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Remote Sensing Technology and Application  2022, Vol. 37 Issue (2): 389-398    DOI: 10.11873/j.issn.1004-0323.2022.2.0389
    
Analysis of Vegetation Cover Change and Driving Forces in Typical Resource
Chuanwu Zhao1,2(),Wei Guo1(),Yueguan Yan1,Huayang Dai1,Jian Zhang1
College of Geoscience and Surveying Engineering，China University of Mining and Technology，Beijing，Beijing 100083，ChinaInstitute of Remote Sensing Science and Engineering，Faculty of Geographical Sciences，Beijing Normal University，Beijing 100875，China
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Abstract  

There are many researches on vegetation change in arid and semi-arid areas， but little attention has been paid on the social and economic impact of resource-based cities on vegetation change. Based on MOD13Q1 data， climate data such as rainfall and temperature， 11 socio-economic indicators such as raw coal production from 2000 to 2020， combined with GIS technology and statistical methods such as linear regression， the spatial and temporal changes of Ordos vegetation and its influencing factors were studied. The results are as follows： ①The NDVI value of Ordos ranged from 0.233 to 0.395， showing a fluctuating growth trend with a growth rate of 0.059/10 a during 2000 to 2020； the NDVI values of the eight counties under its jurisdiction also showed a fluctuating growth trend， but there were many differences among different regions. ②The vegetation in Ordos is high in the northeast and it is low in the southwest. The area of low vegetation area is 53 500 km2， accounting for 61.58% of the total area of Ordos. The area of high vegetation is only 20 000 km2. The area of the vegetation improvement is much larger than that of the vegetation degradation area. The improvement area accounts for 52.19% of the entire Ordos area， and the vegetation degradation area only accounts for 3.69%. ③The NDVI value is extremely significant positively related to rainfall， with a correlation coefficient of 0.794 （P<0.01）； the correlation coefficient between the change of NDVI and the accumulated rainfall in the month is larger， and the correlation coefficient with the temperature one month ago is larger. ④The NDVI change is extremely significantly positively correlated with the 11 socioeconomic indicators， with a correlation of 0.728~0.796 （P<0.01）. From 2000 to 2020， the restoration effect of Ordos vegetation is good. Rainfall and temperature are the main factors affecting the growth of vegetation in Ordos， of which rainfall dominates. The response of NDVI changes to rainfall has less obvious lag， and the response to temperature has a one-month lag. The positive effects of socio-economic development on vegetation cover outweigh the negative effects.
Key words:  Vegetation cover      Influencing factors      Ordos     
Received:  17 December 2020      Published:  17 June 2022
ZTFLH:  TP79  
Corresponding Authors:  Wei Guo     E-mail:  cumtb_zhao@163.com;guowei_rs@163.com
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Chuanwu Zhao
Wei Guo
Yueguan Yan
Huayang Dai
Jian Zhang

Cite this article: 

Chuanwu Zhao,Wei Guo,Yueguan Yan,Huayang Dai,Jian Zhang. Analysis of Vegetation Cover Change and Driving Forces in Typical Resource. Remote Sensing Technology and Application, 2022, 37(2): 389-398.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2022.2.0389     OR     http://www.rsta.ac.cn/EN/Y2022/V37/I2/389

Fig.1  The geographical location of Ordos and the distribution of meteorological stations
Fig.2  Temporal variation of vegetation coverage in Ordos during 2000 to 2020
Fig.3  Temporal variation trends of vegetation coverage in enght counties of Ordos during 2000 to 2020
Fig.4  Spatial distribution of NDVI in Ordos during 2000 to 2020
Fig.5  Statistics of vegetation coverage level in Ordos during 2000 to 2020
Fig.6  Spatial distribution of variation trends of vegetation coverage in Ordos during 2000 to 2020
Fig.7  Statistics of variation trends of vegetation coverage variation in Ordos during 2000 to 2020
Fig.8  The relationship between NDVI and climate factors
Fig.9  The distribution of in Ordos during 2000 to 2020
NDVI与降雨量NDVI与温度
年份0~1月0~2月0~3月0个月1个月2个月0~1月0~2月0~3月0个月1个月2个月
20020.945**0.983**0.886**0.79**0.907**0.665*0.916**0.905**0.774*0.858**0.910**0.635*
20030.919**0.823**0.6160.908**0.761**0.3660.886**0.839**0.671*0.816**0.893**0.595
20040.951**0.829**0.5840.943**0.727*0.240.892**0.874**0.815**0.799**0.866**0.665*
20050.972**0.896**0.726*0.882**0.812**0.3840.895**0.888**0.757*0.870**0.874**0.637*
20060.978**0.915**0.741*0.888**0.786**0.3850.881**0.844**0.817*0.782**0.855**0.691*
20070.966**0.906**0.722*0.854**0.825**0.4410.918**0.901**0.774*0.859**0.887**0.627
20120.974**0.875**0.6260.923**0.823**0.3870.889**0.884**0.783*0.844**0.867**0.642*
20130.984**0.923**0.719*0.893**0.891**0.4280.900**0.891**0.761*0.851**0.869**0.619
20140.881**0.702*0.3840.950**0.671*0.1430.904**0.903**0.777*0.852**0.875**0.615
20150.702*0.354-0.1490.611*0.191-0.1360.948**0.904**0.706*0.912**0.899**0.576
20170.910**0.790*0.5170.907**0.719*0.2380.932**0.911**0.781*0.883**0.897**0.609
Table 1  Correlation between NDVI and hydrothermal factors at monthly scale
Fig.10  Correlation between NDVI and socio-economics in Ordos
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