scholarly journals Analysis On Spatial Distribution And Influencing Factors Of China National Forest Villages Based on GIS

2021 ◽  
Author(s):  
Zhen Wei ◽  
Fengtai Zhang ◽  
Yuzhen Li ◽  
Youzhi An ◽  
Changcheng Sun ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Standard Deviation ◽  
Influencing Factors ◽  
Hot Spots ◽  
Kernel Density ◽  
National Forest ◽  
Distribution Characteristics ◽  
The North ◽  
Spatial Distribution Characteristics ◽  
Cold Spots

Abstract As a carrier to promote rural greening and beautification and further implement the rural revitalization strategy, it is of great significance to study the spatial distribution characteristics of China national forest villages and its influencing factors. Taking 7586 China national forest villages as examples, the spatial distribution characteristics and influencing factors of China national forest villages were studied by using such methods as nearest neighbor index, Tyson polygon, cold hot spot analysis, standard deviation ellipse and kernel density index. The results showed that: (1) the overall clustering distribution characteristics of China national forest villages were significant, and the distribution type was agglomeration. There was no breakthrough in the Hu Huanyong Line, and the southeast of the line was the main concentration area. (2) From the perspective of spatial clustering, it shows the distribution characteristics of "hot spots in the south and cold spots in the north". Hot spots are mostly located in the south, represented by Sichuan, Guangdong, Hunan, etc., while cold spots are mostly in the north, mainly in Xinjiang, Xizang, etc.(3) From the perspective of spatial distribution direction, the standard deviation ellipse coincidence degree of the two batches is relatively high. The two batches are distributed in a dense direction from northeast to southwest with Suizhou city, Hubei as the geometric center. The concentration degree of the second batch increases on the basis of the first batch, showing a trend of migration and distribution in the southwest.(4) From the perspective of the distribution characteristics of kernel density, the distribution of kernel density has a strong correlation with two factors, one is the forest vegetation coverage, the other is the distribution location of urban agglomeration;(5) Elevation, slope direction, river basin, traffic are important factors affecting the distribution of China national forest villages, which show the spatial distribution characteristics of "low altitude, positive, near water and convenient transportation". Based on the spatial distribution characteristics and influencing factors, the paper puts forward policy Suggestions for the evaluation and construction of China national forest villages in the future.

scholarly journals Identifying the density of grassland fire points with kernel density estimation based on spatial distribution characteristics

2021 ◽  
Vol 13 (1) ◽  
pp. 796-806
Author(s):  
Zhen Shuo ◽  
Zhang Jingyu ◽  
Zhang Zhengxiang ◽  
Zhao Jianjun
Keyword(s):  
Spatial Distribution ◽  
Density Estimation ◽  
Kernel Density Estimation ◽  
Function Method ◽  
Kernel Density ◽  
Fire Occurrence ◽  
Distribution Characteristics ◽  
Fire Point ◽  
Spatial Distribution Characteristics ◽  
Grassland Fire

Abstract Understanding the risk of grassland fire occurrence associated with historical fire point events is critical for implementing effective management of grasslands. This may require a model to convert the fire point records into continuous spatial distribution data. Kernel density estimation (KDE) can be used to represent the spatial distribution of grassland fire occurrences and decrease the influences historical records in point format with inaccurate positions. The bandwidth is the most important parameter because it dominates the amount of variation in the estimation of KDE. In this study, the spatial distribution characteristic of the points was considered to determine the bandwidth of KDE with the Ripley’s K function method. With high, medium, and low concentration scenes of grassland fire points, kernel density surfaces were produced by using the kernel function with four bandwidth parameter selection methods. For acquiring the best maps, the estimated density surfaces were compared by mean integrated squared error methods. The results show that Ripley’s K function method is the best bandwidth selection method for mapping and analyzing the risk of grassland fire occurrence with the dependent or inaccurate point variable, considering the spatial distribution characteristics.

Spatial Distribution Characteristics and Influencing Factors of the World Architectural Heritage

Heritage ◽  
2021 ◽  
Vol 4 (4) ◽  
pp. 2942-2959
Author(s):  
Xuefei Wang ◽  
Jiazhen Zhang ◽  
Jeremy Cenci ◽  
Vincent Becue
Keyword(s):  
Spatial Distribution ◽  
Influencing Factors ◽  
Western Europe ◽  
Temporal Distribution ◽  
Distribution Characteristics ◽  
Architectural Heritage ◽  
Heritage Sites ◽  
Spatial Distribution Characteristics ◽  
The World ◽  
Heritage Protection

This research focusing on the world architectural heritage sites registered in the World Heritage List established by UNESCO aimed to analyze its spatial distribution characteristics and influencing factors at the world and regional level to provide a scientific basis for further architectural heritage conservation. Firstly, this study explored the spatial distribution characteristics of the world architectural heritage sites using the ArcGIS spatial analysis method. Then, we used the space–time statistical method to analyze their spatial and temporal distribution characteristics. The main findings are as follows: (1) world architectural heritage sites are distributed in clusters with imbalanced patterns and a strong degree of concentration: in Western Europe, Eastern Asia, and Northwestern Latin America, with clear country distribution, especially in Italy, China, and Mexico; (2) the time of construction can be divided into four stages: the ancient historic sites stage, the uniform and stable stage, the stage of growth in Asia and Europe, and the stage of growth in Europe, America, and Africa; (3) different types of heritage sites are unevenly distributed, and the type distribution differs significantly between regions, with regional uniqueness. The authors also analyzed the influencing factors of the spatial distribution characteristics and highlighted the important influence of the geographical environment, historical evolution, economic strength and discourse power, international heritage protection situation, and registration policy. This study may provide basis for specific guidance and directions for heritage protection for various countries and regions.

scholarly journals Spatial Distribution Characteristics of Soil Salinity and Moisture and Its Influence on Agricultural Irrigation in the Ili River Valley, China

2019 ◽  
Vol 11 (24) ◽  
pp. 7142
Author(s):  
Li Xu ◽  
Hongru Du ◽  
Xiaolei Zhang
Keyword(s):  
Spatial Distribution ◽  
Influencing Factors ◽  
Soil Salinity ◽  
Arid Regions ◽  
Major Influence ◽  
Available Phosphorus ◽  
Arid Areas ◽  
Distribution Characteristics ◽  
Topographic Factors ◽  
Spatial Distribution Characteristics

Soil salinization is a global problem, which threatens agricultural productivity and sustainability, especially in arid and semi-arid regions. Soil salinity and moisture are important factors affecting agricultural production in arid regions. However, few studies have considered the influence of topographic factors on the spatial distribution patterns of soil salinity and moisture. This research aims to explore the spatial distribution characteristics and its influencing factors of soil salinity and moisture in the oasis farmland of arid areas. In this paper, GIS and geostatistics methods were applied to analyze the spatial distribution characteristics and variability of soil salinity and moisture, and then the corresponding proxy variables were used to quantitatively study the influence factors by using the geographical detector model. The results showed the coefficients of the variation of soil salinity and moisture to be 71.25% and 31.89%, respectively. There was moderate spatial autocorrelation of soil salinity and moisture. Soil salinity in the southwest was higher than in the northeast, and soil moisture in the northwest and southeast were lower than in the center and the northeast edge. The main influencing factors were available phosphorus, roughness of terrain, alkaline nitrogen, available potassium, and elevation. Combined action of topographic factors and soil nutrients has a major influence on the spatial distribution of soil salinity and moisture. Therefore, developing a suitable fertilizer regime under different topographic conditions could be an effective way to promote the sustainability of oasis agriculture in arid areas.

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