Volume 8, Issue 1, March 2019, Page: 6-11
The Characteristic Analysis of Canopy Spectrum and Moisture Content of 10 Typical Arid Desert Plants
Wei Huaidong, Collage of Geography and Environmental Science, Northwest Normal University, Lanzhou, China; The State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating of Gansu Desert Control Research Institute, Lanzhou, China
Li Jingjing, The State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating of Gansu Desert Control Research Institute, Lanzhou, China
Chen Fang, The State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating of Gansu Desert Control Research Institute, Lanzhou, China
Zhang Bo, Collage of Geography and Environmental Science, Northwest Normal University, Lanzhou, China
Zhou Lanping, The State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating of Gansu Desert Control Research Institute, Lanzhou, China
Li Ya, The State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating of Gansu Desert Control Research Institute, Lanzhou, China
Yang Xuemei, The State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating of Gansu Desert Control Research Institute, Lanzhou, China
Received: Jan. 7, 2019;       Published: Mar. 8, 2019
DOI: 10.11648/j.jenr.20190801.12      View  238      Downloads  33
Abstract
Plant water is a main factor to affect physiological and biochemical indexes of plants like photosynthesis, respiration, and biomass and so on. The investigation of plant water content is an important part of vegetation research. The study of the relationship between water content and canopy spectrum of typical desert plants by hyper spectral has great significance for remote sensing monitoring of vegetation in arid desert areas. The canopy spectral curves of 10 typical desert plants were determined by ASD portable ground spectrometer in this study. The correlation coefficient method and vegetation index method were used to analyze the spectral characteristics of different desert plants and their relationship with canopy moisture content. The results show: 1) the reflectance curve of desert plants has the general characteristics of green plants in the visible-near-infrared band, with obvious "green peak" characteristics and "red edge effect". 2) In the three wavebands of 954-973 nm, 1184-1198 nm and 1440-1462 nm, desert plants have obvious water absorption valleys. Among them, the correlation coefficient between spectral reflectance and water content in the 1440-1462 nm band is greater than 0.8, and they have strong linear correlation. 3) WBI (Water Band Index), NDWI (Normalized Difference Water Index), NDII (Normalized Difference Infrared Index), MSI (Moisture Stress Index) were significantly correlated with plant water content (P<0.05), and the measured values of canopy moisture content index and vegetation moisture have high consistency and can reflect the change of moisture content of desert vegetation.
Keywords
Spectral Characteristics, Plant Water Content, Correlation Coefficient, Canopy Moisture Content Index, Desert Plant, Minqin
To cite this article
Wei Huaidong, Li Jingjing, Chen Fang, Zhang Bo, Zhou Lanping, Li Ya, Yang Xuemei, The Characteristic Analysis of Canopy Spectrum and Moisture Content of 10 Typical Arid Desert Plants, Journal of Energy and Natural Resources. Vol. 8, No. 1, 2019, pp. 6-11. doi: 10.11648/j.jenr.20190801.12
Reference
[1]
Zhou L P, Wei H D, Ding F, Chen F, Hu X K. Analysis on spectral reflectance characteristics of desert plants in Minqin Basin of Shiyang River. Journal of Arid Land Resources and Environment, 2013, 27 (3): 121-125. (in Chinese)
[2]
Tong Q X, Zhang B, Zheng L F. Hyperspectral Remote Sensing: Principle, Technology and Application. Beijing: Higher Education Press, 2006. (in Chinese)
[3]
Pu R L, Gong P. Hyperspectral Remote Sensing and Its Application. Beijing: Higher Education Press, 2000. (in Chinese)
[4]
Zhao Z, Li X, Yin Y B, Zhou S B. Analysis of spectral features based on water content of desert vegetation. Spectroscopy and Spectral Analysis, 2010, 30 (9): 2500-2503. (in Chinese)
[5]
Zhao Z. Analysis of Spectral Features Based on Water Content of Xinjiang Desert Plants. Master Thesis. Urumqi: Xinjiang Agricultural University, 2011. (in Chinese)
[6]
Wang P L, Zhang J M, Zhang C M, Xu M S, Wang L. The relationships between spectral features and water content of the dominat plant species in the Tengger Desert. Journal of Desert Research, 2013, 33 (3): 737-742. (in Chinese)
[7]
Xu X Y, Ding G D, Sun B P, Zhao M, Jin H X. Ecological water requirement of major sand shifting control forests in Minqin Oasis of lower reaches of inland river. Journal of Soil and Water Conservation, 2007, 21 (3): 144-148. (in Chinese)
[8]
Xia X W, Jin G L, An S Z, Fan Y M, Liang N. Spectral characteristics of typical plants in Seriphidium transiliense desert grassland under enclosure. Pratacultural Science, 2015, 32 (6): 870-876. (in Chinese)
[9]
Wan Y Q, Yan Y Z, Zhang F L. Analyses to spectral character of the vegetation along Yanhe River. Remote Sensing for Land & Resources, 2001, 49 (3): 15-20. (in Chinese)
[10]
Fuan T, William P. Derivative analysis of hyperspectral data. Remote Sensing of Environment, 1998, 66 (1): 41-51.
[11]
Wang Q, Yi Q X, Bao A M, Zhao J. Discussion on hyperspectral index for the estimation of cotton canopy water content. Spectroscopy and Spectral Analysis, 2013, 33 (2): 507-512. 9. (in Chinese)
[12]
Wei X H, Jin G L, Fan Y M, An S Z, Xia X W. Species analysis and identification of spectral characteristics on Seriphidium transiliense desert grassland. Pratacultural Science, 2016, 33 (10): 1924-1932. (in Chinese)
[13]
Zhang B, Niu T, Fang S F, Wu D Y. Research on the spectral characteristic of typical vegetation in desert-oasis crisscross zone. Spectroscopy and Spectral Analysis, 2016, 36 (4): 1104-1108. (in Chinese)
[14]
Lin C, Gong Z N, Zhao Y J. Hyperspectral estimation models for plant community water content at both leaf and canopy levels in Wild Duck Lake wetland. Acta Ecologica Sinica, 2011, 31 (22): 6645-6658. (in Chinese)
[15]
Ding J L, Zhang F, Tashpolat T. Research on the spectral character of vegetation in arid area. Journal of Arid Land Resources and Environment, 2008, 22 (11): 160-165. (in Chinese)
[16]
Cheng Y L, Wang Z J, Hong J M. Analysis of spectral characteristics on different coverage of Hemarthria altissima in Yeyahu Wetland. Journal of Capital Normal University: Natural Sciences Edition, 2013, 34 (6): 16-21. (in Chinese)
[17]
Li Z Z, Zheng X, Niu D K, Guo X M, Xie B Y, Zhang X L. The study on hyperspectral characteristics of main community types in mountain meadow. Pratacultural Science, 2016, 33 (8): 1492-1501. (in Chinese)
[18]
Duan R L, Liu Y X, Zhang S W, Duan L M, Tian J. Matching of Spectral data of typical vegetation on dune in the Horqin Sanddy Land. Arid Zone Research, 2014, 31 (4): 750-755. (in Chinese)
[19]
Feng X W, Chen X, Bao A M, Sun L, Wang D W, Ma Y Q. Analysis on the cotton physiological change and its hyperspectral response under the water stress conditions. Arid Land Geography, 2004, 27 (2): 250-255. (in Chinese)
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