Please wait a minute...
 
Remote Sensing for Natural Resources    2021, Vol. 33 Issue (4) : 258-264     DOI: 10.6046/zrzyyg.2021019
|
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
Download: PDF(4054 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

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.
Keywords vegetation coverage      climate change      spatial-temporal change      trend analysis      socio-economic factors     
ZTFLH:  TP79P208  
Issue Date: 23 December 2021
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Chengming JIN
Xingwang YANG
Haitao JING
Cite this article:   
Chengming JIN,Xingwang YANG,Haitao JING. A RS-based study on changes in fractional vegetation cover in North Shaanxi and their driving factors[J]. Remote Sensing for Natural Resources, 2021, 33(4): 258-264.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021019     OR     https://www.gtzyyg.com/EN/Y2021/V33/I4/258
Fig.1  Geographical map of the study area
类型 劣覆盖度 低覆盖度 中覆盖度 高覆盖度
比例 17.2 25.0 27.1 30.7
Tab.1  Proportion distribution of different vegetation coverage(%)
Fig.2  Spatial distribution of vegetation coverage in the study area from 2000 to 2015
变化等级 slope趋
势分级		 2000—2015年 2000—2005年 2006—2010年 2011—2015年
像元数 比例/% 像元数 比例/% 像元数 比例/% 像元数 比例/%
明显退化 (-∞,-0.01) 881 1.08 61 673 75.80 20 127 24.73 38 094 46.81
中度退化 [-0.01,-0.005) 2 921 3.59 6 924 8.50 7 832 9.63 5 851 7.19
轻度退化 [-0.005,-0.001) 7 360 9.15 4 484 5.52 5 807 7.13 6 502 7.99
几乎不变 [-0.001,0.001) 10 363 12.64 3 733 4.58 10 021 12.31 7 351 9.04
轻度改善 [0.001,0.005) 11 371 13.79 2 058 2.53 7 554 9.29 5 840 7.42
中度改善 [0.005,0.01) 14 376 17.76 1 609 1.98 6 406 7.87 4 768 5.86
明显改善 [0.01,+∞) 34 100 41.90 891 1.09 23 625 29.04 12 766 15.69
Tab.2  Statistics of vegetation coverage trend in the study area from 2000 to 2015
Fig.3  Spatial distribution of precipitation characteristics in the study area from 2000 to 2015
Fig.4  Spatial distribution of annual mean temperature in the study area from 2000 to 2015
Fig.5  Changes in annual average precipitation trends in the study area from 2000 to 2015
Fig.6  Trend of annual average temperature in the study area from 2000 to 2015
Fig.7  Correlation between vegetation coverage and precipitation
Fig.8  Correlation between vegetation coverage and air temperature
主成分 特征值 贡献率/%
GDP 3.36 41.4
农村人口 1.8 -38.3
总人口 0.79 35.7
耕地面积 0.52 32.8
降水 0.21 21.3
气温 0.04 7.1
Tab.3  Contribution rate of drivers of vegetation cover change
[1] 郭力宇, 李雨思, 王涛, 等. 气候变化与人类活动对植被覆盖的影响[J]. 西安科技大学学报, 2020,40(1):148-156.
[1] 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.
[2] 杨元合, 朴世龙. 青藏高原草地植被覆盖变化及其与气候因子的关系[J]. 植物生态学报, 2006(1):1-8.
doi: 10.17521/cjpe.2006.0001
[2] 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
[3] 郭永强, 王乃江, 褚晓升, 等. 基于Google Earth Engine分析黄土高原植被覆盖变化及原因[J]. 中国环境科学, 2019,39(11):4804-4811.
[3] 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.
[4] 李登科, 王钊. 退耕还林后陕西省植被覆盖度变化及其对气候的响应[J]. 生态学杂志, 2020,39(1):1-10.
[4] 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 url: https://www.jstor.org/stable/2256625?origin=crossref
[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 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425706003117
[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 url: http://doi.wiley.com/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 url: https://linkinghub.elsevier.com/retrieve/pii/S0140196303001216
[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.
[9] 韩贵锋. 中国东部地区植被覆盖的时空变化及其人为因素的影响研究[D]. 上海:华东师范大学, 2007.
[9] 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.
[10] 熊育久, 赵少华, 鄢春华, 等. 城市绿地资源多尺度监测与评价方法探讨[J]. 国土资源遥感, 2021,33(1):54-62.doi: 10.6046/gtzyyg.2020069.
doi: 10.6046/gtzyyg.2020069
[10] 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
[11] 朱林富. 基于MODIS数据的植被覆盖度时空变化及石漠化监测研究[D]. 重庆:西南大学, 2018.
[11] Zhu L F. Research on spatiotemporal changes of vegetation coverage and rocky desertification monitoring based on MODIS data[D]. Chongqing:Southwest University, 2018.
[1] GUO Yi, GAN Fuping, YAN Bokun, BAI Juan, XING Naichen, LIU Qi. Spatio-temporal distribution and influencing factors of soil moisture content in Henan Province during 1948—2021[J]. Remote Sensing for Natural Resources, 2023, 35(3): 241-252.
[2] PANG Xin, LIU Jun. Effects of climate changes on the NDVI of vegetation in Asia[J]. Remote Sensing for Natural Resources, 2023, 35(2): 295-305.
[3] HU Xiaoqiang, YANG Shuwen, YAN Heng, XUE Qing, ZHANG Naixin. Time-series InSAR-based monitoring and analysis of surface deformation in the Axi mining area, Xinjiang[J]. Remote Sensing for Natural Resources, 2023, 35(1): 171-179.
[4] ZHANG Zhenqi, CAI Huiwen, ZHANG Pingping, WANG Zelin, LI Tingting. A GEE-based study on the temporal and spatial variations in the carbon source/sink function of vegetation in the Three-River Headwaters region[J]. Remote Sensing for Natural Resources, 2023, 35(1): 231-242.
[5] ZUO Lu, SUN Leigang, LU Junjing, XU Quanhong, LIU Jianfeng, MA Xiaoqian. MODIS-based comprehensive assessment and spatial-temporal change monitoring of ecological quality in Beijing-Tianjin-Hebei region[J]. Remote Sensing for Natural Resources, 2022, 34(2): 203-214.
[6] QIN Dahui, YANG Ling, CHEN Lunchao, DUAN Yunfei, JIA Hongliang, LI Zhenpei, MA Jianqin. A study on the characteristics and model of drought in Xinjiang based on multi-source data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 151-157.
[7] WEI Haohan, XU Renjie, YANG Qiang, ZHOU Quanping. Variation and effect analysis of the water level of the Taihu Lake based on multi-source satellite altimetry data[J]. Remote Sensing for Natural Resources, 2021, 33(3): 130-137.
[8] WANG Jiaxin, SA Chula, MAO Kebiao, MENG Fanhao, LUO Min, WANG Mulan. Temporal and spatial variation of soil moisture in the Mongolian Plateau and its response to climate change[J]. Remote Sensing for Land & Resources, 2021, 33(1): 231-239.
[9] PAN Meng, CAO Yungang. Present status and perspectives of remote sensing survey of glacial lakes in High Asia[J]. Remote Sensing for Land & Resources, 2021, 33(1): 1-8.
[10] Hongxia LUO, Shengpei DAI, Maofen LI, Yuping LI, Qian ZHENG, Yingying HU. Relative roles of climate changes and human activities in vegetation variables in Hainan Island[J]. Remote Sensing for Land & Resources, 2020, 32(1): 154-161.
[11] Yuqi CHENG, Yuqing WANG, Jingping SUN, Chengfu ZHANG. Temporal and spatial variation of evapotranspiration and grassland vegetation cover in Duolun County, Inner Mongolia[J]. Remote Sensing for Land & Resources, 2020, 32(1): 200-208.
[12] Wei WANG, Samat Alim, Abuduwaili Jilili. Geo-detector based spatio-temporal variation characteristics and driving factors analysis of NDVI in Central Asia[J]. Remote Sensing for Land & Resources, 2019, 31(4): 32-40.
[13] Jida PENG, Chungui ZHANG. Remote sensing monitoring of vegetation coverage by GF-1 satellite: A case study in Xiamen City[J]. Remote Sensing for Land & Resources, 2019, 31(4): 137-142.
[14] Qinglin MENG, Mingyu LI, Chunying REN, Zongming WANG, Yanlin TIAN. Dynamic assessment of habitat quality in eastern Jilin Province based on HSI model[J]. Remote Sensing for Land & Resources, 2019, 31(3): 140-147.
[15] Jiaming LAI, Wunian YANG. Dynamic changes of vegetation cover in natural forest area of western Sichuan in recent 29 years based on RS[J]. Remote Sensing for Land & Resources, 2018, 30(4): 132-138.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech