scholarly journals Study on Spatial Imbalance and Determinants of E-Commerce Development in Zhejiang, China

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Haidong Zhong ◽  
Jinhui Zhang ◽  
Shaozhong Zhang ◽  
Wen Zheng
Keyword(s):  
Social Development ◽  
Ordinary Least Squares ◽  
Zhejiang Province ◽  
Analysis Method ◽  
Outlier Analysis ◽  
Related Data ◽  
Geographical Weighted Regression ◽  
Development Data ◽  
Spatial Analyst ◽  
Gwr Model

As a world-famous and well-developed e-commerce region, the development of e-commerce in Zhejiang province has always attracted people’s wide attention. Based on publicly available e-commerce transaction-related data, basic geographic data, and regional economic and social development data, we use the Gini coefficient to measure the imbalance of e-commerce development in Zhejiang province during 2017–2019. With the help of spatial analyst tools in ArcGIS desktop, the cluster and outlier analysis method is used to study the spatial pattern of e-commerce development in the province at the district or county-level city scale. To explore the causes of spatial aggregation and imbalance of e-commerce in Zhejiang province quantitatively, the paper proposes a geographical weighted regression (GWR) model with 15 economic and social development-related indicators. GWR and ordinary least squares (OLS) analysis indicate that 5 of the 15 selected indicators are highly related to the development of regional e-commerce development in Zhejiang, China.

scholarly journals Remote Sensing Estimation of Bamboo Forest Aboveground Biomass Based on Geographically Weighted Regression

2021 ◽  
Vol 13 (15) ◽  
pp. 2962
Author(s):  
Jingyi Wang ◽  
Huaqiang Du ◽  
Xuejian Li ◽  
Fangjie Mao ◽  
Meng Zhang ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Geographically Weighted Regression ◽  
Local Variation ◽  
Zhejiang Province ◽  
Weighted Regression ◽  
Landsat 8 ◽  
Bamboo Forest ◽  
Prediction Ability ◽  
Gwr Model ◽  
Forest Aboveground Biomass

Bamboo forests are widespread in subtropical areas and are well known for their rapid growth and great carbon sequestration ability. To recognize the potential roles and functions of bamboo forests in regional ecosystems, forest aboveground biomass (AGB)—which is closely related to forest productivity, the forest carbon cycle, and, in particular, carbon sinks in forest ecosystems—is calculated and applied as an indicator. Among the existing studies considering AGB estimation, linear or nonlinear regression models are the most frequently used; however, these methods do not take the influence of spatial heterogeneity into consideration. A geographically weighted regression (GWR) model, as a spatial local model, can solve this problem to a certain extent. Based on Landsat 8 OLI images, we use the Random Forest (RF) method to screen six variables, including TM457, TM543, B7, NDWI, NDVI, and W7B6VAR. Then, we build the GWR model to estimate the bamboo forest AGB, and the results are compared with those of the cokriging (COK) and orthogonal least squares (OLS) models. The results show the following: (1) The GWR model had high precision and strong prediction ability. The prediction accuracy (R2) of the GWR model was 0.74, 9%, and 16% higher than the COK and OLS models, respectively, while the error (RMSE) was 7% and 12% lower than the errors of the COK and OLS models, respectively. (2) The bamboo forest AGB estimated by the GWR model in Zhejiang Province had a relatively dense spatial distribution in the northwestern, southwestern, and northeastern areas. This is in line with the actual bamboo forest AGB distribution in Zhejiang Province, indicating the potential practical value of our study. (3) The optimal bandwidth of the GWR model was 156 m. By calculating the variable parameters at different positions in the bandwidth, close attention is given to the local variation law in the estimation of the results in order to reduce the model error.

scholarly journals Geographically weighted regression modelling of the spatial association between malaria cases and environmental factors in Cameroon.

2020 ◽  
Author(s):  
Marlvin Anemey Tewara ◽  
Liu Yunxia ◽  
Weiqiang Ling ◽  
Binang Helen Barong ◽  
Prisca Ngetemalah Mbah-Fongkimeh ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Spatial Variability ◽  
Geographically Weighted Regression ◽  
Environmental Variables ◽  
Vegetation Index ◽  
Spatial Association ◽  
Ordinary Least Squares ◽  
Variable Coefficients ◽  
Weighted Regression ◽  
Gwr Model

Abstract Background: Studies have illustrated the association of malaria cases with environmental factors in Cameroon but limited in addressing how these factors vary in space for timely public health interventions. Thus, we want to find the spatial variability between malaria hotspot cases and environmental predictors using Geographically weighted regression (GWR) spatial modelling technique.Methods: The global Ordinary least squares (OLS) in the modelling spatial relationships tool in ArcGIS 10.3. was used to select candidate explanatory environmental variables for a properly specified GWR model. The local GWR model used the global OLS candidate variables to examine, predict and explore the spatial variability between environmental factors and malaria hotspot cases generated from Getis-Ord Gi* statistical analysis. Results: The OLS candidate environmental variable coefficients were statistically significant (adjusted R2 = 22.3% and p < 0.01) for a properly specified GWR model. The GWR model identified a strong spatial association between malaria cases and rainfall, vegetation index, population density, and drought episodes in most hotspot areas and a weak correlation with aridity and proximity to water with an overall model performance of 0.243 (adjusted R2= 24.3%).Conclusion: The generated GWR maps suggest that for policymakers to eliminate malaria in Cameroon, there should be the creation of malaria outreach programs and further investigations in areas where the environmental variables showed strong spatial associations with malaria hotspot cases.

Exploring Spatial Patterns of Property Crime Risks in Changchun, China

2013 ◽  
Vol 4 (3) ◽  
pp. 80-100 ◽  
Author(s):  
Wei Song ◽  
Daqian Liu
Keyword(s):  
Spatial Patterns ◽  
Hot Spots ◽  
Property Crime ◽  
Ordinary Least Squares ◽  
Neighborhood Characteristics ◽  
Risk Areas ◽  
Gwr Model ◽  
The Relationship ◽  
The City ◽  
Crime Risks

Urban crime has increasingly become a major issue for Chinese cities. Using crime data collected at police precincts in 2008, the main aim of this research is to examine the spatial distribution of property crime which accounted for almost 82% of all crimes in the city of Changchun, and analyze the relationship between the spatial patterns of property crime and neighborhood characteristics. Standardized property crime rates (SCR) were applied to assess the relative risk of property crime across the city. Statistically significant clusters of high-risk areas or hot-spots were detected. A global ordinary least squares (OLS) regression model and a geographically weighted regression (GWR) model were calibrated to explore the risk of property crime as a function of contextual neighborhood characteristics. The analytical results show that significant local variations exist in the relationship between the risk of property crime and several neighborhood socioeconomic variables.

Analysis of Zhejiang Logistics Industry Spreading Effect Based on Inverse Matrix Coefficient Table

2010 ◽  
Vol 143-144 ◽  
pp. 384-388
Author(s):  
Rui Zhang ◽  
Jun Hu ◽  
Lin Ping Huang
Keyword(s):  
Economic Development ◽  
Zhejiang Province ◽  
Inverse Matrix ◽  
Matrix Coefficient ◽  
Analysis Method ◽  
Spreading Effect ◽  
Effect Analysis ◽  
Logistics Industry ◽  
National Economic ◽  
National Economic Development

With economic globalization, the modern logistics industry has been considered as a key of the national economic development. Based on Inverse Matrix Coefficient Table, using spreading effect analysis method, an empirical study was conducted about the development of logistics industry in Zhejiang Province. The position of the logistics industry was identified in national economic development of Zhejiang Province. The conclusion is that government should give priority to the development of basic industries and bottlenecks industry including of logistics industry.

A Comparative Study of Humane Ecological Status Quo in New Rural Areas of Zhejiang Province Based on the Interaction Analysis Method

2013 ◽  
Vol 671-674 ◽  
pp. 2165-2169
Author(s):  
Shuang Jun Xing ◽  
Ya Sha Wang
Keyword(s):  
Rural Areas ◽  
Regional Difference ◽  
Industrial Structure ◽  
Interaction Analysis ◽  
Ecological Status ◽  
Zhejiang Province ◽  
Analysis Method ◽  
New Countryside ◽  
Cultural Constructions ◽  
Inspiring Ideas

Scholars have investigated through a survey in 1895 villages within 11 areas of Zhejiang Province by using interaction analysis method in various angles, overall considering regional difference, sized and organizational structure difference, geographic difference, industrial structure difference, economic developmental difference and other factors. The aim of this paper is to sum up features of humane ecological state quo in Zhejiang Province, for giving inspiring ideas and suggestions to a new round of cultural constructions of the new countryside.

scholarly journals PENGARUH PERMAINAN KONSTRUKTIF TERHADAP PERKEMBANGAN SOSIAL ANAK PADA KELOMPOK B GUGUS VI KECAMATAN BULELENG

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Mutiara Hadi Pratiwi . ◽  
Prof. Dr. Anak Agung Gede Agung,M.Pd . ◽  
Mutiara Magta, S.Pd., M.Pd. .
Keyword(s):  
Social Development ◽  
Control Group ◽  
Cluster Sampling ◽  
Control Group Design ◽  
Group Design ◽  
Development Data ◽  
Quasi Experimental ◽  
Equivalent Control ◽  
Group B ◽  
Experimental Group

Perkembangan sosial anak sangat penting untuk dikembangkan dalam melakukan hubungan sosial di lingkungan sekitarnya, tetapi pada kenyataannya perkembangan sosial anak masih rendah dengan rata-rata 42,50%. Hal ini disebabkan minimnya penggunaan permainan konstruktif yang belum efektif, sehingga kualitas proses pembelajaran kurang optimal. Penelitian ini bertujuan untuk mengetahui pengaruh permainan konstruktif terhadap perkembangan sosial anak. Jenis penelitian ini merupakan penelitian quasi eksperimen, dengan desain penelitian Non equivalent Control Group Design. Populasi dalam penelitian ini adalah seluruh anak kelompok B pada gugus VI Kecamatan Buleleng yang berjumlah 387 anak. Pengambilan sampel dengan teknik random sampling dan yang terpilih sekolah TK Negeri Pembina sebagai kelompok eksperimen serta TK Aisyiyah sebagai kelompok kontrol. Hasil penelitian menunjukkan bahwa pada kelompok eksperimen memperoleh rata-rata sebesar 32.23 sedangkan pada kelompok kontrol memperoleh sebesar 24.75. Data perkembangan sosial anak kelompok eksperimen dan kelompok kontrol berdistribusikan normal dan homogen. Kemudian data dianalisis menggunakan uji-t, maka diperoleh hasil t_hitungdari kelompok eksperimen dan kelompok kontrol memperoleh hasil sebesar 12,26 dengan taraf signifikan 5% dan derajat kebebasan dk =57 adalah 2.002, sehingga t_hitung lebih besar dari t_tabel maka H_0 ditolak dan H_1 diterima yang berarti terdapat pengaruh yang signifikan antara kelompok yang mendapatkan perlakuan permainan konstruktif dengan kelompok yang tidak mendapatkan perlakuan.Kata Kunci : perkembangan sosial, permainan konstruktif. Social development of children is very important to be developed in social relationships in the surrounding environment. But in fact, the social development of children is still low with an average of as 42,50%. This is due to the lack of use of contructive games that have not been effective.so, the quality of learning process is less than optimal. This study aims to determine the effect of constructive game on social development of children. This type of study is a quasi experimental research, with research design Non equivalent Control Group Design. The population in this study were all children of group B in cluster VI Buleleng sub-district which amounting to 387 children. Sampling by technique cluster sampling, and selected one is Negeri Pembina kindergarten school as experimental group and Aisyiyah kindergarten as a control group. The results showed that in the experimental group earn on average 32,23 while in the control group earn on average 24,75. The children's social development data of the experimental group and the control group are normal and homogeneous distributed. Then the data were analyzed using t-test, the result obtained t_hitung of the experimental group and the control group obtained the result of 12.26 with a significant level of 5% degree of freedom = 57 t_tabel of 2.002, so t_hitung bigger than t_tabel then H_0 rejected and H_1 accepted which means there is a significant influence between groups receiving constructive game treatment with non-treated groups.keyword : social development, constructive game.

scholarly journals GRICE’S COOPERATIVE PRINCIPLES VIOLATION IN THE COMMUNICATION OF CHILDREN WITH AUTISM

2020 ◽  
Vol 22 (1) ◽  
Author(s):  
Dian Wahyunianto ◽  
Djatmika Djatmika ◽  
Dwi Purnanto
Keyword(s):  
Social Interaction ◽  
Social Development ◽  
Children With Autism ◽  
Analysis Method ◽  
Exceptional Children ◽  
Pragmatic Analysis ◽  
Language Obstacles ◽  
Cooperative Principles

The involvement of children with autism in social interaction is mostly at a lower level. It is due to the language obstacles faced by children with autism that become the reason why children with autism tend to violate the cooperative principles in communication. This study aims to demonstrate how children with autism violate Grice’s cooperative principles maxims and what causes it. The Grice’s cooperative principles maxims are the focus of this observation and 5 children with autism were the subjects of this study. The research was done in SLBN Surakarta which is the school for exceptional children in Surakarta. By utilizing the observational approach, the data were collected using recording and transcribing technique. Leech’s heuristic pragmatic analysis method was used to analyze the data. The results showed that 67.65% of utterances spoken by the children with autism violated 1 maxim, 20.59% utterances violated 2 maxims and 3 maxims violation was found in 2.94% utterances. 4 maxims violation was also found indicating that there are 8.82% utterances of the children with autism failed to fulfill cooperative principles. Language and social development problems are considered responsible for the violations well as their disability to stay focus are considered the cause of maxim of relevance become the most violated maxim in this study.

scholarly journals ANALYSIS OF THE SPATIOTEMPORALLY VARYING EFFECTS OF URBAN SPATIAL PATTERNS ON LAND SURFACE TEMPERATURES

2018 ◽  
Vol 26 (3) ◽  
pp. 216-231 ◽  
Author(s):  
Cheng Li ◽  
Jie Zhao ◽  
Nguyen Xuan Thinh ◽  
Wenfu Yang ◽  
Zhen Li
Keyword(s):  
Spatial Patterns ◽  
Land Surface ◽  
Spatial Scales ◽  
Pearson Correlation ◽  
Ordinary Least Squares ◽  
Related Factors ◽  
Spatial Metrics ◽  
Surface Temperatures ◽  
Land Surface Temperatures ◽  
Gwr Model

Urban heat islands (UHIs) are a worldwide phenomenon that have many ecological and social consequences. It has become increasingly important to examine the relationships between land surface temperatures (LSTs) and all related factors. This study analyses Landsat data, spatial metrics, and a geographically weighted regression (GWR) model for a case study of Hangzhou, China, to explore the correlation between LST and urban spatial patterns. The LST data were retrieved from Landsat images. Spatial metrics were used to quantify the urban spatial patterns. The effects of the urban spatial patterns on LSTs were further investigated using Pearson correlation analysis and a GWR model, both at three spatial scales. The results show that the LST patterns have changed significantly, which can be explained by the concurrent changes in urban spatial patterns. The correlation coefficients between the spatial metrics and LSTs decrease as the spatial scale increases. The GWR model performs better than an ordinary least squares analysis in exploring the relationship of LSTs and urban spatial patterns, which is indicated by the higher adjusted R2 values, lower corrected Akaike information criterion and reduced spatial autocorrelations. The GWR model results indicate that the effects of urban spatial patterns on LSTs are spatiotemporally variable. Moreover, their effects vary spatially with the use of different spatial scales. The findings of this study can aid in sustainable urban planning and the mitigation the UHI effect.

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