首页 » 文章 » 文章详细信息
Mathematical Problems in Engineering Volume 2017 ,2017-06-22
An Integrated Field and Hyperspectral Remote Sensing Method for the Estimation of Pigments Content of Stipa Purpurea in Shenzha, Tibet
Research Article
Bo Kong 1 Bing He 1 Huan Yu 2 Yu Liu 2
Show affiliations
DOI:10.1155/2017/4787054
Received 2016-11-28, accepted for publication 2017-05-07, Published 2017-05-07
PDF
摘要

Stipa purpurea is the representative type of alpine grassland in Tibet and the surviving and development material for herdsmen. This paper takes Shenzha County as the research area. Based on the analysis of typical hyperspectral variables sensitive to chlorophyll content of Stipa purpurea, 10 spectral variables with significant correlation with chlorophyll were extracted. The estimation model of chlorophyll was established. The photosynthetic pigment contents in the Shenzha area were calculated by using HJ-1A remote sensing images. The results show that (1) there are significant correlations between chlorophyll content and spectral variables; in particular, the coefficient of Chlb in Stipa purpurea with RVI is the largest (0.728); (2) 10 variables are correlated with chlorophyll, and the order of correlation is Chlb > Chla > Chls; (3) for the estimation of Chla, the EVI is the best variable. RVI, NDVI, and VI2 are suitable for Chlb; RVI and NDVI are also suitable for the estimation of Chls; (4) the mean estimated content of Chla in Stipa bungeana is about 4.88 times that of Chlb, while Cars is slightly more than Chlb; (5) the distribution of Chla is opposite to Chlb and Chls content in water area.

授权许可

Copyright © 2017 Bo Kong et al. 2017
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

图表

The study area and schematic plot of sample point.

Field experiment.

Comparison of different coverage of Stipa purpurea spectral reflectance curve.

Results of the optimal estimation model of the photosynthetic pigment of Stipa purpurea.

The map of photosynthetic pigment content.

通讯作者

Bing He.Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China, cas.cn.hebing@imde.ac.cn

推荐引用方式

Bo Kong,Bing He,Huan Yu,Yu Liu. An Integrated Field and Hyperspectral Remote Sensing Method for the Estimation of Pigments Content of Stipa Purpurea in Shenzha, Tibet. Mathematical Problems in Engineering ,Vol.2017(2017)

您觉得这篇文章对您有帮助吗?
分享和收藏
0

是否收藏?

参考文献
[1] G. A. Blackburn. (1998). Quantifying chlorophylls and carotenoids at leaf and canopy scales: An evaluation of some hyperspectral approaches. Remote Sensing of Environment.66(3):273-285. DOI: 10.1007/s12686-016-0519-x.
[2] W. M. Yong, X. M. Wang. (2016). Progress on grassland chlorophyll content estimation by hyperspectral analysis. Progress in Geography.35(1):25-34. DOI: 10.1007/s12686-016-0519-x.
[3] M. Gupta, P. K. Srivastava, S. Mukherjee, G. Sandhya Kiran. et al.(2014). Chlorophyll retrieval using ground based hyperspectral data from a tropical area of india using regression algorithms. Remote Sensing Applications in Environmental Research.4:177-194. DOI: 10.1007/s12686-016-0519-x.
[4] A. Bannari, K. S. Khurshid, K. Staenz, J. W. Schwarz. et al.(2007). A comparison of hyperspectral chlorophyll indices for wheat crop chlorophyll content estimation using laboratory reflectance measurements. IEEE Transactions on Geoscience and Remote Sensing.45(10):3063-3074. DOI: 10.1007/s12686-016-0519-x.
[5] M. J. Duan, Q. Z. Gao, Y. F. Wan, Y. Li. et al.(2010). Effect of grazing on community characteristics and species diversity of stipa purpurea alpine grassland in northern tibet. Acta Ecologica Sinica.30(14):3892-3900. DOI: 10.1007/s12686-016-0519-x.
[6] D. A. Sims, J. A. Gamon. (2002). Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment.81(2-3):337-354. DOI: 10.1007/s12686-016-0519-x.
[7] A. A. Gitelson, G. P. Keydan, M. N. Merzlyak. (2006). Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research Letters.33(11). DOI: 10.1007/s12686-016-0519-x.
[8] X. M. Zhou, Q. J. Wang, Y. Q. Zhang, X. Q. Zhao. et al.(1987). Quantitative analysis of vegetation succession in alpine meadow under different grazing intensity. Journal of Plant Ecology and Botany.11(4):276-285. DOI: 10.1007/s12686-016-0519-x.
[9] M. J. Gallardo, J. P. Staforelli, P. Meza, I. Bordeu. et al.(2014). Characterization of Chromobacterium violaceum pigment through a hyperspectral imaging system. AMB Express.4(4):2-9. DOI: 10.1007/s12686-016-0519-x.
[10] A. C. Madeira, A. Mendonça, M. E. Ferreira. (2000). Relationship between spectroradiometric and chlorophyll measurements in green beans. Communications in Soil Science and Plant Analysis.31(5-6):631-643. DOI: 10.1007/s12686-016-0519-x.
[11] A. A. Gitelson, C. Buschmann, H. K. Lichtenthaler. (1999). The chlorophyll fluorescence ratio F735F700 as an accurate measure of the chlorophyll content in plants. Remote Sensing of Environment.69(3):296-302. DOI: 10.1007/s12686-016-0519-x.
[12] P. Chen, D. Haboudane, N. Tremblay, J. Wang. et al.(2010). New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat. Remote Sensing of Environment.114(9):1987-1997. DOI: 10.1007/s12686-016-0519-x.
[13] H. A. Jin, D. W. Liu, K. S. Song, Z. M. Wang. et al.(2007). Comparing the performance of broad-band and narrow-band vegetation indices for estimation of soybean LAI. System Sciences and Comprehensive Studies in Agriculture.23(4):503-508. DOI: 10.1007/s12686-016-0519-x.
[14] J. Delegido, L. Alonso, G. González, J. Moreno. et al.(2010). Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC). International Journal of Applied Earth Observation and Geoinformation.12(3):165-174. DOI: 10.1007/s12686-016-0519-x.
[15] G. L. Jin, J. Z. Zhu, H. L. Liu, S. M. Tang. et al.(2011). Study on physiology/ecology adaptation of main plant in degraded seriphidiumtransiliense desert rangeland. ActaAgrectirSinica.19(1):26-30. DOI: 10.1007/s12686-016-0519-x.
[16] J. Dash, P. J. Curran. (2007). Evaluation of the MERIS terrestrial chlorophyll index (MTCI). Advances in Space Research.39(1):100-104. DOI: 10.1007/s12686-016-0519-x.
[17] D. Haboudane, J. R. Miller, N. Tremblay, P. J. Zarco-Tejada. et al.(2002). Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment.81(2-3):416-426. DOI: 10.1007/s12686-016-0519-x.
[18] D. Filella, J. Peñuelas. (1994). The red edge position and shape as indicators of plant chlorophyll content, biomass and hydric status. International Journal of Remote Sensing.15(7):1459-1470. DOI: 10.1007/s12686-016-0519-x.
[19] F. Flores-de-Santiago, J. M. Kovacs, F. Flores-Verdugo. (2013). The influence of seasonality in estimating mangrove leaf chlorophyll-a content from hyperspectral data. Wetlands Ecology and Management.21(3):193-207. DOI: 10.1007/s12686-016-0519-x.
[20] P. P. Yue, X. F. Lu, R. R. Ye, C. X. Zhang. et al.(2011). Distribution of Stipa purpurea steppe in the northeastern qinghai-xizang plateau (China). Russian Journal of Ecology.42(1):50-56. DOI: 10.1007/s12686-016-0519-x.
[21] D. N. H. Horler, J. Barber, A. R. Barringer. (1980). Effects of heavy metals on the absorbance and reflectance spectra of plants. International Journal of Remote Sensing.1(2):121-136. DOI: 10.1007/s12686-016-0519-x.
[22] D. Lu, Y. Zhao, R. Han, L. Wang. et al.(2016). The complete chloroplast genome sequence of the Purple Feathergrass Stipa purpurea (Poales: Poaceae). Conservation Genetics Resources.8(2):101-104. DOI: 10.1007/s12686-016-0519-x.
[23] A. D. Richardson, S. P. Duigan, G. P. Berlyn. (2002). An evaluation of noninvasive methods to estimate foliar chlorophyll content. New Phytologist.153(1):185-194. DOI: 10.1007/s12686-016-0519-x.
[24] G. Le Maire, C. François, E. Dufrêne. (2004). Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment.89(1):1-28. DOI: 10.1007/s12686-016-0519-x.
[25] J. G. P. W. Clevers, L. Kooistra. Using hyperspectral remote sensing data for retrieving total canopy chlorophyll and nitrogen content. . DOI: 10.1007/s12686-016-0519-x.
[26] C. J. Nichol, J. Grace. (2010). Determination of leaf pigment content in Calluna vulgaris shoots from spectral reflectance. International Journal of Remote Sensing.31(20):5409-5422. DOI: 10.1007/s12686-016-0519-x.
文献评价指标
浏览 27次
下载全文 4次
评分次数 0次
用户评分 0.0分
分享 0次