2006—2015年秦巴山区植被光合有效辐射吸收比例的时空变化特征
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摘要
光合有效辐射吸收比例(fraction of absorbed photosynthetically active radiation,FPAR)反映了植被吸收光合有效辐射的能力,是许多陆面模型的重要输入参数。本文旨在研究中国重要的南北气候分界带秦巴山区植被FPAR的时空变化特征。基于2006—2015年MODIS遥感数据及气象数据,采用趋势分析法对秦巴山区植被FPAR像元尺度的时空变化特征进行了分析,并利用相关分析法探讨了植被FPAR变化对气候变化的响应。结果表明:秦巴山区植被FPAR空间差异明显,呈西北和东北低、中部和东南部高的分布特征,并且随海拔的升高而降低,具有明显的垂直地带性; 2006—2015年秦巴山区植被FPAR空间变化表现为中部增加、四周减少的空间格局,显著增加的区域主要分布在嘉陵江、丹江流域及汉江下游地区,甘南高原及川西高原等地呈不显著减少趋势;近10年秦巴山区植被FPAR呈显著增加趋势,增速为4.8%·10 a~(-1)(P<0.05),以作物FPAR增加趋势最为明显(P<0.05),并且植被FPAR在冬季上升显著(P<0.05);从年际水平看,秦巴山区植被FPAR变化总体上与气温的关系比降水量更加密切,但存在植被类型差异:针叶林、阔叶林FPAR与年平均气温相关性更高,草地、作物FPAR受年降水量影响更大。
Fraction of absorbed photosynthetically active radiation( FPAR),the part of photosynthetically active radiation that is absorbed by vegetation,is one of the important parameters in terrestrial ecosystem simulating models. The purpose of this study was to clarify spatial-temporal changes of the FPAR in Qinling-Daba Mountains where is on the important north-south climate transitional zone in China. Based on the MODIS remote sensing data and climate datasets from2006 to 2015,a linear regression analysis was used to examine spatial-temporal changes of FPAR at pixel scale in Qinling-Daba Mountains. A correlation analysis was conducted to analyze the relationship between vegetation FPAR and climate factors. The results showed that there was spatial difference in FPAR distribution in the Qinling-Daba Mountains,with high FPAR values in the center and southeast and lower values in the northwest and northeast of study area. They decreased with altitude,with obvious vertical zonality along mountains. From 2006 to 2015,the FPAR increased in the central region and decreased in the surrounding area. The areas with significantly increased FPAR values were mainly distributed in the basins of Jialing River and Danjiang River and the downstream of Hanjiang River. The FPAR values slightly decreased in parts of the Gannan Plateau and the Western Sichuan Plateau. During last decade,the FPAR of vegetation,on the whole,appeared a significantly increasing trend with a rate of 4.8%·10 a-1( P<0.05) and the most outstanding vegetation was crop( P < 0. 05). Among the four seasons,the FPAR significantly increased in winter( P<0.05). Annually,the correlation between vegetation FPAR and climate factors showed that vegetation FPAR was more correlated with mean annual temperature than that with mean annual precipitation on all vegetation types. However,the correlations differed among vegetation types. Coniferous forest and broad-leaved forest FPAR had higher correlations with mean annual temperature than other types,while grasslands and croplands were influenced much more by mean annual precipitation than by mean annual temperature.
Fraction of absorbed photosynthetically active radiation( FPAR),the part of photosynthetically active radiation that is absorbed by vegetation,is one of the important parameters in terrestrial ecosystem simulating models. The purpose of this study was to clarify spatial-temporal changes of the FPAR in Qinling-Daba Mountains where is on the important north-south climate transitional zone in China. Based on the MODIS remote sensing data and climate datasets from2006 to 2015,a linear regression analysis was used to examine spatial-temporal changes of FPAR at pixel scale in Qinling-Daba Mountains. A correlation analysis was conducted to analyze the relationship between vegetation FPAR and climate factors. The results showed that there was spatial difference in FPAR distribution in the Qinling-Daba Mountains,with high FPAR values in the center and southeast and lower values in the northwest and northeast of study area. They decreased with altitude,with obvious vertical zonality along mountains. From 2006 to 2015,the FPAR increased in the central region and decreased in the surrounding area. The areas with significantly increased FPAR values were mainly distributed in the basins of Jialing River and Danjiang River and the downstream of Hanjiang River. The FPAR values slightly decreased in parts of the Gannan Plateau and the Western Sichuan Plateau. During last decade,the FPAR of vegetation,on the whole,appeared a significantly increasing trend with a rate of 4.8%·10 a-1( P<0.05) and the most outstanding vegetation was crop( P < 0. 05). Among the four seasons,the FPAR significantly increased in winter( P<0.05). Annually,the correlation between vegetation FPAR and climate factors showed that vegetation FPAR was more correlated with mean annual temperature than that with mean annual precipitation on all vegetation types. However,the correlations differed among vegetation types. Coniferous forest and broad-leaved forest FPAR had higher correlations with mean annual temperature than other types,while grasslands and croplands were influenced much more by mean annual precipitation than by mean annual temperature.
引文
白红英.2014.秦巴山区森林植被对环境变化的响应.北京:科学出版社.
包刚,包玉海,覃志豪,等.2013.近10年蒙古高原植被覆盖变化及其对气候的季节响应.地理科学,33(5):613-621.
崔晓临,白红英,王涛.2013.秦岭地区植被NDVI海拔梯度差异及其气温响应.资源科学,35(3):618-626.
邓晨晖,白红英,高山,等.2018.秦岭植被覆盖时空变化及其对气候变化与人类活动的双重响应.自然资源学报,33(3):425-438.
邓晨晖,白红英,翟丹平,等.2017.气候变化背景下1964-2015年秦岭植物物候变化.生态学报,37(23):7882-7893.
董泰锋,蒙继华,吴炳方.2012.基于遥感的光合有效辐射吸收比率(FPAR)估算方法综述.生态学报,32(22):7190-7201.
盖颖颖,刘媛,范闻捷,等.2014.黑河流域植被FAPAR时间序列模拟分析与预测.北京大学学报:自然科学版,50(3):515-525.
高彦净.2015.基于CASA模型的植被NPP时空动态研究---以甘肃白龙江流域为例(硕士学位论文).兰州:兰州大学.
贺映娜,白红英,高翔,等.2011.基于NDVI的米仓山植被覆盖变化趋势分析.西北植物学报,31(8):1677-1682.
蒋冲,朱枫,杨陈,等.2013.秦岭南北地区光合有效辐射时空变化及突变特征.地理科学进展,32(3):435-446.
李丽.2010.基于多源遥感数据的PAR及FPAR反演算法研究(博士学位论文).北京:中国科学院研究生院.
李登科,王钊.2018.基于MOD17A3的中国陆地植被NPP变化特征分析.生态环境学报,27(3):397-405.
李晓兵,史培军.2000.中国典型植被类型NDVI动态变化与气湿,降水变化的敏感性分析.植物生态学报,24(3):379-382.
李晓宇,李飞,包玉海,等.2015.基于HJ-1CCD影像的呼伦贝尔草原区MODIS/FPAR产品验证与分析.遥感技术与应用,30(6):1129-1137.
刘思瑶,卢涛,唐斌,等.2013.基于CASA模型的四川植被净初级生产力及其时空格局分析.四川农业大学学报,31(3):269-276,282.
刘宪锋,潘耀忠,朱秀芳,等.2015.2000-2014年秦巴山区植被覆盖时空变化特征及其归因.地理学报,70(5):705-716.
马杰.2018.基于卫星遥感的FAPAR产品在中国区域的评估与应用(硕士学位论文).南京:南京大学.
穆少杰,李建龙,陈奕兆,等.2012.2001-2010年内蒙古植被覆盖度时空变化特征.地理学报,67(9):1255-1268.
孙华,白红英,张清雨,等.2009.秦岭南北地区植被覆盖对区域环境变化的响应.环境科学报,9(12):2635-2641.
孙华.2010.近30年来秦岭南北坡植被指数时空差异及其对区域气候的响应(硕士学位论文).西安:西北大学.
王强,张廷斌,易桂花,等.2017.横断山区2004-2014年植被NPP时空变化及其驱动因子.生态学报,37(9):3084-3095.
王伟军,赵雪雁,万文玉,等.2016.2000-2014年甘南高原植被覆盖度变化及其对气候变化的响应.生态学杂志,35(9):2494-2504.
王正兴,王亚琴.2013.利用LDOPE工具解码MODIS陆地产品质量信息.遥感技术与应用,28(3):459-466.
谢军飞,郭佳.2016.2010-2012年北京植被光合有效辐射吸收比例的时空变化.应用生态学报,27(4):1203-1210.
左艳.2016.基于全球土地覆盖产品的安徽省土地覆盖和景观格局动态变化研究(硕士学位论文).合肥:安徽大学.
Chen BX,Zhang XZ,Sun YF,et al.2017.Alpine grassland f PAR change over the Northern Tibetan Plateau from 2002to 2011.Advances in Climate Change Research,8:108-116.
Dong TF,Liu JG,Shang JL,et al.2016a.Assessing the impact of climate variability on cropland productivity in the Canadian Prairies using time series MODIS FAPAR.Remote Sensing,8:1-18.
Dong TF,Wu BF,Meng JH,et al.2016b.Sensitivity analysis of retrieving fraction of absorbed photosynthetically active radiation(FPAR)using remote sensing data.Acta Ecologica Sinica,36:1-7.
Tao X,Liang SL,Wang DD.2015.Assessment of five global satellite products of fraction of absorbed photosynthetically active radiation:Inter-comparison and direct validation against ground-based data.Remote Sensing of Environment,163:270-285.
Thompson SD,Nelson TA,Coops NC,et al.2017.Global spatial-temporal variability in terrestrial productivity and phenology regimes between 2000 and 2012.Annals of the American Association of Geographers,107:1519-1537.
Tsalyuk M,Kelly M,Getz WM.2017.Improving the prediction of African savanna vegetation variables using time series of MODIS products.ISPRS Journal of Photogrammetry and Remote Sensing,131:77-91.
Wu JS,Fu G.2018.Modelling aboveground biomass using MODIS FPAR/LAI data in alpine grasslands of the Northern Tibetan Plateau.Remote Sensing Letters,9:150-159.
Yan K,Park TJ,Yan GJ,et al.2016a.Evaluation of MODISLAI/FPAR product collection 6.Part 1:Consistency and improvements.Remote Sensing,8:1-16.
Yan K,Park TJ,Yan GJ,et al.2016b.Evaluation of MODISLAI/FPAR product collection 6.Part 2:Validation and inter-comparison.Remote Sensing,8:1-26.
包刚,包玉海,覃志豪,等.2013.近10年蒙古高原植被覆盖变化及其对气候的季节响应.地理科学,33(5):613-621.
崔晓临,白红英,王涛.2013.秦岭地区植被NDVI海拔梯度差异及其气温响应.资源科学,35(3):618-626.
邓晨晖,白红英,高山,等.2018.秦岭植被覆盖时空变化及其对气候变化与人类活动的双重响应.自然资源学报,33(3):425-438.
邓晨晖,白红英,翟丹平,等.2017.气候变化背景下1964-2015年秦岭植物物候变化.生态学报,37(23):7882-7893.
董泰锋,蒙继华,吴炳方.2012.基于遥感的光合有效辐射吸收比率(FPAR)估算方法综述.生态学报,32(22):7190-7201.
盖颖颖,刘媛,范闻捷,等.2014.黑河流域植被FAPAR时间序列模拟分析与预测.北京大学学报:自然科学版,50(3):515-525.
高彦净.2015.基于CASA模型的植被NPP时空动态研究---以甘肃白龙江流域为例(硕士学位论文).兰州:兰州大学.
贺映娜,白红英,高翔,等.2011.基于NDVI的米仓山植被覆盖变化趋势分析.西北植物学报,31(8):1677-1682.
蒋冲,朱枫,杨陈,等.2013.秦岭南北地区光合有效辐射时空变化及突变特征.地理科学进展,32(3):435-446.
李丽.2010.基于多源遥感数据的PAR及FPAR反演算法研究(博士学位论文).北京:中国科学院研究生院.
李登科,王钊.2018.基于MOD17A3的中国陆地植被NPP变化特征分析.生态环境学报,27(3):397-405.
李晓兵,史培军.2000.中国典型植被类型NDVI动态变化与气湿,降水变化的敏感性分析.植物生态学报,24(3):379-382.
李晓宇,李飞,包玉海,等.2015.基于HJ-1CCD影像的呼伦贝尔草原区MODIS/FPAR产品验证与分析.遥感技术与应用,30(6):1129-1137.
刘思瑶,卢涛,唐斌,等.2013.基于CASA模型的四川植被净初级生产力及其时空格局分析.四川农业大学学报,31(3):269-276,282.
刘宪锋,潘耀忠,朱秀芳,等.2015.2000-2014年秦巴山区植被覆盖时空变化特征及其归因.地理学报,70(5):705-716.
马杰.2018.基于卫星遥感的FAPAR产品在中国区域的评估与应用(硕士学位论文).南京:南京大学.
穆少杰,李建龙,陈奕兆,等.2012.2001-2010年内蒙古植被覆盖度时空变化特征.地理学报,67(9):1255-1268.
孙华,白红英,张清雨,等.2009.秦岭南北地区植被覆盖对区域环境变化的响应.环境科学报,9(12):2635-2641.
孙华.2010.近30年来秦岭南北坡植被指数时空差异及其对区域气候的响应(硕士学位论文).西安:西北大学.
王强,张廷斌,易桂花,等.2017.横断山区2004-2014年植被NPP时空变化及其驱动因子.生态学报,37(9):3084-3095.
王伟军,赵雪雁,万文玉,等.2016.2000-2014年甘南高原植被覆盖度变化及其对气候变化的响应.生态学杂志,35(9):2494-2504.
王正兴,王亚琴.2013.利用LDOPE工具解码MODIS陆地产品质量信息.遥感技术与应用,28(3):459-466.
谢军飞,郭佳.2016.2010-2012年北京植被光合有效辐射吸收比例的时空变化.应用生态学报,27(4):1203-1210.
左艳.2016.基于全球土地覆盖产品的安徽省土地覆盖和景观格局动态变化研究(硕士学位论文).合肥:安徽大学.
Chen BX,Zhang XZ,Sun YF,et al.2017.Alpine grassland f PAR change over the Northern Tibetan Plateau from 2002to 2011.Advances in Climate Change Research,8:108-116.
Dong TF,Liu JG,Shang JL,et al.2016a.Assessing the impact of climate variability on cropland productivity in the Canadian Prairies using time series MODIS FAPAR.Remote Sensing,8:1-18.
Dong TF,Wu BF,Meng JH,et al.2016b.Sensitivity analysis of retrieving fraction of absorbed photosynthetically active radiation(FPAR)using remote sensing data.Acta Ecologica Sinica,36:1-7.
Tao X,Liang SL,Wang DD.2015.Assessment of five global satellite products of fraction of absorbed photosynthetically active radiation:Inter-comparison and direct validation against ground-based data.Remote Sensing of Environment,163:270-285.
Thompson SD,Nelson TA,Coops NC,et al.2017.Global spatial-temporal variability in terrestrial productivity and phenology regimes between 2000 and 2012.Annals of the American Association of Geographers,107:1519-1537.
Tsalyuk M,Kelly M,Getz WM.2017.Improving the prediction of African savanna vegetation variables using time series of MODIS products.ISPRS Journal of Photogrammetry and Remote Sensing,131:77-91.
Wu JS,Fu G.2018.Modelling aboveground biomass using MODIS FPAR/LAI data in alpine grasslands of the Northern Tibetan Plateau.Remote Sensing Letters,9:150-159.
Yan K,Park TJ,Yan GJ,et al.2016a.Evaluation of MODISLAI/FPAR product collection 6.Part 1:Consistency and improvements.Remote Sensing,8:1-16.
Yan K,Park TJ,Yan GJ,et al.2016b.Evaluation of MODISLAI/FPAR product collection 6.Part 2:Validation and inter-comparison.Remote Sensing,8:1-26.