A RS-based study on changes in fractional vegetation cover in North Shaanxi and their driving factors
JIN Chengming1(), YANG Xingwang1, JING Haitao2
1. Shanghai Railway Beidou Survey Engineering Technology Co., Ltd., Shanghai 200040, China 2. School of Surveying and Mapping and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
This study investigates the spatial-temporal changes in the fractional vegetation cover in North Shanxi using the methods of inverse distance weighting and Pearson correlation analysis based on the GIS, RS, and SPSS22.0 platforms and the MODIS data of North Shanxi from 2000 to 2015. Meanwhile, it researches the driving factors of the vegetation changes according to the data of precipitation, air temperature, and social economy. The results are as follows. During 2000-2015, the overall fractional vegetation cover in the study area varied in the range of 0.35~0.55. Meanwhile, the spatial-temporal differences in the distribution of climatic factors produced different effects on the fractional vegetation cover. According to the results of principal component analysis, the contribution rates of GDP, rural population, total population, cultivated land area, precipitation, and air temperature were 41.4%, -38.3%, 35.7%, 32.8%, 21.3%, and 7.1%, respectively for the changes in the fractional vegetation cover. The study on the driving factors of vegetation cover will provide a scientific basis for future ecological protection.
晋成名, 杨兴旺, 景海涛. 基于RS的陕北地区植被覆盖度变化及驱动力研究[J]. 自然资源遥感, 2021, 33(4): 258-264.
JIN Chengming, YANG Xingwang, JING Haitao. A RS-based study on changes in fractional vegetation cover in North Shaanxi and their driving factors. Remote Sensing for Natural Resources, 2021, 33(4): 258-264.
Guo L Y, Li Y S, Wang T, et al. The impact of climate change and human activities on vegetation coverage[J]. Journal of Xi’an University of Science and Technology, 2020,40(1):148-156.
Yang Y H, Piao S L. Grassland vegetation cover change on the Qinghai-Tibet Plateau and its relationship with climate factors[J]. Chinese Journal of Plant Ecology, 2006(1):1-8
Guo Y Q, Wang N J, Chu X S, et al. Analysis of vegetation cover changes and causes in the Loess Plateau based on Google Earth Engine[J]. China Environmental Science, 2019,39(11):4804-4811.
Li D K, Wang Z. The change of vegetation coverage in Shaanxi Province after returning farmland to forest and its response to climate[J]. Journal of Ecology, 2020,39(1):1-10.
doi: 10.2307/2256625
[5]
Camberlin P, Martiny N, Philippon N, et al. Determinants of the interannual relationships between remote sensed photosynthetic activity and rainfall in tropical Africa[J]. Remote Sensing of Environment, 2008,106(2):199-216.
doi: 10.1016/j.rse.2006.08.009
[6]
Cuomo V, Lanfredi M, Lasaponara R, et al. Detection of interannual variation of vegetation in middle and southern Italy during 1985—1999 with 1 km NOAA AVHRR NDVI data[J]. Journal of Geophysical Research Atmospheres, 2001,106(D16):17863-17876.
doi: 10.1029/2001JD900166
[7]
Evans J, Geerken R. Discrimination between climate and human-induced dryland degradation[J]. Journal of Arid Environments, 2004,57(4):535-554.
doi: 10.1016/S0140-1963(03)00121-6
[8]
Sun C F, Liu Y, Song H M, et al. Tree-ring evidence of the impacts of climate change and agricultural cultivation on vegetation coverage in the upper reaches of the Weihe River,northwest China[J]. Science of the Total Environment, 2020,707.
Han G F. Study on the temporal and spatial changes of vegetation cover in eastern China and the influence of human factors[D]. Shanghai:East China Normal University, 2007.
Xiong Y J, Zhao S H, Yan C H, et al. Discussion on multi-scale monitoring and evaluation methods of urban green space resources[J]. Remote Sensing for Land and Resources, 2021,33(1):54-62.doi: 10.6046/gtzyyg.2020069.
doi: 10.6046/gtzyyg.2020069
Zhu L F. Research on spatiotemporal changes of vegetation coverage and rocky desertification monitoring based on MODIS data[D]. Chongqing:Southwest University, 2018.
2021, Vol. 33 
), 杨兴旺1, 景海涛2
