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  • CN 62-1070/P
  • ISSN 1000-694X
  • 双月刊 创刊于1981年
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生物与土壤

科尔沁沙地几种固沙植物光谱-生物量模型构建与分析

  • 岳喜元 ,
  • 常学礼 ,
  • 刘良旭 ,
  • 黄海涛
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  • 鲁东大学 地理与规划学院, 山东 烟台 264025
岳喜元(1987- ),男,安徽蚌埠人,硕士研究生,主要从事土地利用变化与遥感监测研究.Email:yuexiyuan393@126.com

收稿日期: 2013-10-23

  修回日期: 2013-12-16

  网络出版日期: 2014-11-20

基金资助

国家自然科学基金项目(41271193);国家科技支撑计划项目(2011BAC07B02)资助

Spectrum-biomass Models for Several Sand-fixing Plant Species in the Horqin Sandy Land

  • Yue Xiyuan ,
  • Chang Xueli ,
  • Liu Liangxu ,
  • Huang Haitao
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  • College of Geography and Planning, Ludong University, Yantai 264025, Shandong, China

Received date: 2013-10-23

  Revised date: 2013-12-16

  Online published: 2014-11-20

摘要

在控制背景反射噪音、植被盖度和水分含量的条件下,利用ASD光谱仪对科尔沁沙地4种主要固沙植物杨树(Populus spp.)、黄柳(Salix gordejevii)、小叶锦鸡儿(Caragana microphylla)、樟子松(Pinus sylvestris)光谱反射特征和地面光谱生物量模型构建进行了研究.结果表明:科尔沁沙地4种主要固沙植物光谱反射曲线的趋势基本一致,但是在620~670 nm与841~876 nm波长范围内存在差别,其中在波长620~670 nm最易识别的植物为小叶锦鸡儿,其次是黄柳、杨树,在波长841~876 nm范围最易识别的植物为樟子松、杨树.不同植物的NDVI与盖度和生物量的关系密切,模型拟合精度较高.相对而言,NDVI-盖度模型优于NDVI-生物量模型.不同植物种构建的NDVI盖度模型计算结果相差较小,而NDVI生物量模型的计算结果相差较大.在区域植被生产力遥感监测中,植被样方选择要考虑优势植物种影响,数据采样要涵盖研究区主要植物种.

本文引用格式

岳喜元 , 常学礼 , 刘良旭 , 黄海涛 . 科尔沁沙地几种固沙植物光谱-生物量模型构建与分析[J]. 中国沙漠, 2014 , 34(6) : 1496 -1502 . DOI: 10.7522/j.issn.1000-694X.2013.00449

Abstract

ASD spectrometer was used to the study on the spectral reflectance of four kinds of sand-fixing plants Populus spp., Salix gordejevii, Caragana microphylla and Pinus sylvestris in Horqin sandyland under the controlled background reflectance noise, vegetation coverage and plant water content, and its ground spectral biomass models were analyzed by using NDVI and plant coverage and above ground biomass, respectively. The results showed that the trend of spectral reflection curves of four kinds of sand-fixed plant species was basically similar, but there were differences in wavelength of 620-670 nm and 841-876 nm. C. microphylla was one of the easiest plants to be distinguished in wavelength of 620-670 nm, following S. gordejevii and Populus spp., P. sylvestris and Populus spp. were easy to be distinguished in the wavelength of 841-876 nm. The relationship between NDVI and vegetation coverage and biomass was very close for the four, and the fitting precision of the models were highest. Compared with them, the models of NDVI-vegetation coverage were better than the NDVI-biomass because the differences of calculated results by the NDVI-coverage models were very smaller than the calculated results by the models of NDVI-biomass of these. However, the influence of dominant plant species should be paid more attention and conformed them involved in the quadrats sampling during remote sensing monitoring in regional vegetation productivity.

参考文献

[1] Zheng X,Eltahir E A B.The role of vegetation in the dynamics of West African monsoons[J].Journal of Climate,1998,11(8):2078-2096.
[2] 郭妮.植被指数及其研究进展[J].干旱气象,2003,21(4):71-75.
[3] Adam E,Mutanga O,Rugege D.Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation:a review[J].Wetlands Ecology and Management,2010,18(3):281-296.
[4] Fava F,Colombo R,Bocchi S,et al.Identification of hyperspectral vegetation indices for Mediterranean pasture characterization[J].International Journal of Applied Earth Observation and Geoinformation,2009,11(4):233-243.
[5] Magiera A,Feilhauer H,Otte A,et al.Relating canopy reflectance to the vegetation composition of mountainous grasslands in the Greater Caucasus[J].Agriculture,Ecosystems & Environment,2013,177:101-112.
[6] 张凯,郭妮,王小平,等.陇中黄土高原春小麦光谱反射特征[J].生态学杂志,2008,27(3):369-373.
[7] 孙小艳,常学礼,张宁,等.不同取样单元对干旱区绿洲小麦地上生物量光谱估算模型的影响[J].中国沙漠,2012,32(2):568-573.
[8] 刘庆生,刘高焕,储晓雷.水稻、大豆与芦苇农田冠层光谱特征研究——以辽河三角洲为例[J].中国生态农业学报,2006,14(2):66-69.
[9] 朱西存,赵庚星,王瑞燕,等.苹果叶片的高光谱特征及其色素含量监测[J].中国农业科学,2010,43(6):1189-1197.
[10] 万余庆,阎永忠,张凤丽.延河流域植物光谱特征分析[J].国土资源遥感,2001,49(3):15-20.
[11] 范燕敏,武红旗,靳瑰丽.新疆草地类型高光谱特征分析[J].草业科学,2006,23(6):15-18.
[12] 孙成明,刘涛,田婷,等.南方3种类型草地地上生物量的光谱估测模型[J].扬州大学学报(农业与生命科学版),2012,33(4):51-55.
[13] Spanglet H J,Ustin S L,Rejmankova E.Spectral reflectance characteristics of California subalpine marsh plant communities[J].Wetlands,1998,18(3):307-319.
[14] Schmidt K S,Skidmore A K.Spectral discrimination of vegetation types in a coastal wetland[J].Remote Sensing of Environment,2003,85(1):92-108.
[15] Gao J X,Chen Y M,Lü S H,et al.A ground spectral model for estimating biomass at the peak of the growing season in Hulunbeier grassland,Inner Mongolia,China[J].International Journal of Remote Sensing,2012,33(13):4029-4043.
[16] 范文义,杜华强,刘哲.科尔沁沙地地物光谱数据分析[J].东北林业大学学报,2004,32(2):45-48.
[17] 刘新民,赵哈林,赵爱芬,等.科尔沁沙地风沙环境与植被[M].北京:科学出版社,1996.
[18] 常学礼,赵文智.樟子松、小叶杨水分生理及林地水分状况的研究[J].中国沙漠,1990,10(4):18-24.
[19] 张华,何红,李锋瑞,等.科尔沁沙地灌木对风沙土壤的生态效应[J].地理研究,2005,24(5):708-716.
[20] 贺山峰,蒋德明,阿拉木萨,等.科尔沁沙地小叶锦鸡儿灌木林固沙效应的研究[J].水土保持学报,2007,21(1):84-87.
[21] 曾德慧,姜凤岐,范志平,等.樟子松人工固沙林稳定性的研究[J].应用生态学报,1996,7(4):337-343.
[22] 张华,李锋瑞,张铜会,等.科尔沁沙地人工杨树林生态服务效能评价[J].应用生态学报,2003,14(10):1591-1596.
[23] 郭轶瑞,赵哈林,赵学勇,等.科尔沁沙地人工林下结皮发育对表土特性影响的研究[J].中国沙漠,2007,27(6):1000-1006.
[24] 赵哈林,苏永中,张华,等.灌丛对流动沙地土壤特性和草本植物的影响[J].中国沙漠,2007,27(3):385-390.
[25] 张学霞,朱清科,吴根梅,等.数码照相法估算植被盖度[J].北京林业大学学报,2008,30(1):164-169.
[26] 章文波,刘宝元,吴敬东.小区植被覆盖度动态快速测量方法研究[J].水土保持通报,2001,21(6):60-63.
[27] 高志海,李增元,魏怀东,等.干旱地区植被指数(VI)的适宜性研究[J].中国沙漠,2006,26(2):243-248.
[28] 李登科,郭铌.陕西MODIS/NDVI的区域分布和季节变化[J].中国沙漠,2008,28(1):108-112.
[29] 郭铌,韩天虎,王静,等.玛曲退牧还草工程生态效果的遥感监测[J].中国沙漠,2010,30(1):154-160.
[30] 席海洋,冯起,司建华,等.黑河下游绿洲NDVI对地下水位变化的响应研究[J].中国沙漠,2013,33(2):574-582.
[31] 王焕炯,范闻捷,崔要奎,等.草地退化的高光谱遥感监测方法[J].光谱学与光谱分析,2010,30(10):2734-2738.
[32] 戴小华,余世孝.遥感技术支持下的植被生产力与生物量研究进展[J].生态学杂志,2004,23(4):92-98.
[33] 王鹏龙,张建明,张春梅,等.腾格里沙漠典型植被含水率与地物光谱的关系分析[J].中国沙漠,2013,33(3):737-742.
[34] 曹巍,邵全琴,喻小勇,等.内蒙古不同利用方式温性草原植被光谱特征分析[J].草业科学,2013,21(2):243-252.
[35] 赵金,陈曦,古丽·加帕尔,等.塔里木河荒漠植被光谱可分性模型[J].中国沙漠,2009,29(2):270-278.
[36] 林文鹏,李厚增,黄敬峰,等.上海市植被光谱反射特征分析[J].光谱学与光谱分析,2010,30(11):3111-3114.
[37] 黄德青,于兰,张耀生,等.祁连山北坡5类天然草地地上部数量特征及其与环境因子的关系[J].西北农业学报,2011,20(6):174-180.
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