Research on the Temporal and Spatial Distribution and Influencing Factors of Forestry Output Efficiency in China

Forestry output efficiency is key to forestry development. China is now promoting the development of forestry, and thus the research on forestry output efficiency is of practical significance. Through the data envelopment analysis (DEA)-Malmquist index, spatial autocorrelation model, and fixed effect model of panel data, in this study, we analyzed the forestry output efficiency of China with indicators, such as the fixed asset input, employed personnel, total output value, and timber output, and drew the following conclusions. In the time series, the forestry total-factor productivity (TFP) in China saw a rapid increase, which is attributed to the technological progress change (TC), whereas the efficiency change (EC) imposed negative influences upon the forestry TFP. In the spatial distribution, there was a difference in the increase in the forestry output efficiency among the eastern, central, and western regions of China, with the eastern region having the fastest growth and the central region having the slowest growth. According to the spatial autocorrelation, there was spatial aggregation (high–high (HH) and low–low (LL)) with a significant positive correlation. Through the optimized fixed effect regression model, the fixed asset input, employed personnel, total output value, and timber output all had significant influences on the comprehensive technical efficiency of the forestry output, wherein the input indicators had negative influences, and the output indicators had positive influences.

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Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation

Infectious Diseases of Poverty ◽

10.1186/s40249-017-0338-7 ◽

2017 ◽

Vol 6 (1) ◽

Cited By ~ 6

Author(s):

Hai-Wen Du ◽

Yong Wang ◽

Da-Fang Zhuang ◽

Xiao-San Jiang

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Mongolian Gerbils ◽

Distribution Characteristics ◽

Temporal And Spatial Distribution ◽

Spatial Distribution Characteristics ◽

Temporal And Spatial

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An Empirical Study on Scientific Research Performance of Universities in Different Regions of China Based on PCA and Malmquist Index Method

Education Research International ◽

10.1155/2021/9699640 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Cun-Yang Xia ◽

Ze-Hui Yuan ◽

Wen-Yu He ◽

Ju-Hui Zhao

Keyword(s):

Research Performance ◽

Malmquist Index ◽

Scientific Research ◽

Principal Component ◽

Development Trend ◽

Entropy Method ◽

Evaluation Index System ◽

Eastern Region ◽

Index Method ◽

Output Efficiency

This paper uses principal component analysis (PCA) and entropy method to construct the evaluation index system of the scientific research performance of universities in 31 provinces and cities in China. Based on the traditional DEA model, the development trend of the scientific research performance of the research objects from 2015 to 2019 is dynamically evaluated by the Malmquist index method. The results show that the scientific research performance of universities in various regions of China is not ideal, and the level of scientific research performance is declining. The total factor productivity of scientific research in the central and western regions is much higher than that in the eastern region. The main factor that hinders the improvement of scientific research performance is the efficiency of technological progress. Finally, aiming at the existing problems, some feasible suggestions are put forward to further improve the input-output efficiency of scientific research in universities.

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Analysis of the Spatial Distribution of Aedes Albopictus by Indicator Kriging in an Urban Area of Shanghai, China

10.21203/rs.3.rs-72176/v1 ◽

2020 ◽

Author(s):

Yibin Zhou ◽

Hongxia Liu ◽

Peien Leng ◽

Jiang Zhu ◽

Shenjun Yao ◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Urban Area ◽

Aedes Albopictus ◽

Urban Areas ◽

Light Trap ◽

Indicator Kriging ◽

Surveillance Program ◽

Temporal And Spatial Distribution ◽

Positive Rate

Abstract Background: Aedes albopictus is a well-recognized vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. The current monitoring system, based on sub-district scale, in most cities of China for the spread of Ae. albopictus has not taken spatial distribution for the analysis of density of species. So it is not accurate enough for epidemic investigations, especially in big cities like Shanghai.Methods: In this study, a new surveillance program integrate the actual monitoring locations was used to investigate the temporal and spatial distribution of Ae. albopictus abundance in an urban area of Shanghai, China, from 2018 to 2019 by using the mosquito-oviposition trap (MOT) method. The study area of 14 sub-districts was divided into 133 grids with a side length of approximately 500 m. The vector abundance and spatial structure of Ae. Albopictus were predicted by the indicator Kriging based on eight MOTs in each grid. Meanwhile, the light trap (LT) method was also used for the analysis and compared with the MOT method.Results: A total of 8,192 MOTs were placed in the study area in 2018, and 7,917 (96.6%) were retrieved with a positive rate of 6.45%, while in 2019, 22,715 (97.0%) of 23,408 MOTs were recovered with a positive rate of 5.44%. When using the LT method, 273 (93.5%) and 312 (94.5%) adult female Ae. albopictus were gathered in 2018 and 2019, respectively. The Ae. albopictus populations in the urban area of Shanghai increased slowly from May, reached a peak in July, and declined gradually from September. The MOT positivity index (MPI) showed a significant positive spatial autocorrelation across the study area, while LT collections indicated a non-significant spatial autocorrelation. The MPI was suitable for spatial interpolation by using the indicator Kriging, and showed different hotspots in different years.Conclusions: The new surveillance system integrate geographic information can help improve our understanding of the spatial and temporal distribution of Ae. albopictus in urban areas of Shanghai and could provide a practical method for decision-makers to implement vector control and management of mosquitoes.

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Research on Input-output Efficiency of Urban Industrial Land based on Super-SBM Model

E3S Web of Conferences ◽

10.1051/e3sconf/201913604016 ◽

2019 ◽

Vol 136 ◽

pp. 04016

Author(s):

Quanhua Qian ◽

Xu Lu

Keyword(s):

Spatial Distribution ◽

Variable Coefficient ◽

Liaoning Province ◽

Input Output ◽

Fixed Asset ◽

Industrial Land ◽

Sbm Model ◽

Output Efficiency ◽

The Difference ◽

Output Indicators

The industrial land efficiency of 14 prefecture-level cities in Liaoning Province in China was measured and calculated by using three categories of input indicators (land, fixed asset, employed person) and output indicators (output value, profit, pollutant) and by using Super-SBM model. The results showed that the most of industrial land efficiency of every prefecture-level city in Liaoning Province was completely coordinated, the difference in their efficiency values was larger, the variable coefficient of their efficiency was large, and they had obvious two polarization; besides, they showed the decrease progressively from east to west on the spatial distribution and the trend of reducing from periphery to inner.

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The Spatial Patterns of Service Facilities Based on Internet Big Data: A Case Study on Chengdu

Mathematical Problems in Engineering ◽

10.1155/2021/9283185 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Hao Li ◽

Jianshu Duan ◽

Yidan Wu ◽

Sizhuo Gao ◽

Ting Li

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Spatial Patterns ◽

Spatial Data ◽

Spatial Clustering ◽

Spatial Data Mining ◽

Sustainable Urban Development ◽

Practical Significance ◽

Ring Road ◽

Multiple Clusters

In the context of the mid-late development of China’s urbanization, promoting sustainable urban development and giving full play to urban potential have become a social focus, which is of enormous practical significance for the study of urban spatial pattern. Based on such Internet data as a map’s Point of Interest (POI), this paper studies the spatial distribution pattern and clustering characteristics of POIs of four categories of service facilities in Chengdu of Sichuan Province, including catering, shopping, transportation, scientific, educational, and cultural services, by means of spatial data mining technologies such as dimensional autocorrelation analysis and DBSCAN clustering. Global spatial autocorrelation is used to study the correlation between an index of a certain element and itself (univariate) or another index of an adjacent element (bivariate); partial spatial autocorrelation is used to identify characteristics of spatial clustering or spatial anomaly distribution of geographical elements. DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is able to detect clusters of any shape without prior knowledge. The final step is to carry out quantitative analysis and reveal the distribution characteristics and coupling effects of spatial patterns. According to the results, (1) the spatial distribution of POIs of all service facilities is significantly polarized, as they are concentrated in the old city, and the trend of suburbanization is indistinctive, showing three characteristics, namely, central driving, traffic accessibility, and dependence on population activity; (2) the spatial distribution of POIs of the four categories of service facilities is featured by the pattern of “one center, multiple clusters,” where “one center” mainly covers the area within the first ring road and partial region between the first ring road and the third ring road, while “multiple clusters” are mainly distributed in the well-developed areas in the second circle of Chengdu, such as Wenjiang District and Shuangliu District; and (3) there is a significant correlation between any two categories of POIs. Highly mixed multifunctional areas are mainly distributed in the urban center, while service industry is less aggregated in urban fringe areas, and most of them are single-functional or dual-functional regions.

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Temporal and Spatial Distribution Characteristics of NOx Emissions of City Buses on Real Road Based on Spatial Autocorrelation

Aerosol and Air Quality Research ◽

10.4209/aaqr.200059 ◽

2021 ◽

Vol 21 ◽

Author(s):

Qikai Peng ◽

Jiaqiang Li ◽

Yanyan Wang ◽

Longqing Zhao ◽

Jianwei Tan ◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Nox Emissions ◽

Distribution Characteristics ◽

Temporal And Spatial Distribution ◽

Spatial Distribution Characteristics ◽

Temporal And Spatial

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Analysis of the Spatial Distribution of Aedes Albopictus by Indicator Kriging in an Urban Area of Shanghai, China

10.21203/rs.3.rs-72176/v2 ◽

2020 ◽

Author(s):

Yibin Zhou ◽

Hongxia Liu ◽

Peien Leng ◽

Jiang Zhu ◽

Shenjun Yao ◽

...

Keyword(s):

Spatial Distribution ◽

Spatial Autocorrelation ◽

Urban Area ◽

Aedes Albopictus ◽

Urban Areas ◽

Light Trap ◽

Indicator Kriging ◽

Surveillance Program ◽

Temporal And Spatial Distribution ◽

Positive Rate

Abstract Background: Aedes albopictus is a well-recognized vector of major arboviral diseases and a primary pest in tropical and temperate regions of China. In the current monitoring system for the spread of Ae. albopictus based on the sub-district scale in most cities of China, spatial distribution has not been considered for the analysis of the density of species. So, the system is not accurate enough for epidemic investigations, especially in big cities like Shanghai.Methods: In this study, an improved surveillance program integrating the actual monitoring locations was used to investigate the temporal and spatial distribution of Ae. albopictus abundance in an urban area of Shanghai, China, from 2018 to 2019 by using the mosquito-oviposition trap (MOT) method. The study area of 14 sub-districts was divided into 133 grids. The vector abundance and spatial structure of Ae. Albopictus were predicted by the indicator Kriging based on eight MOTs in each grid. Meanwhile, the light trap (LT) method was also used for the analysis and compared with the MOT method.Results: A total of 8,192 MOTs were placed in the study area in 2018, and 7,917 (96.6%) were retrieved with a positive rate of 6.45%, while in 2019, 22,715 (97.0%) of 23,408 MOTs were recovered with a positive rate of 5.44%. When using the LT method, 273 (93.5%) and 312 (94.5%) adult female Ae. albopictus were gathered in 2018 and 2019, respectively. The Ae. albopictus populations in the urban area of Shanghai increased slowly from May, reached a peak in July, and declined gradually from September. The MOT positivity index (MPI) showed a significant positive spatial autocorrelation across the study area, while LT collections indicated a non-significant spatial autocorrelation. The MPI was suitable for spatial interpolation by using the indicator Kriging and showed different hotspots in different years.Conclusions: The improved surveillance system integrating geographic information can help improve our understanding of the spatial and temporal distribution of Ae. albopictus in urban areas of Shanghai and could provide a practical method for decision-makers to implement vector control and management of mosquitoes.

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