2001—2015年天山地区草地NDVI时空演变和气候驱动特征分析
|
摘要
草地分布时空特征演变和气候驱动特征研究对草地生态环境评价意义重大。基于2000—2015年MOD13Q1 NDVI数据开展了天山地区近15年NDVI年均状况及其变化趋势的空间制图,以及12种典型草地NDVI年均状况等级及其面积发展趋势的时空统计。根据地面气象站同期日观测数据形成了3—8月≥10℃积温和5月、6月、7月及5—6月累积降水序列并完成了空间制图,与天山地区7月NDVI均值进行相关分析和F检验,得到NDVI水热影响空间特征。结果显示,不同草地类型NDVI差异显著,温性草原化荒漠、温性荒漠和温性草原NDVI集中在[0.2,0.4],低地草甸、高寒草甸、高寒草原、沼泽集中在[0.4,0.7],山地草甸、改良草地和热性灌草丛集中在[0.7,1.0],温性荒漠草原类和温性草甸草原类分别介于[0.4,0.7]和[0.7,1.0]。约44%的区域NDVI呈增加趋势,其中8.3%显著增加;约10.6%的区域NDVI显著下降。山地草甸、温性草甸草原和改良草地及热性灌草丛类的NDVI下降趋势显著,温性草原化荒漠、温性荒漠、低地草甸和沼泽增加趋势显著,其他草地类型变化趋势不显著。不同草地类型水热影响程度差异显著,约41%的区域与降水量呈显著正相关,31%的区域与温度呈显著负相关,说明草地生态系统受气候环境因子影响程度较大。
The study on spatio-temporal evolution characteristics of grassland and climate drive is of great significance to the evaluation of grassland ecological environment. Based on the MOD13Q1 data covering Tianshan Mountain area during the 2000—2015 years, the paper performed annually averaged situation of NDVI data and spatial mapping of its development trend in the nearest 15 years, and presented the average annual level of NDVI value for 12 typical grassland types and their development trends in the past 15 years. Using the observed meteorological daily data over the same period, accumulated temperature more than 10 degrees from March to August were calculated, and cumulative rainfall sequence in May, June and July and May—June were formed so as to realize spatial mapping. Furthermore, spatial characteristics of water and heat effect on the value of NDVI were achieved performing a correlation analysis with the averaged NDVI value on July and a F test. The results showed the NDVI values of different grass area differ significantly, and the NDVI value of temperate steppe-desert, temperate desert and temperate steppe types concentrated in [0.2, 0.4]; The types of Lowland meadow, high-cold meadow, high-cold steppe and marsh concentrated in [0.4, 0.7]; The types of temperate montane meadow, tropical shrub herbage, improved grassland concentrated in [0.7, 1.0]; These types of temperate desert steppe, temperate meadow steppe concentrated in [0.4, 0.7] and [0.7, 1.0], respectively. In addition, NDVI values of about 44% regions showed a rise trend, in which showed a significant rise in the 8.3% regions such as temperate steppe-desert, temperate desert, lowland meadow and marsh, but showed a significant decline in the 10.6% regions such as temperate montane meadow, temperate meadow steppe, improved grassland and tropical shrub herbage. NDVI values of other grassland types don not vary significantly. Additionally, water and heat had significant influence on different grassland types, it showed a significant positive correlation between NDVI value and precipitation in the about 41% area and a significant negative correlation in the about 31% area. Conclusions can be drawn that grassland ecosystem is greatly affected by climate and environmental factors.
The study on spatio-temporal evolution characteristics of grassland and climate drive is of great significance to the evaluation of grassland ecological environment. Based on the MOD13Q1 data covering Tianshan Mountain area during the 2000—2015 years, the paper performed annually averaged situation of NDVI data and spatial mapping of its development trend in the nearest 15 years, and presented the average annual level of NDVI value for 12 typical grassland types and their development trends in the past 15 years. Using the observed meteorological daily data over the same period, accumulated temperature more than 10 degrees from March to August were calculated, and cumulative rainfall sequence in May, June and July and May—June were formed so as to realize spatial mapping. Furthermore, spatial characteristics of water and heat effect on the value of NDVI were achieved performing a correlation analysis with the averaged NDVI value on July and a F test. The results showed the NDVI values of different grass area differ significantly, and the NDVI value of temperate steppe-desert, temperate desert and temperate steppe types concentrated in [0.2, 0.4]; The types of Lowland meadow, high-cold meadow, high-cold steppe and marsh concentrated in [0.4, 0.7]; The types of temperate montane meadow, tropical shrub herbage, improved grassland concentrated in [0.7, 1.0]; These types of temperate desert steppe, temperate meadow steppe concentrated in [0.4, 0.7] and [0.7, 1.0], respectively. In addition, NDVI values of about 44% regions showed a rise trend, in which showed a significant rise in the 8.3% regions such as temperate steppe-desert, temperate desert, lowland meadow and marsh, but showed a significant decline in the 10.6% regions such as temperate montane meadow, temperate meadow steppe, improved grassland and tropical shrub herbage. NDVI values of other grassland types don not vary significantly. Additionally, water and heat had significant influence on different grassland types, it showed a significant positive correlation between NDVI value and precipitation in the about 41% area and a significant negative correlation in the about 31% area. Conclusions can be drawn that grassland ecosystem is greatly affected by climate and environmental factors.
引文
CHEN X Q,HU B,YU R.2005.Spatial and temporal of phenological growing season and climate change impacts in temperate Eastern China[J].Global Change Biology,11(7):1118-1130.
HEUMANN B W,SEAQUIST J W,EKLUNDH L,et al.2007.AVHRRderived phenological change in the Sahel and Soudan,Africa,1982-2005[J].Remote Sensing of Environment,108(4):385-392.
JIN Y X,XU B,YANG X C,et al.2011.Remote sensing dynamic estimation of grass production in Xilinguole,Inner Mongolia[J].Scientia Sinica,41(12):1185-1195.
LEISHER C,HESS S,BOUCHER T M,et al.2012.Measuring the impacts of community-based grasslands management in Mongolia's Gobi[J].Plos One,7(2):e30991.
MUUKKONEN P,HEISKANEN J.2007.Biomass estimation over a large area based on standwise forest inventory data and ASTER and MODISsatellite data:A possibility to verify carbon inventories[J].Remote Sensing of Environment,107(4):617-624.
OUYANG W,HAO F H,SKIDMORE A K,et al.2012.Integration of multi-sensor data to assess grassland dynamics in a Yellow River sub-watershed[J].Ecological Indicators,18:163-170.
PIAO S L,FANG J Y,ZHOU L M,et al.2003.Interannual varia-tions of monthly and seasonal normalized difference vegetation index(NDVI)in China from 1982 to 1999[J].Journal of Geophysical Research,108(D14):4401.
PIAO S L,FANG J Y,ZHOU L M,et al.2007.Changes in biomass carbon stocks in China's grasslands between 1982 and 1999[J].Global Biogeochemical Cycles,21(2):B2002(1-10).
SEAQUIST J W,HICKLER T,EKLUNDH L.2009.Disentangling the effects of climate and people on Sahel vegetation dynamics[J].Biogeosciences,6(3):469-477.
曹孟磊,肖继东,陈爱京,等.2016.伊犁地区不同草地类型植被指数与气候因子的关系[J].沙漠与绿洲气象,10(6):73-80.
杜加强,赵晨曦,贾尔恒·阿哈提,等.2016.近30 a新疆月NDVI动态变化及其驱动因子分析[J].农业工程学报,32(5):172-181.
刘芳,张红旗,董光龙.2014.伊犁河谷草地植被NDVI变化及其降水敏感性特征[J].资源科学,36(8):1724-1731.
刘新平,吕晓.2009.新疆牧草地资源利用动态变化及其绩效分析[J].干旱区地理,32(1):81-85.
王佃来,刘文萍,黄心渊.2013.基于Sen+Mann-Kendall的北京植被变化趋势分析[J].计算机工程与应用,49(5):13-17.
王新欣,朱进忠,范燕敏,等.2008.利用EOS/MODIS植被指数建立草地估产模型的研究[J].新疆农业科学,45(5):843-846.
夏浩铭,李爱农,赵伟,等.2015.2001-2010年秦岭森林物候时空变化遥感监测[J].地理科学进展,34(10):1297-1305.
谢国辉,李晓东,周立平,等.2007.气候因子影响天山北坡植被指数时空分布研究[J].地球科学进展,22(6):618-624.
许鹏.1993.新疆草地资源及其利用[M].乌鲁木齐:科技卫生出版社.
闫俊杰,乔木,周宏飞,等.2013.基于MODIS/NDVI的新疆伊犁河谷植被变化[J].干旱区地理(汉文版),36(3):512-519.
严建武,李春娥,袁雷,等.2008.EOS-MODIS数据在草地资源监测中的应用进展综述[J].草业科学,25(4):1-9.
HEUMANN B W,SEAQUIST J W,EKLUNDH L,et al.2007.AVHRRderived phenological change in the Sahel and Soudan,Africa,1982-2005[J].Remote Sensing of Environment,108(4):385-392.
JIN Y X,XU B,YANG X C,et al.2011.Remote sensing dynamic estimation of grass production in Xilinguole,Inner Mongolia[J].Scientia Sinica,41(12):1185-1195.
LEISHER C,HESS S,BOUCHER T M,et al.2012.Measuring the impacts of community-based grasslands management in Mongolia's Gobi[J].Plos One,7(2):e30991.
MUUKKONEN P,HEISKANEN J.2007.Biomass estimation over a large area based on standwise forest inventory data and ASTER and MODISsatellite data:A possibility to verify carbon inventories[J].Remote Sensing of Environment,107(4):617-624.
OUYANG W,HAO F H,SKIDMORE A K,et al.2012.Integration of multi-sensor data to assess grassland dynamics in a Yellow River sub-watershed[J].Ecological Indicators,18:163-170.
PIAO S L,FANG J Y,ZHOU L M,et al.2003.Interannual varia-tions of monthly and seasonal normalized difference vegetation index(NDVI)in China from 1982 to 1999[J].Journal of Geophysical Research,108(D14):4401.
PIAO S L,FANG J Y,ZHOU L M,et al.2007.Changes in biomass carbon stocks in China's grasslands between 1982 and 1999[J].Global Biogeochemical Cycles,21(2):B2002(1-10).
SEAQUIST J W,HICKLER T,EKLUNDH L.2009.Disentangling the effects of climate and people on Sahel vegetation dynamics[J].Biogeosciences,6(3):469-477.
曹孟磊,肖继东,陈爱京,等.2016.伊犁地区不同草地类型植被指数与气候因子的关系[J].沙漠与绿洲气象,10(6):73-80.
杜加强,赵晨曦,贾尔恒·阿哈提,等.2016.近30 a新疆月NDVI动态变化及其驱动因子分析[J].农业工程学报,32(5):172-181.
刘芳,张红旗,董光龙.2014.伊犁河谷草地植被NDVI变化及其降水敏感性特征[J].资源科学,36(8):1724-1731.
刘新平,吕晓.2009.新疆牧草地资源利用动态变化及其绩效分析[J].干旱区地理,32(1):81-85.
王佃来,刘文萍,黄心渊.2013.基于Sen+Mann-Kendall的北京植被变化趋势分析[J].计算机工程与应用,49(5):13-17.
王新欣,朱进忠,范燕敏,等.2008.利用EOS/MODIS植被指数建立草地估产模型的研究[J].新疆农业科学,45(5):843-846.
夏浩铭,李爱农,赵伟,等.2015.2001-2010年秦岭森林物候时空变化遥感监测[J].地理科学进展,34(10):1297-1305.
谢国辉,李晓东,周立平,等.2007.气候因子影响天山北坡植被指数时空分布研究[J].地球科学进展,22(6):618-624.
许鹏.1993.新疆草地资源及其利用[M].乌鲁木齐:科技卫生出版社.
闫俊杰,乔木,周宏飞,等.2013.基于MODIS/NDVI的新疆伊犁河谷植被变化[J].干旱区地理(汉文版),36(3):512-519.
严建武,李春娥,袁雷,等.2008.EOS-MODIS数据在草地资源监测中的应用进展综述[J].草业科学,25(4):1-9.