官渡河流域植被覆盖变化与地形因子相关性
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摘要
以南水北调中线水源区源头之一的官渡河流域为研究区域,区域内以山地为主,生态环境脆弱。基于GIS和RS技术,利用1990年、1999年、2004年、2007年、2010年Landsat TM遥感影像,基于像元二分模型和变化斜率法,从数理统计角度定量估算了研究区各时期植被覆盖度及其时空分布特征。结果表明:(1)植被覆盖度在不同河段呈现明显的规律性,上、中、下游植被覆盖度5期平均值分别为94.52%,87%,81.69%。(2)植被覆盖变化受地形因子影响比较明显,植被覆盖度与不同地形因子响应程度不同,对不同时期植被覆盖度,高程和坡度对其影响明显高于坡向。随着坡度的不断增加,植被覆盖度也随着增大;整体上向阳区植被覆盖度要大于同区域的背阳区;官渡河流域不同时期植被覆盖度随着高程的增加均出现先增加后减少的趋势。(3)不同地质单元组植被覆盖变化各不相同。
In South-to-North Water Transfer Project source, Guandu River Basin was selected as the study area. The area is mainly mountainous and the ecological environment is fragile. Based on GIS and RS technology, using 1990, 1999, 2004, 1999 and 2010, Landsat TM remote sensing image, binary model based on pixels, and changes the slope method, vegetation coverage of different periods in the study area was quantitatively estimated and its space-time distribution characteristics were analyzed. The results showed that:(1) the vegetation coverage had obvious regularity in different river sections, the average values of the five periods of vegetation coverage in upper, middle and lower reaches were 94.52%, 87%, and 81.69%, respectively;(2) the change of vegetation cover was obviously influenced by topographic factors, the vegetation coverage was different from that of different terrain factors, and the effect of vegetation coverage, elevation and slope on different periods was significantly higher than that of aspect; as the slope increases, the vegetation coverage increases; the vegetation coverage of the whole area was greater than that of the region in terms of slope aspect; the vegetation coverage of Guandu River Basin increased with the increase of elevation in different periods;(3) vegetation cover changes in different geological units were different.
In South-to-North Water Transfer Project source, Guandu River Basin was selected as the study area. The area is mainly mountainous and the ecological environment is fragile. Based on GIS and RS technology, using 1990, 1999, 2004, 1999 and 2010, Landsat TM remote sensing image, binary model based on pixels, and changes the slope method, vegetation coverage of different periods in the study area was quantitatively estimated and its space-time distribution characteristics were analyzed. The results showed that:(1) the vegetation coverage had obvious regularity in different river sections, the average values of the five periods of vegetation coverage in upper, middle and lower reaches were 94.52%, 87%, and 81.69%, respectively;(2) the change of vegetation cover was obviously influenced by topographic factors, the vegetation coverage was different from that of different terrain factors, and the effect of vegetation coverage, elevation and slope on different periods was significantly higher than that of aspect; as the slope increases, the vegetation coverage increases; the vegetation coverage of the whole area was greater than that of the region in terms of slope aspect; the vegetation coverage of Guandu River Basin increased with the increase of elevation in different periods;(3) vegetation cover changes in different geological units were different.
引文
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[22]陈云浩,李晓兵,史培军,等.北京海淀区植被覆盖的遥感动态研究[J].植物生态学报,2001(5):588-593.
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[24]马明国,董立新,王雪梅.过去21a中国西北植被覆盖动态监测与模拟[J].冰川冻土,2003(2):232-236.
[25]王毅,郭跃.喀斯特地貌区植被覆盖与地形因子的空间关系分析:以贵州普定县为例[J].长江流域资源与环境,2018,27(1):157D167.
[26]张静,任志远.汉江流域植被净初级生产力时空格局及成因[J].生态学报,2016,36(23):7667-7677.
[27]张方方,齐述华,舒晓波,廖富强.南方山地丘陵土地利用类型的地形影响GIS分析:以江西省为例[J].地球信息科学学报,2010,12(6):784-790.
[2]Gitelson A A,Kaufman Y J,Stark R,et al.Novel algorithms for remote estimation of vegetation fraction[J].Remote Sens Environ,2002,80(1):76-87.
[3]蔡朝朝,安沙舟,蒲智,等.基于TM NDVI的库尔勒市域植被覆盖动态变化[J].草业科学,2015,32(7):1069-1078.
[4]Fu B,Burgher I.Riparian vegetation NDVI dynamics and its relationship with climate,surface water and groundwater.Journal of Arid Environment[J].Journal of Arid Environments,2015,113:59-68.
[5]Johansen B,Tmmervik H.The relationship between phytomass,NDVI and vegetation communities on Svalbard[J].International Journal of Applied Earth Observation and Geoinformation,2014,27(Part A):20-30.
[6]Kong D,Zhang Q,Singh V P,et al.Seasonal vegetation response to climate change in the Northern Hemisphere(1982-2013)[J].Global and Planetary Change,2017,148:1-8.
[7]Posse G,Cingolani A M.Environmental controls of NDVIand sheep production in the Tierra del Fuego steppe of Argentina[J].Applied Vegetation Science,2000,32:253-260.
[8]张含玉,方怒放,史志华.黄土高原植被覆盖时空变化及其对气候因子的响应[J].生态学报,2016,36(13):3960-3968.
[9]何月,樊高峰,张小伟,等.浙江省植被NDVI动态及其对气候的响应[J].生态学报,2012,32(14):4352-4362.
[10]姚晨,黄微,李先华.地形复杂区域的典型植被指数评估[J].遥感技术与应用,2009,24(4):496-501.
[11]芮孝芳,蒋成煜.流域水文与地貌特征关系研究的回顾与展望[J].水科学进展,2010,21(4):444-449.
[12]Ostendorf B,Reynolds J F.A model of arctic tundra vegetation derived from topographic gradientss[J].Landscape Ecology,1998,13(3):187-201.
[13]Herzog F,Lausch A,Eckhard M L,et al.Landscape metrics for assessment of landscape destruction and rehabilitation[J].Environmental Management,2001,27(1):91-107.
[14]程圣东,李占斌,鲁克新,等.文安驿流域植被覆盖度时空分异及其与地貌因子关系研究[J].西安理工大学学报,2011,27(2):145-150.
[15]李斌斌,李占斌,宇涛,等.基于归一化植被指数的流域植被覆盖分形维数研究[J].农业工程学报,2014,30(15):239-247.
[16]李薇,谈明洪.太行山区不同坡度NDVI变化趋势差异分析[J].中国生态农业学报,2017,25(4):509-519.
[17]吴志杰,何国金,黄绍霖,等.南方丘陵区植被覆盖度遥感估算的地形效应评估[J].遥感学报,2017,21(1):159-167.
[18]崔英,何意,计强,等.南水北调中线水源地堵河流域降水变化分析[J].湖北农业科学,2017,56(14):2657-2660.
[19]姚道强,任玮颖,徐茂玲.堵河流域致洪暴雨气候特征分析[J].安徽农业科学,2010,38(18)9623-9626.
[20]朱长明,沈占锋,骆剑承,等.基于MODIS数据的Landsat-7SLC-off影像修复方法研究[J].测绘学报,2010,39(3):251-256.
[21]马娜,胡云锋,庄大方,等.基于遥感和像元二分模型的内蒙古正蓝旗植被覆盖度格局和动态变化[J].地理科学,2012,32(2):251-256.
[22]陈云浩,李晓兵,史培军,等.北京海淀区植被覆盖的遥感动态研究[J].植物生态学报,2001(5):588-593.
[23]Sandholt I,Rasmussen K,Andersen J.A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status.Remote Sensing of Environment[J].Remote Sensing of Environment,2002,79(2):213-224.
[24]马明国,董立新,王雪梅.过去21a中国西北植被覆盖动态监测与模拟[J].冰川冻土,2003(2):232-236.
[25]王毅,郭跃.喀斯特地貌区植被覆盖与地形因子的空间关系分析:以贵州普定县为例[J].长江流域资源与环境,2018,27(1):157D167.
[26]张静,任志远.汉江流域植被净初级生产力时空格局及成因[J].生态学报,2016,36(23):7667-7677.
[27]张方方,齐述华,舒晓波,廖富强.南方山地丘陵土地利用类型的地形影响GIS分析:以江西省为例[J].地球信息科学学报,2010,12(6):784-790.