地理科学 ›› 2022, Vol. 42 ›› Issue (6): 1113-1123.doi: 10.13249/j.cnki.sgs.2022.06.017
林玉英1,2,3(), 李宝银3,4, 邱荣祖5, 林金国6, 伍世代1,4,*(
)
收稿日期:
2021-04-16
修回日期:
2021-08-10
出版日期:
2022-06-25
发布日期:
2022-08-23
通讯作者:
伍世代
E-mail:linyuying2019@fjnu.edu.cn;sdlw8726@sina.com
作者简介:
林玉英(1988−),女,福建龙岩人,副教授,博士后,主要从事道路景观生态、旅游地理等研究。E-mail: linyuying2019@fjnu.edu.cn
基金资助:
Lin Yuying1,2,3(), Li Baoyin3,4, Qiu Rongzu5, Lin Jinguo6, Wu Shidai1,4,*(
)
Received:
2021-04-16
Revised:
2021-08-10
Online:
2022-06-25
Published:
2022-08-23
Contact:
Wu Shidai
E-mail:linyuying2019@fjnu.edu.cn;sdlw8726@sina.com
Supported by:
摘要:
以闽江上游地区为例,在分析三明市2007—2016年森林碳密度时空动态的基础上,采用常规的以及改进后的道路网络测度指标,应用缓冲区分析方法和地理加权回归(Geographically Weighted Regression,GWR)模型,从线上和面上分别探讨道路网络对森林碳密度干扰的地理变异规律。结果表明:① 碳密度受到道路网络的较大影响,路网影响域内外碳密度的大小排序为:路网影响域内<整个研究区<路网影响域外;多条道路影响域重叠区的碳密度(26.330 Mg/hm2)明显低于单条道路影响域的碳密度(37.406 Mg/hm2);不同等级道路影响域的碳密度由大到小依次为县道>高速>省道>其它道路>国道>乡道。道路网络对2007—2016年碳密度的降低也有明显影响。② GWR模型的分析结果表明,路网对碳密度的影响程度随着样点的变化而变化,具有“空间非平稳性”。碳密度随着路网密度的增加而降低,而随着离道路距离的增加而增加。③ 研究区西北部和中部,GWR的回归系数及相关系数均较大,表明这2个区域道路对碳密度影响大且解释力皆较强。
中图分类号:
林玉英, 李宝银, 邱荣祖, 林金国, 伍世代. 基于GWR模型的道路网络对森林碳密度干扰的地理变异[J]. 地理科学, 2022, 42(6): 1113-1123.
Lin Yuying, Li Baoyin, Qiu Rongzu, Lin Jinguo, Wu Shidai. Geographic Variation of Road Network Effects on Forest Carbon Density Based on GWR Model: A Case Study of the Upstream District of the Minjiang River[J]. SCIENTIA GEOGRAPHICA SINICA, 2022, 42(6): 1113-1123.
Table 1
Comparison of carbon density within and outside of road effect zone in Sanming City from 2007 to 2016
变化等级 | 路域内 | 路域外 | 三明市 | |||||
面积/hm2 | 比例/% | 面积/hm2 | 比例/% | 面积/hm2 | 比例/% | |||
降低 | 14832.44 | 32.51 | 16149.37 | 23.46 | 30950.77 | 27.04 | ||
不变 | 11634.24 | 25.50 | 17803.48 | 25.86 | 29426.13 | 25.71 | ||
提高 | 19163.90 | 42.00 | 34891.35 | 50.68 | 54097.88 | 47.26 | ||
合计 | 45630.58 | 100.00 | 68844.20 | 100.00 | 114474.78 | 100.00 |
Table 2
Comparison of GWR and OLS models in fitting the relationship between carbon density and road measurements
模型 | 道路指标 | 残差平方和 | Sigma无偏估计 | 修正AIC | 拟合优度R2 |
注:LDE为常规的道路网络线密度指标、WLDE为加权的LDE指标、KDE为基于核密度估算方法计算道路网络线密度指标、WKDE为加权的KDE指标、REZD为道路网络影响域面密度指标、MREZD为考虑坡度的道路网络影响域面密度指标、DNR为离道路距离指标。 | |||||
GWR | LDE | 2468.68 | 1.49 | 4197.54 | 0.151 |
WLDE | 2458.05 | 1.49 | 4197.12 | 0.154 | |
KDE | 2373.78 | 1.47 | 4160.88 | 0.183 | |
WKDE | 2388.69 | 1.47 | 4165.70 | 0.178 | |
REZD | 2610.00 | 1.54 | 4271.79 | 0.102 | |
MREZD | 2608.26 | 1.54 | 4270.90 | 0.102 | |
DNR | 2386.47 | 1.47 | 4159.28 | 0.179 | |
OLS | LDE | 2612.39 | 1.51 | 4207.84 | 0.101 |
WLDE | 2620.48 | 1.51 | 4211.39 | 0.098 | |
KDE | 2544.65 | 1.49 | 4177.68 | 0.124 | |
WKDE | 2561.85 | 1.50 | 4185.41 | 0.118 | |
REZD | 2832.40 | 1.57 | 4300.67 | 0.025 | |
MREZD | 2833.01 | 1.57 | 4300.91 | 0.025 | |
DNR | 2617.75 | 1.51 | 4210.19 | 0.099 |
Table 3
Comparison of GWR coefficients of impacts of road measurements on the carbon density
指标 | 最小值 | 最大值 | 下四分位数 | 中位数 | 上四分位数 | 平均值 | 标准差 |
注:指标含义见 | |||||||
LDE | −1.430 | 0.018 | −0.747 | −0.552 | −0.377 | −0.571 | 0.296 |
WLDE | −14.038 | 1.866 | −5.527 | −4.052 | −2.335 | −4.340 | 2.866 |
KDE | −1.264 | 0.021 | −0.761 | −0.512 | −0.338 | −0.542 | 0.303 |
WKDE | −11.756 | 0.612 | −5.792 | −3.855 | −2.180 | −4.228 | 2.677 |
REZD | −1.841 | 1.230 | −0.868 | −0.420 | 0.030 | −0.374 | 0.663 |
MREZD | −1.869 | 1.216 | −0.865 | −0.406 | 0.039 | −0.371 | 0.666 |
DNR | 0.031 | 0.722 | 0.183 | 0.354 | 0.431 | 0.328 | 0.164 |
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