| 关中平原城市群植被覆盖的时空特征与影响因素 |
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| 引用本文： | 王治国,白永平,车磊,陈志杰,乔富伟.关中平原城市群植被覆盖的时空特征与影响因素[J].干旱区地理,2020,43(4):1041-1050. |
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| 作者姓名： | 王治国 白永平 车磊 陈志杰 乔富伟 |
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| 作者单位： | 西北师范大学地理与环境科学学院,甘肃 兰州 730070 |
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| 基金项目： | 教育部高等学校博士学科点专项科研基金联合资助课题（20106203110002）; 甘肃省重点研发计划（18YF1FA052）; 国家自然科学基金项目（41661035）资助 |
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| 摘 要： | 植被是全球及区域生态系统环境变化的重要指标,也是对人类社会活动有重要贡献的资源之一。为了研究关中平原城市群不同区域植被覆盖变化对自然和人文因子的响应,以划分为三个区域的植被作为研究对象,选取2000—2017年MODIS-NDVI遥感数据,运用趋势分析、探索性空间数据分析与地理探测器等方法,从时序演进与空间分布方面研究了18 a内植被覆盖的演化及分布特征,定量分析影响植被覆盖的主导因子。遥感数据要通过投影转换、拼接、最大值合成等方法进行处理,再运用Python程序进行影像批量裁剪,将遥感数据和气象数据进行分区统计,最后对该处理数据进行讨论研究。结论表明：（1） 研究期内关中平原城市群植被覆盖呈显著上升趋势,NDVI平均值增速为0.077·（10 a）–1,阶段性变化特征明显,其中2005—2007阶段和2011—2013阶段极显著增加,最大上升速率达到了0.05·a–1。（2） 空间上总体呈现“南高北低”的分布特征,研究区总体得到改善;高值区主要分布在南部秦岭北坡,受气候因子的影响更大,植被覆盖增加速度缓慢,达到轻度改善水平;低值区聚集在黄土高原边缘地区,植被增加趋势明显;中部关中平原极少部分地区植被覆盖出现了轻度退化或严重退化,以西安市及临近城市最为典型。（3） 热点区主要分布在秦岭山区及关中平原中部地区,冷点区则集中于黄土高原边缘地区,植被覆盖总体以增长为主。热点区格网数量持续增多,2013年达到最大为45.07%;冷点区域数量不断减少,2017年减少到9.82%;次热点区与次冷点区主要分布在中部平原地带及北部地区,由连片分布转化为零散分布,且总量不断减少。（4） 自然因素对植被覆盖的影响最为突出,其中气温和降水为影响植被覆盖的主导因子,决定力q值分别为0.955和0.931,且气温的影响大于降水的影响;人文因子影响力较为显著,GDP因子决定力q值达到0.387。研究可为当地改善植被覆盖环境提供理论依据。
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| 关 键 词： | NDVI 趋势分析 ESDA 地理探测器 关中平原城市群 |
| 收稿时间： | 2019-10-25 |
Spatio-temporal characteristics and influencing factors of vegetation coverage in urban agglomeration of Guanzhong Plain |
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| WANG Zhi-guo,BAI Yong-ping,CHE Lei,CHEN Zhi-jie,QIAO Fu-wei.Spatio-temporal characteristics and influencing factors of vegetation coverage in urban agglomeration of Guanzhong Plain[J].Arid Land Geography,2020,43(4):1041-1050. |
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| Authors: | WANG Zhi-guo BAI Yong-ping CHE Lei CHEN Zhi-jie QIAO Fu-wei |
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| Affiliation: | College of Geography and Environmental Science,Northwest Normal University,Lanzhou 730070,Gansu,China |
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| Abstract: | Vegetation is an important indicator of environmental changes in global and regional ecosystems,and it is also one of the resources that make an important contribution to human social activities. To study the response of vegetation coverage to natural and human factors in different parts of the Guanzhong Plain urban agglomeration in western China,we divided the region of interest into three vegetation areas for our research. We selected MODIS-NDVI remote-sensing data obtained during 2000-2017. Using trend analysis,exploratory spatial data analysis,and geodetector methods,we studied the evolution and distribution characteristics of vegetation cover during those 18 years from the perspectives of temporal evolution and spatial distribution. We quantitatively analyzed the main factors affecting vegetation coverage. We first processed remote-sensing data by such methods as projection conversion,splicing,and maximum-value synthesis and then applied batch image cropping using Python. The remote-sensing and meteorological data were categorized by applying statistical methods. From the processed data,we drew the following conclusions：（1） During the study period,vegetation coverage of the Guanzhong Plain urban agglomeration showed a significant upward trend. The average NDVI growth rate was 0.077 every 10 years,and the characteristics of periodic changes were obvious. Among them,the 2005-2007 and 2011-2013 periods increased significantly,and the maximum ascent rate reached 0.05 per year. （2） Our spatial data generally confirmed the distribution characterized as “high in the south and low in the north,” and vegetation coverage improved overall in the study area. The high-value areas are mainly distributed on the northern slope of the southern Qinling Mountains,which is more affected by climatic factors. The vegetation coverage is increasing slowly and has slightly improved. The low-value areas are concentrated on the edge of the Loess Plateau,and the vegetation coverage is obviously increasing there,whereas a small portion of the central part of the Guanzhong Plain showed slight to severe degradation,with Xi’an and its neighboring cities being the most typical. （3） Hot spots are mainly distributed in the Qinling Mountains and the central of the Guanzhong Plain,while cold spots are concentrated along the margins of the Loess Plateau,where vegetation coverage is mainly increasing. Hot-spot areas continue to increase,having reached a maximum of 45.07% in 2013,while the number of cold spots continues to decrease,having been reduced to 9.82% in 2017. The hot and cold spots are mainly distributed in the central plains and northern areas,which have changed from continuous to scattered distribution,and the total volume is continuously decreasing. （4） The most-prominent influences on vegetation coverage are natural factors,among which temperature and precipitation are dominant. The determinant q values are 0.955 and 0.931,respectively,the influence of temperature being greater than that of precipitation. The influence of human factors is important but not prominent; the determinant q value of the GDP factor reaches only 0.387. The conclusions of this paper could provide some theoretical basis to improve vegetation-coverage environment in the study area. |
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| Keywords: | NDVI trend analysis ESDA Geodetector urban agglomeration of Guanzhong Plain |
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