基于MODIS-EVI的广西西江流域植被时空变化特征及其影响因素
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摘要
基于MODIS-EVI数据对2007—2016年广西西江流域植被时空变化特征进行了分析,进而探讨其影响因素。结果表明:近10年来,研究区月EVI呈周期性变化,每年7—8月份最高,1—2月份最低,明显受到季节性气候等自然因素控制。EVI年际变化总体呈上升的趋势,可能与一系列植被保护措施有关,但存在两次骤然下降现象,可能是受到重大自然灾害的影响。岩溶区与非岩溶区EVI变化趋势与全区基本一致。研究区EVI具有明显的空间差异,EVI高值(>0.4)主要分布于高海拔或人为破坏小的地区,适合实施封山育林、人工造林等生态修复举措;EVI低值(≤0.4)主要分布于水系发达或城市中心地带等低海拔地区,受到自然条件和城镇化发展的制约。另外,研究区植被EVI与气温和降雨均呈显著正相关,且与气温的相关性明显高于降雨,对气温和降雨的响应均存在1个月的滞后期。
Based on the MODIS-EVI data, the spatiotemporal variation of vegetation in Xijiang River Basin of Guangxi from 2007 to 2016 was analyzed and then its influencing factors were discussed. The results indicated that in recent decade, the monthly EVI in the study area periodically oscillated, and had the peak and nadir values from July to August and from January to February, respectively, which was clearly controlled by natural factors such as seasonal climate. The interannual variation of EVI was on the rise as a whole, and possibly related to a series of vegetation protection measures, but displayed two abrupt drops which might be affected by serious natural disasters in Southwest China. The variation trend of EVI in karst region and non-karst region was nearly consistent with that of the whole region. EVI of vegetation mainly ranging from 0.4 to 0.6 in the study area had obvious spatial differences. High EVI values(>0.4) mainly distributed in the high altitude areas with little anthropogenic damage where the measures of forest reservation and artificial afforestation were feasible. Conversely, low EVI values(≤0.4) were observed in the low altitude areas such as river system and urban center restricting the increase of vegetation coverage. In addition, EVI of vegetation showed a significant positive correlation with-and a one-month lag in response to both temperature and rainfall, and its correlation with temperature was higher than that with rainfall.
Based on the MODIS-EVI data, the spatiotemporal variation of vegetation in Xijiang River Basin of Guangxi from 2007 to 2016 was analyzed and then its influencing factors were discussed. The results indicated that in recent decade, the monthly EVI in the study area periodically oscillated, and had the peak and nadir values from July to August and from January to February, respectively, which was clearly controlled by natural factors such as seasonal climate. The interannual variation of EVI was on the rise as a whole, and possibly related to a series of vegetation protection measures, but displayed two abrupt drops which might be affected by serious natural disasters in Southwest China. The variation trend of EVI in karst region and non-karst region was nearly consistent with that of the whole region. EVI of vegetation mainly ranging from 0.4 to 0.6 in the study area had obvious spatial differences. High EVI values(>0.4) mainly distributed in the high altitude areas with little anthropogenic damage where the measures of forest reservation and artificial afforestation were feasible. Conversely, low EVI values(≤0.4) were observed in the low altitude areas such as river system and urban center restricting the increase of vegetation coverage. In addition, EVI of vegetation showed a significant positive correlation with-and a one-month lag in response to both temperature and rainfall, and its correlation with temperature was higher than that with rainfall.
引文
[1]Bar-On Y M,Phillips R,Milo R.The biomass distribution on Earth[J].Proceedings of the National Academy of Sciences,2018,1-6.
[2]Menzel A,Fabian P.Growing season extended in Europe[J].Nature,1999,397(6721):659.
[3]Schwartz M D.Green-wave phenology[J].Nature,1998,394(6696):839-840.
[4]郭铌.植被指数及其研究进展[J].干旱气象,2003,21(4):71-75.
[5]信忠保,许炯心,郑伟.气候变化和人类活动对黄土高原植被覆盖变化的影响[J].中国科学,2007,37(11):1504-1514.
[6]徐茜,任志远,杨忍.黄土高原地区归一化植被指数时空动态变化及其与气候因子的关系[J].陕西师范大学学报:自然科学版,2012,40(1):82-87.
[7]冯莉莉,何贞铭,刘学锋,等.基于MODIS-NDVI数据的吉林省植被覆盖度及其时空动态变化[J].中国科学院大学学报,2014,31(4):492-499.
[8]李开丽,蒋建军,茅荣正,等.植被叶面积指数遥感监测模型[J].生态学报,2005,25(6):1491-1496.
[9]王正兴,刘闯,Huete A.植被指数研究进展:从AVHRR-NDVI到MODIS-EVI[J].生态学报,2003,23(5):979-987.
[10]赵丽苹.基于MODIS数据的喀斯特地区石漠化时空演变特征研究[D].北京:中国地质大学(北京),2015.
[11]Sj9str9m M,Ard9J,Arneth A,et al.Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems[J].Remote Sensing of Environment,2011,115(4):1081-1089.
[12]Pan Y,Li L,Zhang J,et al.Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index[J].Remote Sensing of Environment,2012,119(3):232-242.
[13]叶琦,赵萍,孙静.基于MODIS/NDVI与EVI的皖江流域植被覆盖比较分析[J].长江流域资源与环境,2012,21(3):361-368.
[14]郭鹏.基于MODIS的青藏高原地表参数时空变化研究[D].北京:中国石油大学,2010.
[15]李红军,郑力,雷玉平,等.基于EOS/MODIS数据的NDVI与EVI比较研究[J].地理科学进展,2007,26(1):26-32.
[16]林辉,熊育久,万玲凤,等.湖南省MODIS遥感植被指数的时空变化[J].应用生态学报,2007,18(3):581-585.
[17]董丹,倪健.利用CASA模型模拟西南喀斯特植被净第一性生产力[J].生态学报,2011,31(7):1855-1866.
[18]杨绍锷,谭裕模,胡钧铭.基于NDVI的广西近十年植被变化特征分析[J].南方农业学报,2012,43(11):1783-1788.
[19]韦振锋,任志远,张翀.近12年广西植被覆盖与降水和气温的时空响应特征[J].水土保持研究,2013,20(5):33-44.
[20]陈燕丽,黄敏堂,莫伟华,等.基于MODIS NDVI的广西西南典型生态区植被变化对比监测[J].气象科学,2015,35(1):93-99.
[21]孙光,罗遵兰,徐靖,等.用指数平衡法对广西西江流域水资源承载能力的分析[J].中国农业大学学报,2013,18(5):57-61.
[22]Holben B N.Characteristics of maximum-value composite images from temporal AVHRR data[J].International Journal of Remote Sensing,1986,7(11):1417-1434.
[23]刘宪锋,朱秀芳,潘耀忠,等.1982-2012年中国植被覆盖时空变化特征[J].生态学报,2015,35(16):5331-5342.
[24]Stow D,Daeschner S,Hope A,et al.Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the1990s[J].International Journal of Remote Sensing,2003,24(5):7.
[25]戴声佩,张勃,王海军,等.中国西北地区植被覆盖变化驱动因子分析[J].干旱区地理,2010,33(4):636-643.
[26]李小亚,张勃,靳自宝.基于MODIS-NDVI的甘肃河东地区植被覆盖度动态监测[J].水土保持研究,2013,20(1):112-115.
[27]徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,2002.
[28]靖娟利,王永锋.1998-2012年中国西南岩溶区植被覆盖时空变化分析[J].水土保持研究,2014,21(4):163-167.
[29]邱海军,曹明明.基于SPOT VEGETATION数据的中国植被覆盖时空变化分析[J].资源科学,2011,33(2):335-340.
[30]周成虎,万庆,黄诗峰,等.基于GIS的洪水灾害风险区划研究[J].地理学报,2000,55(1):15-24.
[31]周峰,许有鹏,吕慧华.基于MODIS-EVI数据的长江三角洲地区植被变化的特征[J].长江流域资源与环境,2012,21(11):1363-1369.
[32]鲍雅静,宋国宝,李政海,等.纵向岭谷区植被覆盖的空间分异及其对气候的时滞效应[J].科学通报,2007,52(S2):37-42.
[33]Goward S N,Prince S D.Transient effects of climate on vegetation dynamics:satellite observations[J].Journal of Biogeography,1995,22(2/3):549-564.
[34]何奕萱,易桂花,张廷斌,李景吉,别小娟,闾利,郑飞鸽.红河流域“通道-阻隔”作用下2000-2014年植被EVI变化趋势与驱动力[J].生态学报,2018,38(6):2056-2064.
[35]宋富强,邢开雄,刘阳,等.基于MODIS/NDVI的陕北地区植被动态监测与评价[J].生态学报,2011,31(2):354-363.
[36]李先琨,苏宗明,吕仕洪,等.广西岩溶植被自然分布规律及对岩溶生态恢复重建的意义[J].山地学报,2003,21(2):129-139.
[37]王永锋,靖娟利.广西近15a植被覆盖变化及其对气候因子的响应[J].农业现代化研究,2017,38(6):1086-1096.
[38]杨绍锷,廖雪萍,谭裕模,等.广西近十年植被NDVI变化及其对降水的响应特征分析[J].西南农业学报,2013,26(2):766-771.
[2]Menzel A,Fabian P.Growing season extended in Europe[J].Nature,1999,397(6721):659.
[3]Schwartz M D.Green-wave phenology[J].Nature,1998,394(6696):839-840.
[4]郭铌.植被指数及其研究进展[J].干旱气象,2003,21(4):71-75.
[5]信忠保,许炯心,郑伟.气候变化和人类活动对黄土高原植被覆盖变化的影响[J].中国科学,2007,37(11):1504-1514.
[6]徐茜,任志远,杨忍.黄土高原地区归一化植被指数时空动态变化及其与气候因子的关系[J].陕西师范大学学报:自然科学版,2012,40(1):82-87.
[7]冯莉莉,何贞铭,刘学锋,等.基于MODIS-NDVI数据的吉林省植被覆盖度及其时空动态变化[J].中国科学院大学学报,2014,31(4):492-499.
[8]李开丽,蒋建军,茅荣正,等.植被叶面积指数遥感监测模型[J].生态学报,2005,25(6):1491-1496.
[9]王正兴,刘闯,Huete A.植被指数研究进展:从AVHRR-NDVI到MODIS-EVI[J].生态学报,2003,23(5):979-987.
[10]赵丽苹.基于MODIS数据的喀斯特地区石漠化时空演变特征研究[D].北京:中国地质大学(北京),2015.
[11]Sj9str9m M,Ard9J,Arneth A,et al.Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems[J].Remote Sensing of Environment,2011,115(4):1081-1089.
[12]Pan Y,Li L,Zhang J,et al.Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index[J].Remote Sensing of Environment,2012,119(3):232-242.
[13]叶琦,赵萍,孙静.基于MODIS/NDVI与EVI的皖江流域植被覆盖比较分析[J].长江流域资源与环境,2012,21(3):361-368.
[14]郭鹏.基于MODIS的青藏高原地表参数时空变化研究[D].北京:中国石油大学,2010.
[15]李红军,郑力,雷玉平,等.基于EOS/MODIS数据的NDVI与EVI比较研究[J].地理科学进展,2007,26(1):26-32.
[16]林辉,熊育久,万玲凤,等.湖南省MODIS遥感植被指数的时空变化[J].应用生态学报,2007,18(3):581-585.
[17]董丹,倪健.利用CASA模型模拟西南喀斯特植被净第一性生产力[J].生态学报,2011,31(7):1855-1866.
[18]杨绍锷,谭裕模,胡钧铭.基于NDVI的广西近十年植被变化特征分析[J].南方农业学报,2012,43(11):1783-1788.
[19]韦振锋,任志远,张翀.近12年广西植被覆盖与降水和气温的时空响应特征[J].水土保持研究,2013,20(5):33-44.
[20]陈燕丽,黄敏堂,莫伟华,等.基于MODIS NDVI的广西西南典型生态区植被变化对比监测[J].气象科学,2015,35(1):93-99.
[21]孙光,罗遵兰,徐靖,等.用指数平衡法对广西西江流域水资源承载能力的分析[J].中国农业大学学报,2013,18(5):57-61.
[22]Holben B N.Characteristics of maximum-value composite images from temporal AVHRR data[J].International Journal of Remote Sensing,1986,7(11):1417-1434.
[23]刘宪锋,朱秀芳,潘耀忠,等.1982-2012年中国植被覆盖时空变化特征[J].生态学报,2015,35(16):5331-5342.
[24]Stow D,Daeschner S,Hope A,et al.Variability of the Seasonally Integrated Normalized Difference Vegetation Index Across the North Slope of Alaska in the1990s[J].International Journal of Remote Sensing,2003,24(5):7.
[25]戴声佩,张勃,王海军,等.中国西北地区植被覆盖变化驱动因子分析[J].干旱区地理,2010,33(4):636-643.
[26]李小亚,张勃,靳自宝.基于MODIS-NDVI的甘肃河东地区植被覆盖度动态监测[J].水土保持研究,2013,20(1):112-115.
[27]徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,2002.
[28]靖娟利,王永锋.1998-2012年中国西南岩溶区植被覆盖时空变化分析[J].水土保持研究,2014,21(4):163-167.
[29]邱海军,曹明明.基于SPOT VEGETATION数据的中国植被覆盖时空变化分析[J].资源科学,2011,33(2):335-340.
[30]周成虎,万庆,黄诗峰,等.基于GIS的洪水灾害风险区划研究[J].地理学报,2000,55(1):15-24.
[31]周峰,许有鹏,吕慧华.基于MODIS-EVI数据的长江三角洲地区植被变化的特征[J].长江流域资源与环境,2012,21(11):1363-1369.
[32]鲍雅静,宋国宝,李政海,等.纵向岭谷区植被覆盖的空间分异及其对气候的时滞效应[J].科学通报,2007,52(S2):37-42.
[33]Goward S N,Prince S D.Transient effects of climate on vegetation dynamics:satellite observations[J].Journal of Biogeography,1995,22(2/3):549-564.
[34]何奕萱,易桂花,张廷斌,李景吉,别小娟,闾利,郑飞鸽.红河流域“通道-阻隔”作用下2000-2014年植被EVI变化趋势与驱动力[J].生态学报,2018,38(6):2056-2064.
[35]宋富强,邢开雄,刘阳,等.基于MODIS/NDVI的陕北地区植被动态监测与评价[J].生态学报,2011,31(2):354-363.
[36]李先琨,苏宗明,吕仕洪,等.广西岩溶植被自然分布规律及对岩溶生态恢复重建的意义[J].山地学报,2003,21(2):129-139.
[37]王永锋,靖娟利.广西近15a植被覆盖变化及其对气候因子的响应[J].农业现代化研究,2017,38(6):1086-1096.
[38]杨绍锷,廖雪萍,谭裕模,等.广西近十年植被NDVI变化及其对降水的响应特征分析[J].西南农业学报,2013,26(2):766-771.