榆林地区植被时空分异特征及其影响因素研究

doi:10.16258/j.cnki.1674-5906.2022.01.004

生态环境学报 ›› 2022, Vol. 31 ›› Issue (1): 26-36.DOI: 10.16258/j.cnki.1674-5906.2022.01.004

榆林地区植被时空分异特征及其影响因素研究

聂桐¹^,²(), 董国涛²^,³^,^*(), 蒋晓辉¹, 郭欣伟², 党素珍², 郑嘉昊¹, 李立缠¹, 王江¹

1.西北大学,陕西西安 710127
2.黄河水利委员会黄河水利科学研究院,河南郑州 450003
3.黑河水资源与生态保护研究中心,甘肃兰州 730030

收稿日期:2021-03-31 出版日期:2022-01-18 发布日期:2022-03-10
通讯作者: *董国涛（1982年生）,男,正高级工程师,博士,主要从事水文水资源遥感方面研究。E-mail: dongguotao@hhglj.yrcc.gov.cn
作者简介:聂桐（1997年生）,女,硕士研究生,主要从事社会水文学方面研究。E-mail: ntongxd@163.com
基金资助:
国家自然科学基金项目(51779099);国家自然科学基金项目(51779209);国家自然科学基金项目(51909099);国家重点研发计划项目(2016YFC0402400)

Spatio-temporal Variations and Influencing Factors of Vegetation in Yulin

NIE Tong¹^,²(), DONG Guotao²^,³^,^*(), JIANG Xiaohui¹, GUO Xinwei², DANG Suzhen², ZHENG Jiahao¹, LI Lichan¹, WANG Jiang¹

1. College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, P. R. China
2. Yellow River Conservancy Commission, Yellow River Institute of Hydraulic Research, Zhengzhou, 450003, P. R. China
3. Heihe Water Resources and Ecological Protection Research Center, Lanzhou, 730030, P. R. China

Received:2021-03-31 Online:2022-01-18 Published:2022-03-10

摘要/Abstract

摘要：

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用。以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特征。结果表明,（1）研究区2000—2018年植被覆盖趋向改善,NDVI呈现增加趋势,增速为0.11/10 a,2008年以后植被增长较为明显;NDVI在2018年中高等级（0.6—0.8）面积比2000年中高等级面积明显增加;中高等级集中于榆林市东部黄土丘陵区,中低等级（0.2—0.4）集中于榆林市西北部的风沙区,植被覆盖呈现东部高西北低的空间分布特征。（2）人口密度和气温因子较好地解释植被NDVI空间分异性,是影响NDVI空间分异性的主要因子,GDP、土地利用类型和坡度是次级影响因子,其他因子对NDVI空间分异存在间接影响;坡向、降水和土壤类型因子与其他自然、人文因素对植被空间分布影响存在显著性差异。（3）自然、人文因子对榆林市NDVI的影响存在交互作用,因子之间的交互效应表现为相互增强或非线性增强关系,不存在独立关系。该研究揭示了促进植被生长的各影响因素适宜类型或范围,自然、人文因子的共同作用对植被影响更加显著,为地方政府指导区域植被恢复和生态修复提供科学依据。

关键词: 植被, 归一化植被指数（NDVI）, 地理探测器, 空间分异性, 驱动力, 榆林市

Abstract:

As an essential indicator that reflects terrestrial ecosystem and climate, vegetation plays an important role in the study of global or regional ecological environment changes. Based on the Geographic Detector Model, five categories of natural factors (i.e., aspect, slope, temperature, precipitation, and soil type) and three categories of human factors (i.e., land use type, population density, and GDP) were selected to analyze the spatial differentiation characteristics and driving forces of vegetation in the Yulin area. In addition, the study revealed top factors that promote vegetation growth in this area. The results show that the vegetation coverage in the study area had improved from 2000 to 2018. The Normalized Differential Vegetation Index (NDVI) suggested an increasing trend with a growth rate of 0.11/10 and a faster growing rate after 2008. Areas with a medium-high NDVI value(0.6-0.8) had increased significantly from 2000 to 2018. The medium-high NDVI was concentrated in the eastern loess hilly area of Yulin, while the medium-low NDVI (0.2-0.4) in the wind-sand area in the northwest of Yulin. The vegetation cover exhibited spatial characteristics of high in the east and low in the northwest. Second, among the factors examined in the study, the population density and temperature were main factors affecting NDVI and could better explain its spatial variability, while GDP, land-use type, and slope were secondary influencing factors. Significant differences existed among the effects of slope direction, precipitation, soil type, and other natural or human factors on the spatial distribution of vegetation. Finally, the natural and human factors had an interactive effect on the NDVI in Yulin as these factors enhanced each other or had a non-linear relationship. Overall, the results of this study further revealed the type and range of influencing factors that promote vegetation growth. The combination of natural and human factors showed a more prominent impact on vegetation, providing scientific evidence for local governments to guide vegetation and ecological restoration.

Key words: vegetation, Normalized Differential Vegetation Index (NDVI), geographic detector model, spatial heterogeneity, driving forces, Yulin

中图分类号:

Q948
X173

聂桐, 董国涛, 蒋晓辉, 郭欣伟, 党素珍, 郑嘉昊, 李立缠, 王江. 榆林地区植被时空分异特征及其影响因素研究[J]. 生态环境学报, 2022, 31(1): 26-36.

NIE Tong, DONG Guotao, JIANG Xiaohui, GUO Xinwei, DANG Suzhen, ZHENG Jiahao, LI Lichan, WANG Jiang. Spatio-temporal Variations and Influencing Factors of Vegetation in Yulin[J]. Ecology and Environment, 2022, 31(1): 26-36.

图/表 13

参考文献 41

[1]	DU J Q, QUAN Z J, FANG S F, et al., 2020. Spatiotemporal changes in vegetation coverage and its causes in China since the Chinese economic reform[J]. Springer Berlin Heidelberg, 27(1): 1144-1159.
[2]	GHOLAMNIA M, KHANDAN R, BONAFONI S, et al., 2019. Spatiotemporal analysis of MODIS NDVI in the semi-arid region of Kurdistan (Iran)[J]. Remote Sensing, 11(14): 1723-1741. DOI URL
[3]	HAWLEY MARK E, JACKSON THOMAS J, MCCUEN RICHARD H, 1983. Surface soil moisture variation on small agricultural watersheds[J]. Journal of Hydrology, 62(1-4): 179-200. DOI URL
[4]	HEIN L, RIDDER N D, HIEMAUX P, et al., 2011. Desertification in the Sahel: Towards better accounting for ecosystem dynamics in the interpretation of remote sensing images[J]. Journal of Arid Environments, 75(11): 1164-1172. DOI URL
[5]	LIU S Y, HUANG S Z, XIE Y Y, et al., 2019. Spatial-temporal changes in vegetation cover in a typical semi-humid and semi-arid region in China: Changing patterns, causes and implications[J]. Ecological Indicators, 9: 462-475. DOI URL
[6]	MENG X Y, GAO X, LI S Y, et al., 2020. Spatial and Temporal Characteristics of Vegetation NDVI Changes and the Driving Forces in Mongolia during 1982-2015 [J]. Remote Sensing, 12(4): 603-628. DOI URL
[7]	WEI X D, WANG S N, WANG Y K, 2018. Spatial and temporal change of fractional vegetation cover in North-western China from 2000 to 2010 [J]. Geological Journal, 53(S2): 427-434. DOI URL
[8]	YUAN L H, CHEN X Q, WANG X Y, et al., 2019. Spatial associations between NDVI and environmental factors in the Heihe River Basin[J]. Science Press, 29(9): 1548-1564.
[9]	YUE S, PILON P, CAVADIAS G, 2002. Power of the Mann-Kendall and Spearman’s rho tests for detecting monotonic trends in hydrological series[J]. Journal of Hydrology, 259(1-4): 254-271. DOI URL
[10]	陈晓莹, 陈林, 宋乃平, 等, 2020. 荒漠草原两种类型土壤的水分动态对比[J]. 应用生态学报, 31(5): 1560-1570.
	CHEN X Y, CHEN L, SONG N P, et al., 2020. Comparison on moisture dynamics of two different soil types in desert steppe[J]. Chinese Journal of Applied Ecology, 31(5): 1560-1570.
[11]	邓晨晖, 白红英, 高山, 等, 2018. 秦岭植被覆盖时空变化及其对气候变化与人类活动的双重响应[J]. 自然资源学报, 33(3): 425-438.
	DENG C H, BAI H Y, GAO S, et al., 2018. Spatial-temporal variation of the vegetation coverage in qinling mountains and its dual response to climate change and human activities[J]. Journal of Natural Resources, 33(3): 425-438.
[12]	高江波, 焦珂伟, 吴绍洪, 2019. 1982-2013年中国植被NDVI空间异质性的气候影响分析[J]. 地理学报, 74(3): 534-543. DOI
	GAO J B, JIAO K W, WU S H, 2019. Revealing the climatic impacts on spatial heterogeneity of NDVI in China during 1982-2013 [J]. Acta Geographica Sinica, 74(3): 534-543.
[13]	黄麟, 曹巍, 祝萍, 2020. 退耕还林还草工程生态效应的地域分异特征[J]. 生态学报, 40(12): 4041-4052.
	HUANG L, CAO W, ZHU P, 2020. The regional variation characters of ecological effects of the grain for green project[J]. Acta Ecologica Sinica, 40(12): 4041-4052.
[14]	贾坤, 姚云军, 魏香琴, 等, 2013. 植被覆盖度遥感估算研究进展[J]. 地球科学进展, 28(7): 774-782.
	JA K, YAO Y J, WEI X Q, et al., 2013. A Review on Fractional Vegetation Cover Estimation Using Remote Sensing[J]. Advances in Earth Science, 28(7): 774-782.
[15]	金凯, 王飞, 韩剑桥, 等, 2020. 1982-2015年中国气候变化和人类活动对植被NDVI变化的影响[J]. 地理学报, 75(5): 961-974. DOI
	JIN K, WANG F, HAN J Q, et al., 2020. Contribution of climatic change and human activities to vegetation NDVI change over China during 1982-2015 [J]. Acta Geographica Sinica, 75(5): 961-974. DOI
[16]	孔冬冬, 张强, 黄文琳, 等, 2017. 1982-2013年青藏高原植被物候变化及气象因素影响[J]. 地理学报, 72(1): 39-52. DOI
	KONG D D, ZHANG Q, HANG W L, et al., 2017. Vegetation phenology change in Tibetan Plateau from 1982 to 2013 and its related meteorological factors[J]. Acta Geographica Sinica, 72(1): 39-52.
[17]	李辉霞, 刘国华, 傅伯杰, 2011. 基于NDVI的三江源地区植被生长对气候变化和人类活动的响应研究[J]. 生态学报, 31(19): 5495-5504.
	LI H X, LIU G H, FU B J, 2011. Response of vegetation to climate change and human activity based on NDVI in the Three-River Headwaters region[J]. Acta Ecologica Sinica, 31(19): 5495-5504.
[18]	刘斌, 孙艳玲, 王中良, 等, 2015. 华北地区植被覆盖变化及其影响因子的相对作用分析[J]. 自然资源学报, 30(1): 12-23.
	LIU B, SUN Y L, WANG Z L, et al., 2015. Analysis of the Vegetation Cover Change and the Relative Role of Its Influencing Factors in North China[J]. Journal of Natural Resources, 30(1): 12-23.
[19]	刘宪锋, 任志远, 林志慧, 等, 2013. 2000-2011年三江源区植被覆盖时空变化特征[J]. 地理学报, 68(7): 897-908.
	LIU X F, REN Z Y, LIN Z H, et al., 2013. The spatial-temporal changes of vegetation coverage in the Three-River Headwater Region in recent 12 years[J]. Acta Geographica Sinica, 68(7): 897-908.
[20]	刘宪锋, 潘耀忠, 朱秀芳, 等, 2015. 2000-2014年秦巴山区植被覆盖时空变化特征及其归因[J]. 地理学报, 70(5): 705-716. DOI
	LIU X F, PAN Y Z, ZHU X F, et al., 2015. Spatiotemporal variation of vegetation coverage in Qinling-Daba Mountains in relation to environmental factors[J]. Acta Geographica Sinica, 70(5): 705-716.
[21]	刘彦随, 李进涛, 2017. 中国县域农村贫困化分异机制的地理探测与优化决策[J]. 地理学报, 72(1): 161-173. DOI
	LIU Y S, LI J T, 2017. Geographic detection and optimizing decision of the differentiation mechanism of rural poverty in China[J]. Acta Geographica Sinica, 72(1): 161-173.
[22]	栾金凯, 刘登峰, 黄强, 等, 2018. 近17年陕西榆林植被指数的时空变化及影响因素[J]. 生态学报, 38(8): 2780-2790.
	LUAN J K, LIU D F, HUANG Q, et al., 2018. Analysis of the spatial- temporal change and impact factors of the vegetation index in Yulin, Shaanxi Province,in the last 17 years[J]. Acta Ecologica Sinica, 38(8): 2780-2790.
[23]	吕渡, 杨亚辉, 赵文慧, 等, 2018. 黄土高原沟壑区不同植被对土壤水分分布特征影响[J]. 水土保持研究, 25(4): 60-64.
	LV D, TANG Y H, ZHAO W H, et al., 2018. Impacts of vegetation types on soil water distributions in Loess Hilly region[J]. Research of Soil and Water Conservation, 25(4): 60-64.
[24]	吕家欣, 李秀芬, 郑晓, 等, 2020. 近40年科尔沁沙地植被时空变化及其驱动力[J]. 生态学杂志, 39(5): 1399-1408.
	LV J X, LI X F, ZHENG X, et al., 2020. Temporal and spatial changes and their driving forces of vegetation cover in Horqin Sandy Land in recent 40 years[J]. Chinese Journal of Ecology, 39(5): 1399-1408.
[25]	庞国伟, 山琳昕, 杨勤科, 等, 2021. 陕西省不同地貌类型区植被覆盖度时空变化特征及其影响因素[J]. 长江科学院院报, 38(3): 51-58, 76.
	PANG G W, SHAN L X, YANG Q K, et al., 2021. Vegetation coverage in different landforms of Shaanxi Province: Spatial and temporal variations and influencing factors[J]. Journal of Yangtze River Scientific Research Institute, 38(3): 51-58, 76.
[26]	彭文甫, 王广杰, 周介铭, 等, 2016. 基于多时相Landsat5/8影像的岷江汶川-都江堰段植被覆盖动态监测[J]. 生态学报, 36(7): 1975-1988.
	PENG W F, WANG G J, ZHOU J M, et al., 2016. Dynamic monitoring of fractional vegetation cover along Minjiang River from Wenchuan County to Dujiangyan city using multi-temporal landsat 5 and 8 images[J]. Acta Ecologica Sinica, 36(7): 1975-1988.
[27]	彭文甫, 张冬梅, 罗艳玫, 等, 2019. 自然因子对四川植被NDVI变化的地理探测[J]. 地理学报, 74(9): 1758-1776. DOI
	PENG W F, ZHANG D M, LUO Y M, et al., 2019. Influence of natural factors on vegetation NDVI using geographical detection in Sichuan Province[J]. Acta Geographica Sinica, 74(9): 1758-1776.
[28]	孙锐, 陈少辉, 苏红波, 2020. 黄土高原不同生态类型NDVI时空变化及其对气候变化响应[J]. 地理研究, 39(5): 1200-1214. DOI
	SUN R, CHEN S H, SU H B, 2020. Spatiotemporal variation of NDVI in different ecotypes on the Loess Plateau and its response to climate change[J]. Geographical Research, 39(5): 1200-1214.
[29]	唐晓灵, 杜莉, 2020. 基于引力模型的区域经济发展与生态环境耦合协调研究--以陕西省为例[J]. 生态经济, 36(7): 164-169.
	TANG X L, DU L, 2020. Research on coupling coordination between regional economic development and ecological environment based on gravity model: Taking Shaanxi Province as an example[J]. Ecological Economy, 36(7): 164-169.
[30]	王建邦, 赵军, 李传华, 等, 2019. 2001-2015年中国植被覆盖人为影响的时空格局[J]. 地理学报, 74(3): 504-519. DOI
	WANG J B, ZHAO J, LI C H, et al., 2019. The spatial-temporal patterns of the impact of human activities on vegetation coverage in China from 2001 to 2015[J]. Acta Geographica Sinica, 74(3): 504-519.
[31]	王劲峰, 徐成东, 2017. 地理探测器:原理与展望[J]. 地理学报, 72(1): 116-134. DOI
	WANG J F, XU C D, 2017. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 72(1): 116-134.
[32]	王涛, 杨梅焕, 2017. 榆林地区植被指数动态变化及其对气候和人类活动的响应[J]. 干旱区研究, 34(5): 1133-1140.
	WANG T, YANG M H, 2017. Dynamic change of NDVI and its response to climate change and human activities in Yulin, Shaanxi Province, China[J]. Arid Zone Research, 34(5): 1133-1140.
[33]	王正兴, 刘闯, HUETE Alfredo, 2003. 植被指数研究进展: 从AVHRR-NDVI到MODIS-EVI[J]. 生态学报, 23(5): 979-987.
	WANG Z X, LIU C, ALFREDO H, 2003. From AVHRR-NDVI to MODIS-EVI: Advances in vegetation index research[J]. Acta Ecologica Sinica, 23(5): 979-987.
[34]	夏安全, 王艳芬, 郝彦宾, 等, 2020. 复杂地形草地植被碳储量遥感估算研究进展[J]. 生态学报, 40(18): 6338-6350.
	XIA A Q, WANG Y F, HAO Y B, et al., 2020. Research progress on estimation of vegetation carbon storage of grassland on complex terrain by remote sensing technology[J]. Acta Ecologica Sinica, 40(18): 6338-6350.
[35]	肖强, 陶建平, 肖洋, 2016. 黄土高原近10年植被覆盖的动态变化及驱动力[J]. 生态学报, 36(23): 7594-7602.
	XIAO Q, TAO J P, XIAO Y, 2016. Dynamic vegetation cover change over the past 10 years on the Loess Plateau, China[J]. Acta Ecologica Sinica, 36(23): 7594-7602.
[36]	杨强, 王运动, 李丽, 等, 2016. 1952-2010年中国人口分布与社会经济发展的时空耦合特征分析[J]. 遥感学报, 20(6): 1424-1434.
	YANG Q, WANG Y D, LI L, et al., 2016. Temporal-spatial coupling analysis between population change trend and socioeconomic development in China from 1952 to 2010 [J]. Journal of remote sensing, 20(6): 1424-1434.
[37]	于璐, 武志涛, 杜自强, 等, 2020. 气候变化背景下京津风沙源区人类活动对植被影响的量化分析[J]. 应用生态学报, 31(6): 2007-2014.
	YU L, WU Z T, DU Z Q, et al., 2020. Quantitative analysis of the effects of human activities on vegetation in the Beijing-Tianjin sandstorm source region under the climate change[J]. Chinese Journal of Applied Ecology, 20(6): 1424-1434.
[38]	榆林市统计局, 2019. 2018年榆林市国民经济和社会发展统计公报. 榆林: 榆林市人民政府 [2021-03-17] http://www.yl.gov.cn/gk/tjxx/ndtjxx/49078.htm.
	Yulin City Statistics Bureau, 2019. 2018 Yulin National Economic and social development statistical bulletin. Yulin:Yulin Municipal People's Government [2021-03-17] http://www.yl.gov.cn/gk/tjxx/ndtjxx/49078.htm.
[39]	赵亮, 刘宇, 罗勇, 等, 2019. 黄土高原近40年人类活动强度时空格局演变[J]. 水土保持研究, 26(4): 306-313.
	ZHAO L, LIU Y, LUO Y, et al., 2019. Temporal and spatial evolution of human impact intensity on the Loess Plateau in recent 40 years[J]. Research of soil and water conservation, 26(4): 306-313.
[40]	赵维清, 李经纬, 褚琳, 等, 2019. 近10年湖北省植被指数时空变化特征及其驱动力[J]. 生态学报, 39(20): 7722-7736.
	ZHAO W Q, LI J W, CHU L, et al., 2019. Analysis of spatial and temporal variations in vegetation index and its driving force in Hubei Province in the last 10 years[J]. Acta Ecologica Sinica, 39(20): 7722-7736.
[41]	郑杰, 冯文兰, 牛晓俊, 等, 2016. 四川省植被变化及其与气象因子的相关性分析[J]. 水土保持通报, 36(2): 99-104, 349-350.
	ZHENG J, FENG W L, NIU X J, et al., 2016. Vegetation change and its correlation with meteorological factors in Sichuan province[J]. Bulletin of Soil and Water Conservation, 36(2): 99-104, 349-350.

地表因素 Surface factors	气候因素 Climatic factors	人文因素 Human factors
坡向 Aspect (X₁)	降水	土地利用类型
坡度 Slope (X₂)	气温	人口密度
土壤类型Soil type (X₃)		GDP (X₈)

地表因素 Surface factors	气候因素 Climatic factors	人文因素 Human factors
坡向 Aspect (X₁)	降水	土地利用类型
坡度 Slope (X₂)	气温	人口密度
土壤类型Soil type (X₃)		GDP (X₈)

年份 Years	2000		2005		2010		2015		2018
NDVI	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%
0-0.2	5540	12.79	933	2.15	226	0.52	215	0.50	73	0.17
0.2-0.4	32308	74.57	19863	45.85	11272	26.02	16178	37.34	4588	10.59
0.4-0.6	4974	11.48	21549	49.74	27874	64.34	24332	56.16	17957	41.45
0.6-0.8	495	1.14	966	2.23	3752	8.66	2527	5.83	20353	46.98
0.8-1	7	0.02	13	0.03	200	0.46	73	0.17	354	0.82

年份 Years	2000		2005		2010		2015		2018
NDVI	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%	面积 Area/km²	比例 Proportion/%
0-0.2	5540	12.79	933	2.15	226	0.52	215	0.50	73	0.17
0.2-0.4	32308	74.57	19863	45.85	11272	26.02	16178	37.34	4588	10.59
0.4-0.6	4974	11.48	21549	49.74	27874	64.34	24332	56.16	17957	41.45
0.6-0.8	495	1.14	966	2.23	3752	8.66	2527	5.83	20353	46.98
0.8-1	7	0.02	13	0.03	200	0.46	73	0.17	354	0.82

	因子 Factors
	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈
q值 q value	0.008	0.141	0.015	0.033	0.208	0.162	0.224	0.183

榆林地区植被时空分异特征及其影响因素研究

Spatio-temporal Variations and Influencing Factors of Vegetation in Yulin

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分区 Partition	A₁	A₂	A₃	A₄	A₅	A₆	A₇	A₈	A₉
A₁
A₂	N
A₃	Y	Y
A₄	Y	Y	Y
A₅	Y	Y	N	Y
A₆	Y	N	Y	Y	Y
A₇	Y	Y	Y	Y	Y	Y
A₈	Y	Y	Y	Y	Y	Y	N
A₉	Y	Y	Y	Y	Y	Y	Y	N
NDVI均值 NDVI mean	0.578	0.602	0.546	0.505	0.545	0.609	0.650	0.655	0.664

分区 Partition	B₁	B₂	B₃	B₄	B₅	B₆	B₇	B₈	B₉
B₁
B₂	N
B₃	Y	N
B₄	Y	Y	N
B₅	Y	Y	N	N
B₆	N	N	N	Y	Y
B₇	N	Y	Y	Y	Y	Y
B₈	Y	Y	Y	Y	Y	Y	N
B₉	N	Y	Y	Y	Y	Y	N	Y
NDVI均值 NDVI mean	0.606	0.578	0.541	0.512	0.502	0.590	0.639	0.661	0.627

自然、人文因子 Natural and human factors	NDVI适应类型或范围 Adaptation type or range of NDVI	NDVI均值 NDVI mean
坡向 Aspect(°)	337.5-22.5	0.595
坡度 Slope(°)	6-15、15-25	0.613
土壤类型 Soil type	钙层土	0.605
降水 Precipitation/mm	520.48-541.71	0.593
气温 Temperature/℃	10.67-10.91	0.650
土地利用类型 Land-use type	耕地、林地	0.614
人口密度 Population density/(person∙km^-2)	100-104	0.664
GDP/(10⁴ yuan∙km^-2)	266-420	0.642

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因子 Factors	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈
X₁	0.008
X₂	0.159	0.141
X₃	0.040	0.195	0.015
X₄	0.085	0.255	0.064	0.033
X₅	0.239	0.324	0.239	0.254	0.208
X₆	0.191	0.306	0.202	0.238	0.307	0.162
X₇	0.257	0.352	0.244	0.322	0.361	0.321	0.224
X₈	0.234	0.277	0.244	0.229	0.285	0.307	0.351	0.183

因子 Factors	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈
X₁	0.008
X₂	0.159	0.141
X₃	0.040	0.195	0.015
X₄	0.085	0.255	0.064	0.033
X₅	0.239	0.324	0.239	0.254	0.208
X₆	0.191	0.306	0.202	0.238	0.307	0.162
X₇	0.257	0.352	0.244	0.322	0.361	0.321	0.224
X₈	0.234	0.277	0.244	0.229	0.285	0.307	0.351	0.183