[1]LIU Wei,JIAO Shulin,LI Yinjiu,et al.Analysis on the Correlation Between Vegetation Cover of Land Surface and Climatic Factors in Karst Area[J].Research of Soil and Water Conservation,2021,28(03):203-215.
Copy
Analysis on the Correlation Between Vegetation Cover of Land Surface and Climatic Factors in Karst Area
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
28
Number of periods:
2021 03
Page number:
203-215
Column:
Public date:
2021-04-20
- Title:
- Analysis on the Correlation Between Vegetation Cover of Land Surface and Climatic Factors in Karst Area
- Keywords:
- vegetation cover; climatic factors; spline function method; correlation analysis; Guizhou Province
- CLC:
- Q948
- DOI:
- -
- Abstract:
- Understanding the temporal and spatial variation of vegetation and its relationship with climatic factors can provide some basis for vegetation restoration and protection in ecologically fragile areas. Based on meteorological data and time series data of vegetation NDVI, the temporal and spatial variation characteristics of vegetation NDVI from 1998 to 2018 in Guizhou Province were analyzed by spline function method and correlation analysis method, and the correlation between vegetation NDVI and temperature and precipitation in different time periods was discussed. The results show that:(1)from 1998 to 2018, vegetation NDVI increased at a rate of 6.4×10-3 /a(p<0.01), and the spatial distribution pattern was high in the south and low in the north, high in the east and low in the west;(2)from 1980 to 2018, the temperature increased significantly at a rate of 0.23℃/decade(p<0.01); except for the negative growth rate in summer, the temperature in other seasons increased at different rates;(3)from 1980 to 2018, the annual cumulative precipitation decreased as a whole at a rate of -10.71 mm/decade(p>0.1), in which precipitation increased in the spring while the precipitation decreased in the other seasons;(4)from 1998 to 2018, the significant increase of vegetation NDVI was closely related to climate warming, but weakly related to precipitation; the increase of temperature or the decrease of precipitation in summer and autumn was conducive to vegetation growth;(5)in the four seasons, the weakest vegetation NDVI sensitivity was about 0.20 in winter when it was about 6.5℃, and the sensitivity to temperature was not obvious in the other seasons; the sensitivity to precipitation was different in each season, and the inhibition effect was most obvious in winter, with the r value of about -0.80. In general, the vegetation coverage in Guizhou Province is good, showing an increasing trend, and the correlation with temperature is higher than the cumulative precipitation, but the sensitivity is weaker.
- References:
- [1] 杜加强,贾尔恒·阿哈提,赵晨曦,等.1982—2012年新疆植被NDVI的动态变化及其对气候变化和人类活动的响应[J].应用生态学报,2015,26(12):3567-3578.[2] 严恩萍,林辉,党永峰,等.2000—2012年京津风沙源治理区植被覆盖时空演变特征[J].生态学报,2014,34(17):5007-5020.[3] 陈秀妍.2000—2016年中亚天山植被动态变化及其驱动因素研究[D].北京:中国科学院大学(中国科学院遥感与数字地球研究所),2018.[4] Nemani R R, Keeling C D, Hashimoto H, et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999[J]. Science, 2003,300(5625):1560-1563.[5] Liu Y, Li Y, Li S, et al. Spatial and temporal patterns of global NDVI trends:correlations with climate and human factors[J]. Remote Sensing, 2015,7(10):13233-13250.[6] 金凯,王飞,韩剑桥,等.1982—2015年中国气候变化和人类活动对植被NDVI变化的影响[J].地理学报,2020,75(5):961-974.[7] 金凯.中国植被覆盖时空变化及其与气候和人类活动的关系[D].陕西杨凌:西北农林科技大学,2019.[8] 罗玲,王宗明,宋开山,等.1982—2003年中国东北地区不同类型植被NDVI与气候因子的关系研究[J].西北植物学报,2009,29(4):800-808.[9] 国志兴,王宗明,宋开山,等.1982—2003年东北林区森林植被NDVI与水热条件的相关分析[J].生态学杂志,2007,26(12):22-28.[10] 穆少杰,李建龙,陈奕兆,等.2001—2010年内蒙古植被覆盖度时空变化特征[J].地理学报,2012,67(9):1255-1268.[11] Piao S, Yin G, Tan J, et al. Detection and attribution of vegetation greening trend in China over the last 30 years[J]. Global Change Biology, 2015,21(4):1601-1609.[12] 杨世凡,安裕伦.生态恢复背景下喀斯特地区植被覆盖的时空变化:以黔中地区为例[J].地球与环境,2014,42(3):404-412.[13] 梅再美.贵州喀斯特脆弱生态区退耕还林还草与节水型混农林业发展的途径探讨[J].中国岩溶,2003,22(4):293-298.[14] 吴端耀,罗娅,王青,等.2001—2014年贵州省林草植被覆盖度时空变化及其与气温降水变化的关系[J].贵州师范大学学报:自然科学版,2017,35(1):1-7.[15] 彭睿文,罗娅,余军林,等.中国西南地区2009—2015年植被覆盖度变化及其与降雨的关系[J].贵州师范大学学报:自然科学版,2017,35(5):15-23.[16] 张继,周旭,蒋啸,等.生态工程建设背景下贵州高原的植被变化及影响因素分析[J].长江流域资源与环境,2019,28(7):1623-1633.[17] 彭睿文,罗娅,余军林,等.中国西南地区2009—2015年植被覆盖度变化及其与降雨的关系[J].贵州师范大学学报:自然科学版,2017,35(5):15-23.[18] 穆少杰,李建龙,陈奕兆,等.2001—2010年内蒙古植被覆盖度时空变化特征[J].地理学报,2012,67(9):1255-1268.[19] 闫星光.基于GIS的云贵高原典型地貌区极端降水时空分布规律研究[D].贵阳:贵州大学,2018.[20] 张梦远,姚瑶.吉林省气温与降水数据空间插值与分布研究[J].吉林农业,2018,30(20):108-110.[21] 杨勇.改进的张力样条函数插值法程序及其设计方法[J].水运工程,1992,21(7):4-10.[22] 彭彬,周艳莲,高苹,等.气温插值中不同空间插值方法的适用性分析:以江苏省为例[J].地球信息科学学报,2011,13(4):539-548.[23] Johnston K, Ver Hoef J M, Krivoruchko K, et al. Using ArcGIS spatial analyst[M]. Redlands, Ca, Usa:Envi-Ronmental Systems Research Institute Inc.,2001,136-148.[24] 彭彬,周艳莲,高苹,等.气温插值中不同空间插值方法的适用性分析:以江苏省为例[J].地球信息科学学报,2011,13(4):539-548.[25] 王晓利.中国沿海极端气候变化及其对NDVI的影响特征研究[D].山东烟台:中国科学院烟台海岸带研究所,2017.[26] 郭梦媚.江西省植被NDVI变化特征及其对气候因子的响应[D].南京:南京信息工程大学,2015.[27] 王彦颖.中国东北植被时空动态变化及其对气候响应研究[D].长春:东北师范大学,2016.[28] Fensholt R, Rasmussen K, Nielsen T T, et al. Evaluation of earth observation based long term vegetation trends—Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data[J]. Remote Sensing of Environment, 2009,113(9):1886-1898.[29] 潘宗源,吴远斌,贾龙,等.湖南宁乡大成桥岩溶地下水对暴雨响应特征及多元回归预测模型[J].中国岩溶,2020,39(2):232-242.[30] 李仕蓉.2000—2013年贵州省植被覆盖时空变化特征与趋势[J].贵州农业科学,2014,42(7):202-205.[31] 张蓓蓓,蔡宏,田鹏举,等.2000—2017年贵州省植被覆盖时空变化特征及其对气候变化的响应[J].地球与环境,2020,48(4):461-470.[32] 任国玉,初子莹,周雅清,等.中国气温变化研究最新进展[J].气候与环境研究,2005,10(4):701-716.[33] 齐冬梅,周长艳,李跃清,等.西南区域气候变化原因分析[J].高原山地气象研究,2012,32(1):35-42.[34] 李聪,肖子牛,张晓玲.近60年中国不同区域降水的气候变化特征[J].气象,2012,38(4):419-424.[35] 周秀华.我国西南及周边地区气候的模拟和预估[D].北京:中国气象科学研究院,2014.[36] 李坤龙,郭跃.2000—2014年贵州省安顺市NDVI变化及其与气温、降水的关系[J].重庆师范大学学报:自然科学版,2018,35(5):120-126,143.
- Similar References:
Memo
-
Last Update:
2021-04-20