Variation of NDVI spatio-temporal characteristics and its driving factors based on geodetector model in Horqin Sandy Land, China

doi:10.17521/cjpe.2022.0020

Abstract

Abstract:

Aims Horqin Sandy Land is an important, but highly degraded, agro-pastoral region in the northern China region of Nei Mongol. There have been significant changes in vegetation condition over the past two decades, in response to changes in climate as well as restoration policies. In this study, we characterize the spatial and temporal changes in vegetation in the region over the past twenty years, in order to understand the complex mechanism of vegetation change, and provide a scientific basis for comprehensive management and rational implementation of ecological engineering in the future.

Methods We assessed the correlation between a time series of Normalized Difference Vegetation Index (NDVI) (derived from MODIS) from 2001 to 2020 with 10 key driving factors (including mean annual temperature, mean annual precipitation, slope, soil type, vegetation type, geomorphic type, population density, accumulated afforestation area, livestock density, and crops area) in space on random sampling points, which were generated in ArcGIS software. Geodetector model was used to explore the individual relationships as well as their interactions.

Important findings The results demonstrated that: (1) over the past 20 years, the vegetation coverage of Horqin Sandy Land has been gradually recovering, primarily in the northern, central and southeastern marginal areas of the study area, recovery area accounted for more than 64.91%. (2) Changes in NDVI were primarily explained in Horqin Sandy Land by variation in three factors, soil type, geomorphic type, and mean annual temperature. (3) The interactions between explanatory factors were nonlinearly and mutually enhanced, of these, there was a strong interaction between soil type and other factors. (4) Increases in vegetation cover in Horqin Sandy Land was primarily observed in association with alfisol, hills or small undulating mountains, and annual average temperature ranges 4.68-5.67 °C and so on. Future restoration programs may want to prioritize sites with these conditions.

Key words: Normalized Difference Vegetation Index (NDVI), geodetector model, driving factor, vegetation restoration, Horqin Sandy Land

CHEN Xue-Ping, ZHAO Xue-Yong, ZHANG Jing, WANG Rui-Xiong, LU Jian-Nan. Variation of NDVI spatio-temporal characteristics and its driving factors based on geodetector model in Horqin Sandy Land, China[J]. Chin J Plant Ecol, 2023, 47(8): 1082-1093.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2022.0020

https://www.plant-ecology.com/EN/Y2023/V47/I8/1082

Figures/Tables 10

References 51

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类型 Type	驱动因子 Driving factor	指标 Index	单位 Unit	数据来源 Data resource
自然因素 Natural factor	X₁	年平均气温 Mean annual temperature	℃	中国气象数据共享网 China Meteorological Data Service Center http://www.nmic.cn/
	X₂	年降水量 Mean annual precipitation	mm	中国气象数据共享网 China Meteorological Data Service Center http://www.nmic.cn/
	X₃	坡度 Slope	。	美国NASA获取的SRTM 30 m DEM数据 SRTM 30 m DEM data acquired by NASA https://nasasearch.nasa.gov/
	X₄	土壤类型 Soil type	-	中国科学院资源环境科学与数据中心 Resource and Environment Science and Data Center, Chinese Academy of Sciences (CAS) https://www.resdc.cn/
	X₅	植被类型 Vegetation type	-	中国科学院资源环境科学与数据中心 Resource and Environment Science and Data Center, CAS https://www.resdc.cn/
	X₆	地貌类型 Geomorphic type	-	中国科学院资源环境科学与数据中心 Resource and Environment Science and Data Center, CAS https://www.resdc.cn/
人为因素 Anthropogenic factor	X₇	人口密度 Population density	人·km^-2 person·km^-2	内蒙古自治区统计年鉴 Inner Mongolia Statistical Yearbook http://tj.nmg.gov.cn/tjyw/jpsj/
	X₈	累积造林面积 Accumulated afforestation area	hm²·km^-2	中国林业统计年鉴 China Forestry Statistical Yearbook https://www.tongjinianjian.com/111453.html
	X₉	牲畜密度 Livestock density	头·km^-2 head·km^-2	内蒙古自治区统计年鉴 Inner Mongolia Statistical Yearbook http://tj.nmg.gov.cn/tjyw/jpsj/
	X₁₀	农作物种植面积 Crops area	hm²·km^-2	内蒙古自治区统计年鉴 Inner Mongolia Statistical Yearbook http://tj.nmg.gov.cn/tjyw/jpsj/

类型 Type	驱动因子 Driving factor	指标 Index	单位 Unit	数据来源 Data resource
自然因素 Natural factor	X₁	年平均气温 Mean annual temperature	℃	中国气象数据共享网 China Meteorological Data Service Center http://www.nmic.cn/
	X₂	年降水量 Mean annual precipitation	mm	中国气象数据共享网 China Meteorological Data Service Center http://www.nmic.cn/
	X₃	坡度 Slope	。	美国NASA获取的SRTM 30 m DEM数据 SRTM 30 m DEM data acquired by NASA https://nasasearch.nasa.gov/
	X₄	土壤类型 Soil type	-	中国科学院资源环境科学与数据中心 Resource and Environment Science and Data Center, Chinese Academy of Sciences (CAS) https://www.resdc.cn/
	X₅	植被类型 Vegetation type	-	中国科学院资源环境科学与数据中心 Resource and Environment Science and Data Center, CAS https://www.resdc.cn/
	X₆	地貌类型 Geomorphic type	-	中国科学院资源环境科学与数据中心 Resource and Environment Science and Data Center, CAS https://www.resdc.cn/
人为因素 Anthropogenic factor	X₇	人口密度 Population density	人·km^-2 person·km^-2	内蒙古自治区统计年鉴 Inner Mongolia Statistical Yearbook http://tj.nmg.gov.cn/tjyw/jpsj/
	X₈	累积造林面积 Accumulated afforestation area	hm²·km^-2	中国林业统计年鉴 China Forestry Statistical Yearbook https://www.tongjinianjian.com/111453.html
	X₉	牲畜密度 Livestock density	头·km^-2 head·km^-2	内蒙古自治区统计年鉴 Inner Mongolia Statistical Yearbook http://tj.nmg.gov.cn/tjyw/jpsj/
	X₁₀	农作物种植面积 Crops area	hm²·km^-2	内蒙古自治区统计年鉴 Inner Mongolia Statistical Yearbook http://tj.nmg.gov.cn/tjyw/jpsj/

交互作用类型 Interaction type	q值关系 q value relationship
非线性减弱 Non-linear reduction	q(X₁∩X₂) < min(q(X₁), q(X₂))
单因子非线性减弱 Single factor non-linear reduction	min(q(X₁), q(X₂)) < q(X₁∩X₂) < max(q(X₁), q(X₂))
双因子增强 Bi-factor enhancement	q(X₁∩X₂) > max(q(X₁), q(X₂))
独立 Independent	q(X₁∩X₂) = q(X₁) + q(X₂)
非线性增强 Non-linear enhancement	q(X₁∩X₂) > q(X₁) + q(X₂)

交互作用类型 Interaction type	q值关系 q value relationship
非线性减弱 Non-linear reduction	q(X₁∩X₂) < min(q(X₁), q(X₂))
单因子非线性减弱 Single factor non-linear reduction	min(q(X₁), q(X₂)) < q(X₁∩X₂) < max(q(X₁), q(X₂))
双因子增强 Bi-factor enhancement	q(X₁∩X₂) > max(q(X₁), q(X₂))
独立 Independent	q(X₁∩X₂) = q(X₁) + q(X₂)
非线性增强 Non-linear enhancement	q(X₁∩X₂) > q(X₁) + q(X₂)

分级 Class	X₁(℃)	X₂(mm)	X₃(°)	X₄	X₅	X₆	X₇(person·km^-2)	X₈(hm²·km^-2)	X₉(head·km^-2)	X₁₀(hm²·km^-2)
1	4.68-5.67	462.77-492.69	0-2	淋溶土 Alfisol	针叶林 Needle leaf forest	平原 Plain	17.67-41.26	1.69-2.94	8.99-70.65	13.30-13.40
2	5.67-6.45	492.69-511.24	2-3	钙层土 Pedocal	阔叶林 Broadleaf forest	台地 Platform	41.26-49.39	2.94-4.41	70.65-96.30	13.40-16.09
3	6.45-7.07	511.24-529.69	3-5	初育土 Primary	灌丛 Shrub	丘陵 Hill	49.39-56.81	4.41-4.89	96.30-110.69	16.09-18.02
4	7.07-7.66	529.69-547.57	5-8	半水成土 Semi- hydromorph	草原 Steppe	小起伏山地 Small undulating mountain	56.81-67.65	4.89-5.14	110.69-118.50	18.02-18.89
5	7.66-8.22	547.57-566.55	8-10	水成土 Hydromorph	草甸 Meadow	中起伏山地 Middle undulating mountain	67.65-86.71	5.14-5.29	118.50-128.85	18.89-20.18
6	8.22-8.72	566.55-587.78	10-13	盐碱土 Saline-alkali	人工林Artificial forest		86.71-132.62	5.29-5.56	128.85-141.48	20.18-21.56
7	8.72-9.32	587.78-628.31	13-15	湖泊水库 Lakes and reservoirs			132.62-260.95	5.56-7.89	141.48-224.26	21.56-33.17
8			15-17	河流 Rivers
9			17-30	河内沙洲 Sandbank