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Remote Sensing for Natural Resources    2025, Vol. 37 Issue (3) : 192-202     DOI: 10.6046/zrzyyg.2024011
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Exploring the dynamic evolution of vegetation cover in Xichuan County, Henan Province by integrating multisource remote sensing data
GE Liling1(), WANG Lu2()
1. Henan Provincial National Land Space Survey and Planning Institute, Zhengzhou 450016, China
2. School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
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Abstract  

Xichuan County serves as a primary water source area for the middle route of the South-to-North Water Diversion Project. Investigating the spatiotemporal variations and driving mechanism of vegetation cover in Xichuan County is significant for the ecological restoration of the county and the environmental protection of the water source area for the middle route. Based on available Landsat and MODIS data, this study constructed long time-series fractional vegetation cover (FVC) data for Xichuan County from 2002 to 2022 using the spatiotemporal adaptive reflection fusion model (STARFM) and the dimidiate pixel model. In combination with regression and trend analyses, the geodetector model, and correlation analysis, this study explored the spatiotemporal variations and driving mechanism of vegetation cover in Xichuan County during the study period. The results indicate that the coefficient of determination (R2) between the STARFM-reconstructed and real annual-scale FVC reached 0.914, an improvement of 0.05 compared to 0.864 under conditions of data missing. Therefore, the STARFM can provide a reliable data basis for more accurately investigating the dynamic evolution of vegetation cover in Xichuan County. From 2002 to 2022, the vegetation cover in Xichuan County was ordinary, with an average FVC value of 0.516, characterized by higher vegetation cover in the northwest compared to the southeast. The vegetation cover in Xichuan County showed an overall improvement trend, with an improved area representing 76.02 %, primarily covering the northwestern and southeastern portions of Xichuan County. In contrast, the degraded area represented 23.98 %, primarily covering the areas surrounding the Danjiangkou reservoir, Danjiang River, and Xishui branch. The spatial heterogeneity of vegetation cover in Xichuan County was predominantly influenced by elevation and slope, followed by soil type and average temperature, with minimal impacts from soil texture and average rainfall. The improvement and degradation of vegetation cover in Xichuan County were principally caused by anthropogenic factors, with minimal influence from climate factors. The primary anthropogenic factor denotes the middle route of the South-to-North Water Diversion Project, which contributed significantly to vegetation growth rather than inhibitory effects.
Keywords Xichuan County      middle route of the South-to-North Water Diversion Project      spatiotemporal adaptive reflection fusion model (STARFM)      fractional vegetation cover (FVC)     
ZTFLH:  TP79  
Issue Date: 01 July 2025
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Liling GE
Lu WANG
Cite this article:   
Liling GE,Lu WANG. Exploring the dynamic evolution of vegetation cover in Xichuan County, Henan Province by integrating multisource remote sensing data[J]. Remote Sensing for Natural Resources, 2025, 37(3): 192-202.
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https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024011     OR     https://www.gtzyyg.com/EN/Y2025/V37/I3/192
Fig.1  Geographic location of the study area
波段类型 Landsat4—5 TM Landsat7 ETM+ Landsat8—9 OLI
波段 波长/μm 波段 波长/μm 波段 波长/μm
近红外
(NIR)		 B4 0.76~0.90 B4 0.76~0.96 B5 0.85~0.88
红波段
(Red)		 B3 0.63~0.69 B3 0.62~0.69 B4 0.64~0.67
Tab.1  Detailed description of the used bands of Landsat data
波段 波长/μm
B2 0.84~0.87
B1 0.62~0.67
Tab.2  Detailed description of MOD13Q1 data
月份 2002年 2004年 2006年 2008年 2010年 2012年 2014年 2016年 2018年 2020年 2022年
4 04/02 — 04/29 04/26 04/16 — — 04/16 04/06 — —
5 05/04 05/17 05/23 05/12 05/02 — 05/29 — — — 05/03
6 06/13 — 06/16 06/05 — — — 06/27 08/14 06/30 06/28
7 07/07 07/04 — — — 09/04 07/08 07/29 — — —
8 08/16 — — — — — — — — 08/09 —
9 09/01 09/22 — 08/09 — — — 09/23 — 09/18 —
10 10/27 10/08 10/14 — — — — — — — 10/18
Tab.3  Landsat image dataset information
月份 2002年 2004年 2006年 2008年 2010年 2012年 2014年 2016年 2018年 2020年 2022年
4 — 04/06 — — — 04/06 04/07 — — 04/06 04/07
5 — — — — — 05/08 — 05/08 05/09 05/08 —
6 — 06/09 — — 06/10 06/09 06/10 — — — —
7 — — 07/12 07/11 07/12 — — — 07/12 07/11 07/12
8 — 08/12 08/13 08/12 08/13 08/12 08/12 08/12 08/13 — 08/13
9 — — 09/14 — 09/14 09/14 09/14 — 09/14 — 09/14
10 — — — 10/15 10/16 10/15 10/16 10/15 10/16 10/15 —
Tab.4  MODIS image dataset information
Fig.2  Experiments to validate the effectiveness of the STARFM method
Fig.3  Scatter plots of validation experiments of the validity of the STARFM method
Fig.4  Long time series FVC dataset in Xichuan County from 2002 to 2022
Fig.5  Spatial distribution of vegetation in Xichuan County from 2002 to 2022
Fig.6  Inter-annual variation curve of FVC in Xichuan County from 2002 to 2022
Fig.7  Trends of FVC in Xichuan County from 2002 to 2022
驱动因子 X1 X2 X3 X4 X5 X6
q值 0.234 0.175 0.259 0.152 0.359 0.302
Tab.5  Risk factor detection results of spatial variability of vegetation in Xichuan County
变化趋势的
显著性		 变化趋势的
正负		 复相关性的
显著性		 驱动因素的判断结果
P≥0.05 — — 未变化区域
P<0.05 Slope≥0 P≥0.05 人为造成的退化
P≥0.05 人为造成的改善
Slope<0 P<0.05 人为和气候造成的退化
P<0.05 人为和气候造成的改善
Tab.6  Criteria for determining the drivers of vegetation growth change in Xiechuan County
Fig.8  Judgment results of drivers of vegetation growth changes in Xichuan County
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