Hu. Vegetation Change and Driving Factors: Contribution Analysis in the Loess Plateau of China during 2000–2015. Sustainability. 2019; 11 (5):1320.

Chicago/Turabian Style

Yunfeng Hu; Rina Dao; Yang Hu. 2019. "Vegetation Change and Driving Factors: Contribution Analysis in the Loess Plateau of China during 2000–2015." Sustainability 11, no. 5: 1320.