激光与光电子学进展, 2018, 55 (7): 072801, 网络出版: 2018-07-20   

基于宽波段与窄波段综合光谱指数的土壤有机质遥感反演 下载: 735次

Remote Sensing Inversion of Soil Organic Matter Based on Broad Band and Narrow Band Comprehensive Spectral Index
作者单位
1 新疆大学资源与环境科学学院绿洲生态重点实验室, 新疆 乌鲁木齐 830046
2 北京联合大学应用文理学院城市科学系, 北京 100083
引用该论文

郑曼迪, 熊黑钢, 乔娟峰, 刘靖朝. 基于宽波段与窄波段综合光谱指数的土壤有机质遥感反演[J]. 激光与光电子学进展, 2018, 55(7): 072801.

Zheng Mandi, Xiong Heigang, Qiao Juanfeng, Liu Jingchao. Remote Sensing Inversion of Soil Organic Matter Based on Broad Band and Narrow Band Comprehensive Spectral Index[J]. Laser & Optoelectronics Progress, 2018, 55(7): 072801.

参考文献

[1] 方少文, 杨梅花, 赵小敏, 等. 红壤区土壤有机质光谱特征与定量估算——以江西省吉安县为例[J]. 土壤学报, 2014, 51(5): 1003-1010.

    Fang S W, Yang M H, Zhao X M, et al. Spectral characteristics and quantitative estimation of SOM in red soil typical of Ji’an Country, Jiangxi Province[J]. Acta Pedologica Sinica, 2014, 51(5): 1003-1010.

[2] 吴一全, 周杨, 龙云淋. 基于自适应参数支持向量机的高光谱遥感图像小目标检测[J]. 光学学报, 2015, 35(9): 0928001.

    Wu Y Q, Zhou Y, Long Y L. Small target detection in hyperspectral remote sensing image based on adaptive parameter SVM[J]. Acta Optica Sinica, 2015, 35(9): 0928001.

[3] Pisek J, Chen J M. Comparison and validation of MODIS and VEGETATION global LAI products over four BigFoot sites in North America[J]. Remote Sensing of Environment, 2007, 109(1): 81-94.

[4] Sims D A, Gamon J A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages[J]. Remote Sensing of Environment, 2002, 81(2): 337-354.

[5] 张娟娟, 田永超, 姚霞, 等. 同时估测土壤全氮、有机质和速效氮含量的光谱指数研究[J]. 土壤学报, 2012, 49(1): 50-59.

    Zhang J J, Tian Y C, Yao X, et al. The spectral index for estimating soil OM, TN and AN content simultaneously using near-infrared spectroscopy[J]. Acta Pedologica Sinica, 2012, 49(1): 50-59.

[6] 王飞, 丁建丽, 魏阳, 等. 基于Landsat系列数据的盐分指数和植被指数对土壤盐度变异性的响应分析—以新疆天山南北典型绿洲为例[J]. 生态学报, 2017, 37(15): 5007-5022.

    Wang F, Ding J L, Wei Y, et al. Sensitivity analysis of soil salinity and vegetation indices to detect soil salinity variation by using Landsat series images: applications in different oases in Xinjiang, China[J]. Acta Ecologica Sinica, 2017, 37(15): 5007-5022.

[7] 张林静, 岳明, 张远东, 等. 新疆阜康绿洲荒漠过渡带植物群落物种多样性特征[J]. 地理科学, 2003, 23(3): 329-334.

    Zhang L J, Yue M, Zhang Y D, et al. Characteristics of plant community species diversity of oasis desert ecotone in Fukang, Xinjiang[J]. Scientia Geographica Sinica, 2003, 23(3): 329-334.

[8] 姚峰, 古丽·加帕尔, 包安明, 等. 基于遥感技术的干旱荒漠区露天煤矿植被群落受损评估[J]. 中国环境科学, 2013, 33(4): 707-713.

    Yao F, Guli·Jiapaer, Bao A M, et al. Damage assessment of the vegetable types based on remote sensing in the open coalmine of arid desert area[J]. China Environmental Science, 2013, 33(4): 707-713.

[9] 赵芳, 彭彦昆. 区间偏最小二乘法结合拉曼光谱测定猪肉皮下脂肪的碘值[J]. 中国激光, 2017, 44(11): 1111001.

    Zhao F, Peng Y K. Measurement of iodine value of pork’s subcutaneous adipose tissue by interval partial least square and Raman spectroscopy[J]. Chinese Journal of Lasers, 2017, 44(11): 1111001.

[10] Fabio C, Angelo P, Federico S, et al. Evaluation of the potential of the current and forthcoming multispectral and hyperspectral imagers to estimate soil texture and organic carbon[J]. Remote Sensing of Environment, 2016, 179: 54-65.

[11] 解宪丽, 孙波, 郝红涛. 土壤可见光-近红外反射光谱与重金属含量之间的相关性[J]. 土壤学报, 2007, 44(6): 982-993.

    Xie X L, Sun B, Hao H T. Relationship between visible-near infrared reflectance spectroscopy and heavy metal of soil concentration[J]. Acta Pedologica Sinica, 2007, 44(6): 982-993.

[12] 陈祯. 不同土壤含水量、体积质量及光谱反射率的关系模型[J]. 农业工程学报, 2012, 28(4): 76-81.

    Chen Z. Relationship model among water content, bulk density and reflectivity of different soil[J]. Transactions of the Chinese Society of Agricultural Engineering, 2012, 28(4): 76-81.

[13] 李萍. 黄河三角洲土壤含水量状况的高光谱估测与遥感反演[D]. 泰安: 山东农业大学, 2016: 26.

    Li P. Hyperspectral estimation and remote sensing retrieval of soil water regime in the Yellow River Delta[D]. Taian: Shandong Agricultural University, 2016: 26.

[14] 徐涵秋, 唐菲. 新一代Landsat系列卫星: Landsat 8遥感影像新增特征及其生态环境意义[J]. 生态学报, 2013, 33(11): 3249-3257.

    Xu H Q, Tang F. Analysis of new characteristics of the first Landsat 8 image and their eco-environmental significance[J]. Acta Ecologica Sinica, 2013, 33(11): 3249-3257.

[15] Khan N M, Rastoskuev V, Sato Y, et al. Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators[J]. Agricultural Water Management, 2005, 77: 96-109.

[16] Inakwu O A Odeh, Onus A. Spatial analysis of soil salinity and soil structural stability in a semiarid region of New South Wales, Australia[J]. Environmental Management, 2008, 42(2): 65-78.

[17] 陈红艳, 赵庚星, 陈敬春, 等. 基于改进植被指数的黄河口区盐渍土盐分遥感反演[J]. 农业工程学报, 2015, 31(5): 107-114.

    Chen H Y, Zhao G X, Chen J C, et al. Remote sensing inversion of saline soil salinity based on modified vegetation index in estuary area of Yellow River[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(5): 107-114.

[18] Baret F, Guyot G. Potentials and limits of vegetation indices for LAI and APAR assessment[J]. Remote Sensing of Environment, 1991, 35(2/3): 161-173.

[19] Schlerf M, Atzberger C, Hill J. Remote sensing of forest biophysical variables using HyMap imaging spectrometer data[J]. Remote Sensing of Environment, 2005, 95(2): 177-194.

[20] Roujean J L, Breon F M. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements[J]. Remote Sensing of Environment, 1995, 51(3): 375-384.

[21] 蔡亮红, 丁建丽. 基于高光谱多尺度分解的土壤含水量反演[J]. 激光与光电子学进展, 2018, 55(1): 013001.

    Cai L H, Ding J L. Inversion of soil moisture content based on hyperspectral multi-scale decomposition[J]. Laser & Optoelectronics Progress, 2018, 55(1): 013001.

[22] Viscarra R V, McGlyn R N, McBratney A B. Determining the composition of mineral-organic mixes using UV-vis-NIR diffuse reflectance spectroscopy[J]. Geoderma, 2006, 137(1/2): 70-82.

[23] 姜雪芹, 叶勤, 林怡, 等. 基于谐波分析和高光谱遥感的土壤含水量反演研究[J]. 光学学报, 2017, 37(10): 1028001.

    Jiang X Q, Ye Q, Lin Y, et al. Inverting study on soil water content based on harmonic analysis and hyperspectral remote sensing[J]. Acta Optica Sinica, 2017, 37(10): 1028001.

[24] 李相, 丁建丽. 基于实测高光谱指数与HSI影像指数的土壤含水量监测[J]. 农业工程学报, 2015, 31(19): 68-75.

    Li X, Ding J L. Soil moisture monitoring based on measured hyperspectral index and HSI image index[J]. Transactions of the Chinese Society of Agricultural Engineering, 2015, 31(19): 68-75.

[25] 梁雪, 吉海彦, 王鹏新, 等. 用MSC-ANN方法建立冬小麦叶片叶绿素与反射光谱的定量分析模型研究[J]. 光谱学与光谱分析, 2010, 30(1): 188-191.

    Liang X, Ji H Y, Wang P X, et al. Study on building quantitative analysis model for chlorophyll in winter wheat with reflective spectrum using MSC-ANN algorithm[J]. Spectroscopy and Spectral Analysis, 2010, 30(1): 188-191.

[26] 唐启义. DPS数据处理系统[M]. 北京: 科学出版社, 2010: 2.

    Tang Q Y. DPS data processing system[M]. Beijing: Science Press, 2010: 2.

[27] Masoud A A, Koikek K. Arid land salinization detected by remotely sensed land cover changes: a case study in the Siwa region, NW Egypt[J]. Journal of Arid Environments, 2006, 66(1): 151-167.

[28] 董志玲. 干旱荒漠区人工梭梭林土壤碳氮储量分布规律及影响因子研究[D]. 北京: 中国林业科学研究院, 2014: 36.

    Dong Z L. The study of artificial Haloxylon forest distribution of soil carbon and nitrogen storage and its influence factors in arid desert area[D]. Beijing: Chinese Academy of Forestry Sciences, 2014: 36.

郑曼迪, 熊黑钢, 乔娟峰, 刘靖朝. 基于宽波段与窄波段综合光谱指数的土壤有机质遥感反演[J]. 激光与光电子学进展, 2018, 55(7): 072801. Zheng Mandi, Xiong Heigang, Qiao Juanfeng, Liu Jingchao. Remote Sensing Inversion of Soil Organic Matter Based on Broad Band and Narrow Band Comprehensive Spectral Index[J]. Laser & Optoelectronics Progress, 2018, 55(7): 072801.

本文已被 1 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!