基于地理加权回归的茶叶种植专业化空间格局及影响因素——以福建省安溪县为例

doi:10.13287/j.1001-9332.201704.037

应用生态学报 ›› 2017, Vol. 28 ›› Issue (4): 1298-1308.doi: 10.13287/j.1001-9332.201704.037

基于地理加权回归的茶叶种植专业化空间格局及影响因素——以福建省安溪县为例

税伟^1,2,3,4*, 杜勇^2,3, 陈毅萍¹, 简小枚¹, 范冰雄¹

¹福州大学环境与资源学院, 福州 350116
²福州大学空间数据挖掘与信息共享教育部重点实验室, 福州 350116
³福建省空间信息工程研究中心, 福州 350116
⁴福建农林大学茶产业发展研究中心, 福建安溪 362400

收稿日期:2016-10-08 出版日期:2017-04-18 发布日期:2017-04-18
通讯作者: * E-mail: shuiwei@fzu.edu.cn
作者简介:税伟,男,1974年生.主要从事土地利用/覆被变化与生态环境效应、生态农业、遥感与地理信息技术应用研究.E-mail:shuiwei@fzu.edu.cn
基金资助:
本文由国家社会科学基金项目(12CJL063)资助

Spatial patterns and influence factors of specialization in tea cultivation based on geographically weighted regression model: A case study of Anxi County of Fujian Province, China

SHUI Wei^1,2,3,4*, DU Yong^2,3, CHEN Yi-ping¹, JIAN Xiao-mei¹, FAN Bing-xiong¹

¹College of Environment and Resources, Fuzhou University, Fuzhou 350116, China
²Key Laboratory of Spatial Data Mining & Information Sharing, Ministry of Education, Fuzhou 350116, China
³Fujian Spatial Information Research Center, Fuzhou 350116, China
⁴Research Center of Tea Industry Development, Fujian Agriculture and Forestry University, Anxi 362400, Fujian, China

Received:2016-10-08 Online:2017-04-18 Published:2017-04-18
Contact: * E-mail: shuiwei@fzu.edu.cn
Supported by:
This work was supported by the National Social Science Foundation of China (12CJL063)

摘要/Abstract

摘要： 以专业化茶叶种植大县安溪县为例,通过评估各乡镇茶叶种植专业化水平,结合Pearson相关分析、普通最小二乘法模型(OLS)和地理加权回归模型(GWR),筛选出平均高程、农民人均纯收入、农业从业人口比重、距交通道路距离4个主要影响安溪县茶叶种植专业化程度的因素,并探讨其对茶叶种植专业化影响程度的空间分异规律.结果表明: 安溪县各乡镇茶叶种植专业化程度呈现显著的空间自相关,以县城为中心,茶叶种植专业化程度由近及远呈现出“低-中-高”的形似杜能农业区位模型的圈层结构;GWR的拟合度(0.624)高于OLS(0.595),且前者对空间数据的解释力更高;与杜能农业区位模型的市场距离决定机制相悖,茶叶种植专业化程度受山地自然环境因素的影响明显较社会经济因素更大;茶叶种植专业化程度与平均高程、农民人均纯收入、农业从业人口比重呈正相关,而与距交通道路距离总体呈负相关;茶叶种植专业化程度与平均高程、农民人均纯收入的回归系数主要呈现出“南高北低”的空间分布特征,农业从业人口比重则呈相反的规律,而距交通道路距离则主要呈现“西南低、东北高”的空间特征.

Abstract: Anxi County, specializing in tea cultivation, was taken as a case in this research. Pearson correlation analysis, ordinary least squares model (OLS) and geographically weighted regression model (GWR) were used to select four primary influence factors of specialization in tea cultivation (i.e., the average elevation, net income per capita, proportion of agricultural population, and the distance from roads) by analyzing the specialization degree of each town of Anxi County. Meanwhile, the spatial patterns of specialization in tea cultivation of Anxi County were evaluated. The results indicated that specialization in tea cultivation of Anxi County showed an obvious spatial auto-correlation, and a spatial pattern with “low-middle-high” circle structure, which was similar to Von Thünen’s circle structure model, appeared from the county town to its surrounding region. Meanwhile, GWR (0.624) had a better fitting degree than OLS (0.595), and GWR could reasonably expound the spatial data. Contrary to the agricultural location theory of Von Thünen’s model, which indicated that distance from market was a determination factor, the specialization degree of tea cultivation in Anxi was mainly decided by natural conditions of mountain area, instead of the social factors. Specialization degree of tea cultivation was positively correlated with the average elevation, net income per capita and the proportion of agricultural population, while a negative correlation was found between the distance from roads and specialization degree of tea cultivation. Coefficients of regression between the specialization degree of tea cultivation and two factors (i.e., the average elevation and net income per capita) showed a spatial pattern of higher level in the north direction and lower level in the south direction. On the contrary, the regression coefficients for the proportion of agricultural population increased from south to north of Anxi County. Furthermore, regression coefficient for the distance from roads showed a spatial pattern of higher level in the northeast direction and lower level in the southwest direction of Anxi County.

税伟, 杜勇, 陈毅萍, 简小枚, 范冰雄. 基于地理加权回归的茶叶种植专业化空间格局及影响因素——以福建省安溪县为例[J]. 应用生态学报, 2017, 28(4): 1298-1308.

SHUI Wei, DU Yong, CHEN Yi-ping, JIAN Xiao-mei, FAN Bing-xiong. Spatial patterns and influence factors of specialization in tea cultivation based on geographically weighted regression model: A case study of Anxi County of Fujian Province, China[J]. Chinese Journal of Applied Ecology, 2017, 28(4): 1298-1308.

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基于地理加权回归的茶叶种植专业化空间格局及影响因素——以福建省安溪县为例

Spatial patterns and influence factors of specialization in tea cultivation based on geographically weighted regression model: A case study of Anxi County of Fujian Province, China

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