Spatiotemporal variation and its driving mechanism of photosynthetic vegetation in the Loess Plateau from 2001 to 2020

doi:10.17521/cjpe.2021.0444

Abstract

Abstract:

Aims The objectives of this study were to reveal the changing trends and regional differences of vegetation fractional coverage on the Loess Plateau 20 years after the implementation of the “Grain for Green (GFG)” policy, and to quantify the contribution of climate and human activities to the change of vegetation fractional coverage and its spatial distribution in the region.

Methods The spatial and temporal variation of photosynthetic vegetation (PV) fractional coverage on the Loess Plateau from 2001 to 2020 and its drivers and contributions were analyzed based on MODIS-PV and meteorological data, and using the methods of the Mann-Kendall method, the Sen estimator, and multivariate residual trend analysis.

Important findings Regional vegetation fractional coverage increased from 40% in 2001 to 60% in 2020. Vegetation fractional coverage of the Loess Plateau showed a significant increasing trend over 20 years, with an increasing rate of 0.8%·a^-1. The proportion of the area with an increasing trend of vegetation fractional coverage for the entire region was 90%, and the proportion of the area with a significant increase was 71%. The contribution to the increase of vegetation fractional coverage in the region was mainly in the loess hilly region (2/5), followed by the sandy hilly region (1/4) and the rocky mountain region (1/5). Within the different geomorphology divisions, vegetation fractional coverage in the loess hilly region increased rapidly in Yulin and Yanʼan in Shaanxi. Vegetation fractional coverage in Ordos, Nei Mongol, changed the fastest in the sandy hilly region. Human activities and climate change contributed 76% and 24%, respectively, to the increase of vegetation fractional coverage on the Loess Plateau during the study period. The areas where human activities contributed positively to vegetation fractional coverage were mainly located in the loess hilly and sandy hilly regions in the northern part of Yanʼan in Shaanxi, the southern part of Taiyuan in Shanxi, the southern part of Tongxin in Ningxia, and the hills and plateaus of Pingliang and Qingyang in Gansu where the ecological projects funded by the Chinese government have been well implemented.

Key words: Loess Plateau, vegetation fractional coverage, spatial and temporal variation, human activities, residual analysis

HE Jie, HE Liang, LÜ Du, CHENG Zhuo, XUE Fan, LIU Bao-Yuan, ZHANG Xiao-Ping. Spatiotemporal variation and its driving mechanism of photosynthetic vegetation in the Loess Plateau from 2001 to 2020[J]. Chin J Plant Ecol, 2023, 47(3): 306-318.

Add to citation manager EndNote|Ris|BibTeX

URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2021.0444

https://www.plant-ecology.com/EN/Y2023/V47/I3/306

Figures/Tables 9

References 55

[1]	Cai BF, Yu R (2009). Advance and evaluation in the long time series vegetation trends research based on remote sensing. Journal of Remote Sensing, 13, 1170-1186.
	[蔡博峰, 于嵘 (2009). 基于遥感的植被长时序趋势特征研究进展及评价. 遥感学报, 13, 1170-1186.]
[2]	Chen N, Li TB, Zhang XP, Chou SR, Xie ML, Liu EJ (2013). Spatiotemporal variations of vegetation coverage in Beiluo River watershed based on remote sensing data analysis. Bulletin of Soil and Water Conservation, 33, 206-210.
	[陈妮, 李谭宝, 张晓萍, 丑述仁, 谢名礼, 刘二佳 (2013). 北洛河流域植被覆盖度时空变化的遥感动态分析. 水土保持通报, 33, 206-210.]
[3]	Daughtry CST (2001). Discriminating crop residues from soil by shortwave infrared reflectance. Agronomy Journal, 93, 125-131. DOI URL
[4]	Dong Y, Yin DQ, Li Y, Yan TL, Wang HS (2020). Spatio- temporal patterns of vegetation change and driving forces in the Loess Plateau. Journal of China Agricultural University, 25(8), 120-131.
	[董镱, 尹冬勤, 李渊, 严泰来, 王红说 (2020). 黄土高原植被的时空变化及其驱动力分析研究. 中国农业大学学报, 25(8), 120-131.]
[5]	Evans J, Geerken R (2004). Discrimination between climate and human-induced dryland degradation. Journal of Arid Environments, 57, 535-554. DOI URL
[6]	Feng Q, Zhao W, Ding J, Fang X, Zhang X (2018). Estimation of the cover and management factor based on stratified coverage and remote sensing indices: a case study in the Loess Plateau of China. Journal of Soils and Sediments, 18, 775-790. DOI URL
[7]	Guan K, Wood EF, Caylor KK (2012). Multi-sensor derivation of regional vegetation fractional cover in Africa. Remote Sensing of Environment, 124, 653-665. DOI URL
[8]	Guerschman JP, Hill MJ, Renzullo LJ, Barrett DJ, Marks AS, Botha EJ (2009). Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors. Remote Sensing of Environment, 113, 928-945. DOI URL
[9]	Guerschman JP, Scarth PF, McVicar TR, Renzullo LJ, Malthus TJ, Stewart JB, Rickards JE, Trevithick R (2015). Assessing the effects of site heterogeneity and soil properties when unmixing photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions from Landsat and MODIS data. Remote Sensing of Environment, 161, 12-26. DOI URL
[10]	Guo MJ, Zhang TT, Zhang JJ, Chen LL, Zhang XP (2014). Response of vegetation coverage to climate change in the Loess Plateau in 1982-2006. Research of Soil and Water Conservation, 21(5), 35-40.
	[郭敏杰, 张亭亭, 张建军, 陈利利, 张晓萍 (2014). 1982-2006年黄土高原地区植被覆盖度对气候变化的响应. 水土保持研究, 21(5), 35-40.]
[11]	Guo YQ, Wang NJ, Chu XS, Li C, Luo XQ, Feng H (2019). Analyzing vegetation coverage changes and its reasons on the Loess Plateau based on Google Earth Engine. China Environmental Science, 39, 4804-4811.
	[郭永强, 王乃江, 褚晓升, 李成, 罗晓琦, 冯浩 (2019). 基于Google Earth Engine分析黄土高原植被覆盖变化及原因. 中国环境科学, 39, 4804-4811.]
[12]	He L, Lyu D, Guo JW, Lei SY, He J, Zhang XP, Yang XH (2020). Study on vegetation coverage change of Beiluo River Basin based on MODIS. Yellow River, 42(2), 67-71.
	[何亮, 吕渡, 郭晋伟, 雷斯越, 贺洁, 张晓萍, 杨希华 (2020). 基于MODIS的北洛河流域植被盖度变化研究. 人民黄河, 42(2), 67-71.]
[13]	Hill MJ, Guerschman JP (2020). The MODIS global vegetation fractional cover product 2001-2018: characteristics of vegetation fractional cover in grasslands and savanna woodlands. Remote Sensing, 12, 406. DOI: 10.3390/rs12030406. DOI
[14]	Hirsch RM, Slack JR, Smith RA (1982). Techniques of trend analysis for monthly water quality data. Water Resources Research, 18, 107-121. DOI URL
[15]	Huang BW (1955). Lessons learned from the development of a soil erosion zoning map for the Middle Yellow River Basin. Chinese Science Bulletin, (12), 15-21.
	[黄秉维 (1955). 编制黄河中游流域土壤侵蚀分区图的经验教训. 科学通报, (12), 15-21.]
[16]	Ji YH, Zhou GS, Wang SD, Wang LX, Zhou MZ (2021). Evolution characteristics and its driving forces analysis of vegetation ecological quality in Qinling Mountains region from 2000 to 2019. Chinese Journal of Plant Ecology, 45, 617-625. DOI URL
	[汲玉河, 周广胜, 王树东, 王丽霞, 周梦子 (2021). 2000-2019年秦岭地区植被生态质量演变特征及驱动力分析. 植物生态学报, 45, 617-625.]
[17]	Jin K, Wang F, Han JQ, Shi SY, Ding WB (2020). Contribution of climatic change and human activities to vegetation NDVI change over China during 1982-2015. Acta Geographica Sinica, 75, 961-974. DOI
	[金凯, 王飞, 韩剑桥, 史尚渝, 丁文斌 (2020). 1982-2015年中国气候变化和人类活动对植被NDVI变化的影响. 地理学报, 75, 961-974.] DOI
[18]	Jing K (1985). Approach to the erosion zonalization of the Loess Plateau. Mountain Research, 3(3), 161-165.
	[景可 (1985). 黄土高原侵蚀分区探讨. 山地研究, 3(3), 161-165.]
[19]	Kendall MG (1990). Rank Correlation Measures. 4th ed. Charles Griffin, London.
[20]	Kim Y, Yang Z, Cohen WB, Pflugmacher D, Lauver CL, Vankat JL (2009). Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-footprint lidar data. Remote Sensing of Environment, 113, 2499-2510. DOI URL
[21]	Li T, Lü YH, Ren YJ, Li PF (2020). Gauging the effectiveness of vegetation restoration and the influence factors in the Loess Plateau. Acta Ecologica Sinica, 40, 8593-8605.
	[李婷, 吕一河, 任艳姣, 李朋飞 (2020). 黄土高原植被恢复成效及影响因素. 生态学报, 40, 8593-8605.]
[22]	Liu B, Zhang K, Yun X (2002). An empirical soil loss equation //Proceedings 12th International Soil Conservation Organization Conference: Process of Soil Erosion and Its Environment Effect II. Qinghua University Press, Beijing. 21-25.
[23]	Liu MX, Zhao RD, Shao P, Jiao J, Li LR, Che YD (2018). Temporal and spatial variation of vegetation coverage and its driving forces in the Loess Plateau from 2001 to 2015. Arid Land Geography, 41, 99-108.
	[刘旻霞, 赵瑞东, 邵鹏, 焦骄, 李俐蓉, 车应弟 (2018). 近15 a黄土高原植被覆盖时空变化及驱动力分析. 干旱区地理, 41, 99-108.]
[24]	Liu XQ, Zhao JB, Yu XF (2006). Study on the climatic warming-drying trend in the Loess Plateau and the countermeasures. Arid Zone Research, 23, 627-631.
	[刘晓清, 赵景波, 于学峰 (2006). 黄土高原气候暖干化趋势及适应对策. 干旱区研究, 23, 627-631.]
[25]	Liu XY, Gao YF, Yang ST, Luo Y (2016). The Causes of the Sharp Decrease in Water and Sand in the Yellow River in Recent Years. Science Press, Beijing.
	[刘晓燕, 高云飞, 杨胜天, 罗娅 (2016). 黄河近年水沙锐减成因. 科学出版社, 北京.]
[26]	Ma F, Zhuo J, He HJ, Han SS (2020). Ecological evolution and driving mechanism of vegetation in Yulin City, Shaanxi Province. Bulletin of Soil and Water Conservation, 40(5), 257-261.
	[马锋, 卓静, 何慧娟, 韩姗姗 (2020). 陕西省榆林市植被生态演变及其驱动机制. 水土保持通报, 40(5), 257-261.]
[27]	Ma QM, Long YP, Jia XP, Wang HB, Li YS (2019). Vegetation response to climatic variation and human activities on the Ordos Plateau from 2000 to 2016. Environmental Earth Sciences, 78, 701-709. DOI
[28]	Mann HB (1945). Nonparametric tests against trend. Econometrica, 13, 245-259. DOI URL
[29]	National Bureau of Statistics (2020). China Statistical Yearbook (County-Level)-2020. China Statistics Press, Beijing.
	[国家统计局 (2020). 中国县域统计年鉴(县市卷)-2020. 中国统计出版社, 北京.]
[30]	National Forestry and Grassland Administration (2019). China Forestry and Grassland Statistical Yearbook. China Forestry Publishing House, Beijing.
	[国家林业和草原局 (2019). 中国林业和草原统计年鉴. 中国林业出版社, 北京.]
[31]	Newnham GJ, Verbesselt J, Grant IF, Anderson SAJ (2011). Relative Greenness Index for assessing curing of grassland fuel. Remote Sensing of Environment, 115, 1456-1463. DOI URL
[32]	Ouyang D, Yuan N, Sheu L, Lau G, Chen C, Lai CJ (2013). Community health education at student-run clinics leads to sustained improvement in patientsʼ hepatitis B knowledge. Journal of Community Health, 38, 471-479. DOI PMID
[33]	Schimel DS (1995). Terrestrial biogeochemical cycles: global estimates with remote sensing. Remote Sensing of Environment, 51, 49-56. DOI URL
[34]	Sen PK (1968). Estimates of the regression coefficient based on Kendallʼs tau. Journal of the American Statistical Association, 63, 1379-1389. DOI URL
[35]	Shi H, Shao MA (2000). Soil and water loss from the Loess Plateau in China. Journal of Arid Environments, 45, 9-20. DOI URL
[36]	Sun R, Chen SH, Su HB (2019). Spatiotemporal variations of NDVl of different land cover types on the Loess Plateau from 2000 to 2016. Progress in Geography, 38, 1248-1258.
	[孙锐, 陈少辉, 苏红波 (2019). 2000-2016年黄土高原不同土地覆盖类型植被NDVI时空变化. 地理科学进展, 38, 1248-1258.] DOI
[37]	Sun WY, Song XY, Mu XM, Gao P, Wang F, Zhao GJ (2015). Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau. Agricultural and Forest Meteorology, 209- 210, 87-99.
[38]	The Integrated Scientific Research Team of Loess Plateau of Chinese Academy of Sciences (2001). Socio-economic Dataset on the Loess Plateau Regionʼs Resources and Environment. China Economy Publishing House, Beijing.
	[中国科学院黄土高原综合科学考察队 (1992). 黄土高原地区资源环境社会经济数据集. 中国经济出版社, 北京.]
[39]	Tian ZH, Ren ZG, Wei HT (2021). Driving mechanism of the spatiotemporal evolution of vegetation in the Yellow River Basin from 2000 to 2020. Environmental Science, 43, 743-751. DOI URL
	[田智慧, 任祖光, 魏海涛 (2021). 2000-2020 年黄河流域植被时空演化驱动机制. 环境科学, 43, 743-751.]
[40]	Tucker CJ, Slayback DA, Pinzon JE, Los SO, Myneni RB, Taylor MG (2001). Higher northern latitude normalized difference vegetation index and growing season trends from 1982 to 1999. International Journal of Biometeorology, 45(4), 184-190. PMID
[41]	Wang J, Xie YW, Wang XY, Guo KM (2020). Driving factors of recent vegetation changes in Hexi region, northwest China based on a new classification framework. Remote Sensing, 12, 1758. DOI: 10.3390/rs12111758. DOI
[42]	Wang JF, He L, Lu SJ, Lü D, Huang T, Cao Q, Zhang XP, Liu BY (2020). Photosynthetic vegetation cover response to precipitation on the Inner Mongolian Steppe. Acta Ecologica Sinica, 40, 5620-5629.
	[王举凤, 何亮, 陆绍娟, 吕渡, 黄涛, 曹琦, 张晓萍, 刘宝元 (2020). 内蒙古不同类型草原光合植被覆盖度对降水变化的响应. 生态学报, 40, 5620-5629.]
[43]	Wessels KJ, Prince SD, Malherbe J, Small J, Frost PE, VanZyl D (2007). Can human-induced land degradation be distinguished from the effects of rainfall variability? A case study in South Africa. Journal of Arid Environments, 68, 271-297. DOI URL
[44]	Wischmeier WH, Smith DD (1978). Predicting Rainfall Erosion Losses—A Guide to Conservation Planning. U.S. Department of Agriculture, Washington D.C.
[45]	Xin ZB, Xu JX, Zheng W (2007). Contribution of climate change and human activities on vegetation cover change on the Loess Plateau. Scientia Sinica (Terrae), 37, 1504-1514.
	[信忠保, 许炯心, 郑伟 (2007). 气候变化和人类活动对黄土高原植被覆盖变化的影响. 中国科学(地球科学), 37, 1504-1514.]
[46]	Yan R, Zhang XP, Yan SJ, Zhao WH (2016). Topographical distribution characteristics of vegetation restoration in the Beiluo River Basin from 1995 to 2014. Journal of Northeastern University (Natural Science), 37, 1598-1603.
	[闫瑞, 张晓萍, 闫胜军, 赵文慧 (2016). 1995-2014 年北洛河流域植被恢复的地形分布特征. 东北大学学报(自然科学版), 37, 1598-1603.] DOI
[47]	Yang QK, Song GQ, Li R (1992). Approaches to land resurces surveying of Loess Plateau. Research of Soil and Water Conservation, (2), 13-25.
	[杨勤科, 宋桂琴, 李锐 (1992). 黄土高原土地资源调查中几个问题的讨论. 水土保持研究, (2), 13-25.]
[48]	Yang WZ, Tian JL (2004). Essential exploration of soil aridization in Loess Plateau. Acta Pedologica Sinica, 41, 1-6.
	[杨文治, 田均良 (2004). 黄土高原土壤干燥化问题探源. 土壤学报, 41, 1-6.]
[49]	Yang XH, Zhang XP, Lv D, Yin SQ, Zhang MX, Zhu QGZ, Yu Q, Liu BY (2020). Remote sensing estimation of the soil erosion cover-management factor for Chinaʼs Loess Plateau. Land Degradation & Development, 31, 1942-1955. DOI URL
[50]	Yi L, Ren ZY, Zhang C, Liu W (2014). Vegetation cover, climate and human activities on the Loess Plateau. Resources Science, 36, 166-174.
	[易浪, 任志远, 张翀, 刘雯 (2014). 黄土高原植被覆盖变化与气候和人类活动的关系. 资源科学, 36, 166-174.]
[51]	Zhang LY, Li X, Feng JH, Rao RG, He TY, Chen Y (2021). Spatial-temporal changes of NDVl in Yellow River Basin and its dual response to climate change and human activities during 2000-2018. Bulletin of Soil and Water Conservation, 41(5), 276-286.
	[张乐艺, 李霞, 冯京辉, 饶日光, 何天英, 陈瑜 (2021). 2000-2018年黄河流域NDVI时空变化及其对气候和人类活动的双重响应. 水土保持通报, 41(5), 276-286.]
[52]	Zhang SL, Yu YM (1994). Methodology for Calculating the Benefits of Water and Soil Conservation for Water and Sand Reduction. China Environmental Press, Beijing.
	[张胜利, 于一鸣 (1994). 水土保持减水减沙效益计算方法. 中国环境科学出版社, 北京.]
[53]	Zhang Y, Liu BY, Shi PJ, Jiang ZS (2001). Crop cover factor estimating for soil loss prediction. Acta Ecologica Sinica, 21, 1050-1056.
	[张岩, 刘宝元, 史培军, 江忠善 (2001). 黄土高原土壤侵蚀作物覆盖因子计算. 生态学报, 21, 1050-1056.]
[54]	Zhao AZ, Liu XF, Zhu XF, Pan YZ, Chen SC (2016). Spatiotemporal analyses and associated driving forces of vegetation coverage change in the Loess Plateau. China Environmental Science, 36, 1568-1578.
	[赵安周, 刘宪锋, 朱秀芳, 潘耀忠, 陈抒晨 (2016). 2000-2014 年黄土高原植被覆盖时空变化特征及其归因. 中国环境科学, 36, 1568-1578.]
[55]	Zhu XM (1991). The formation of Loess Plateau and its harnessing measures. Bulletin of Soil and Water Conservation, 11(1), 1-8.
	[朱显谟 (1991). 黄土高原的形成与整治对策. 水土保持通报, 11(1), 1-8.]

Slope (VFC_O)	驱动要素 Driven factor	划分标准 Standard		贡献率估算依据 Contribution margin estimation basis
Slope (VFC_O)	驱动要素 Driven factor	Slope (VFC_C)	Slope (VFC_H)	气候变化 Climate changes (C)	人类活动 Human activities (H)
>0 (改善 Improvement)	C & H	>0	>0	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{C}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{H}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$
	C	>0	<0	100	0
	H	<0	>0	0	100
<0 (抑制 Inhibition)	C & H	<0	<0	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{C}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{H}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$
	C	<0	>0	100	0
	H	>0	<0	0	100

Slope (VFC_O)	驱动要素 Driven factor	划分标准 Standard		贡献率估算依据 Contribution margin estimation basis
Slope (VFC_O)	驱动要素 Driven factor	Slope (VFC_C)	Slope (VFC_H)	气候变化 Climate changes (C)	人类活动 Human activities (H)
>0 (改善 Improvement)	C & H	>0	>0	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{C}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{H}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$
	C	>0	<0	100	0
	H	<0	>0	0	100
<0 (抑制 Inhibition)	C & H	<0	<0	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{C}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$	$\frac{\text{Slope }(\text{VF}{{\text{C}}_{\text{H}}})}{\text{Slope }(\text{VF}{{\text{C}}_{\text{O}}})}$
	C	<0	>0	100	0
	H	>0	<0	0	100

地貌区 Geomorphological area	C (%)	区内市(省) City (province) in the zones	Slope_i (%)	P_i (%)	C_i (%)
黄土丘陵 Loess-hilly	40	榆林(陕西) Yulin (Shaanxi)	1.2	17	18
		延安(陕西) Yan?an (Shaanxi)	1.4	10	11
		庆阳(甘肃) Qingyang (Gansu)	1.2	9	9
		吕梁(山西) Lüliang (Shanxi)	1.3	7	8
		定西(甘肃) Dingxi (Gansu)	1.3	6	7
		固原(宁夏) Guyuan (Ningxia)	1.6	5	6
		天水(甘肃) Tianshui (Gansu)	1.3	5	6
风沙丘陵 Sandy-hilly	23	鄂尔多斯(内蒙古) Ordos (Nei Mongol)	0.5	57	45
		榆林(陕西) Yulin (Shaanxi)	1.1	11	17
		白银(甘肃) Baiyin (Gansu)	0.8	11	13
		吴忠(宁夏) Wuzhong (Ningxia)	0.8	7	9
		兰州(甘肃) Lanzhou (Gansu)	0.9	6	8
石质山区 Rocky-mountain	18	忻州(山西) Xinzhou (Shanxi)	0.8	8	9
		延安(陕西) Yan?an (Shaanxi)	0.6	8	8
		临汾(山西) Linfen (Shanxi)	0.9	4	6
黄土塬 Loess-tableland	8	庆阳(甘肃) Qingyang (Gansu)	1.1	23	26
		平凉(甘肃) Pingliang (Gansu)	1.3	11	15
		延安(陕西) Yan?an (Shaanxi)	0.9	14	14
		咸阳(陕西) Xianyang (Shaanxi)	1.0	13	13
		临汾(山西) Linfen (Shanxi)	1.2	9	11

地貌区 Geomorphological area	C (%)	区内市(省) City (province) in the zones	Slope_i (%)	P_i (%)	C_i (%)
黄土丘陵 Loess-hilly	40	榆林(陕西) Yulin (Shaanxi)	1.2	17	18
		延安(陕西) Yan?an (Shaanxi)	1.4	10	11
		庆阳(甘肃) Qingyang (Gansu)	1.2	9	9
		吕梁(山西) Lüliang (Shanxi)	1.3	7	8
		定西(甘肃) Dingxi (Gansu)	1.3	6	7
		固原(宁夏) Guyuan (Ningxia)	1.6	5	6
		天水(甘肃) Tianshui (Gansu)	1.3	5	6
风沙丘陵 Sandy-hilly	23	鄂尔多斯(内蒙古) Ordos (Nei Mongol)	0.5	57	45
		榆林(陕西) Yulin (Shaanxi)	1.1	11	17
		白银(甘肃) Baiyin (Gansu)	0.8	11	13
		吴忠(宁夏) Wuzhong (Ningxia)	0.8	7	9
		兰州(甘肃) Lanzhou (Gansu)	0.9	6	8
石质山区 Rocky-mountain	18	忻州(山西) Xinzhou (Shanxi)	0.8	8	9
		延安(陕西) Yan?an (Shaanxi)	0.6	8	8
		临汾(山西) Linfen (Shanxi)	0.9	4	6
黄土塬 Loess-tableland	8	庆阳(甘肃) Qingyang (Gansu)	1.1	23	26
		平凉(甘肃) Pingliang (Gansu)	1.3	11	15
		延安(陕西) Yan?an (Shaanxi)	0.9	14	14
		咸阳(陕西) Xianyang (Shaanxi)	1.0	13	13
		临汾(山西) Linfen (Shanxi)	1.2	9	11