|
|
|
|
|
|
Hyperspectral Features of Typical Plants in Different Mining Disturbance Zones Caused by Coal Mining Collapse in Semi-Arid Areas |
WANG Li1,2, LEI Shao-gang1*, BIAN Zheng-fu1, WANG Kai2, PENG Jian2,3, WU Jian2 |
1. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
2. Geography Information and Tourism College, Chuzhou University, Chuzhou 239000, China
3. Tourism College, Hunan Normal University, Changsha 410081, China |
|
|
Abstract The use of hyperspectral technology to invert and monitor vegetation is based on the identification of its spectral characteristics. The spectral reflectance and the SPAD values of leaves of typical plants, collected in different mining disturbance zones of Coal mining subsidence areas in semi-arid regiens, were simultaneous measured by Field Spec 3 spectrometer and the SPAD-502 chlorophyll meter to explore the spectral characteristics of the plants in the same zone with the SPAD values changing and the spectral differences of typical plants in different mining disturbance zones when the SPAD values was in the same interval. Furthermore, the correlations between SPAD values of leaves of typical plants and the spectral index were analyzed by using Matlab software. The results showed that the spectral characteristics of the same plant species in different mining disturbance zones were distinct with the SPAD values changing, and the spectral curves of different sample zones were clearly distinguished in visible band. In visible band, the green peak of spectral curves of Cleistogenes squarrosa, Artemisia ordosica, Caragana microphylla and Populus tremula in the non-mining zone were absent when the SPAD values was very low, and it appeared with the increase of SPAD value, but the position was red-shifted, when the SPAD value was above 30, the spectral features of the blue valley, green peak, red valley and red edge were obvious, and the higher the SPAD value of leaves of Chinese pine, the lower the spectral reflectance, while no rule was observed in the other zones. In addition, the spectral reflectance of samples with lower SPAD values of Cleistogenes squarrosa, Artemisia ordosica, Chinese pine and Caragana microphylla in the different mining disturbance zones was significantly higher than that of the samples with higher SPAD values from 400 to 700 nm band in general, but the trend of leaves of Populus tremula was just the opposite. The reflectance of the higher and lower groups of SPAD values of Cleistogenes squarrosa in the drawing zone, Artemisia ordosica and Caragana microphylla in the non-mining zone, and Chinese pine and Populus tremula in the compression zone were similar. Compared with the non-mining zone, the differences between the reflectance of the higher and lower groups of SPAD values of the Cleistogenes squarrosa, Artemisia ordosica, and Caragana microphylla in the mining disturbance zones significantly reduced. Moreover, the correlation between the SPAD value and the spectral index of the samples in the mining disturbance zones was enhanced in some bands than that in non-mining zone. The maximum correlation coefficient values between the SPAD value and the spectral index of Artemisia ordosica, Chinese pine, Caragana microphylla and Populus tremula had become lager in neutral zone than that in the non-mining zone, while that of Cleistogenes squarrosa was just opposite. At the same time, the maximum correlation coefficient between SPAD value and NDVI in non-mining zone was higher than that of DI, and the band combinations were mostly in the near infrared, but in the other zones, the band combinations were mostly in visible band. The results of this study provided theoretical support for identifying the differences in the spectral characteristics of typical plants in different mining disturbance zones, further monitoring the health status of plants and accurately controlling the ecological environment in mining area.
|
Received: 2018-06-23
Accepted: 2018-09-06
|
|
Corresponding Authors:
LEI Shao-gang
E-mail: lsgang@126.com
|
|
[1] Dong S, Samsonov S, Yin H, et al. Environmental Earth Sciences, 2015, 73(9): 5523.
[2] Marschalko M, Bednárik M, Yilmaz I, et al. Bulletin of Engineering Geology & the Environment, 2012, 71(1): 105.
[3] LEI Shao-gang, BIAN Zheng-fu(雷少刚, 卞正富). Acta Ecologica Sinica(生态学报), 2014, 34(11): 2837.
[4] QIE Chen-long, BIAN Zheng-fu, YANG De-jun, et al(郄晨龙,卞正富,杨德军,等). Journal of China Coal Society(煤炭学报), 2015, 40(6): 1448.
[5] TAI Xiao-li, HU Zhen-qi, CHEN Chao(台晓丽,胡振琪,陈 超). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2016, 32(15): 225.
[6] Sun Q, Zhang J X, Zhang Q, et al. Energies, 2017, 10(6): 786.
[7] FAN Li-min, MA Xiong-de, LI Yong-hong, et al(范立民,马雄德,李永红,等). Journal of China Coal Society(煤炭学报), 2017, 42(2): 282.
[8] Fan G, Zhang D. Mine Water & the Environment, 2015, 34(1): 95.
[9] Bian Z F, Miao X X, Lei S G, et al. Science, 2012, 337(609S): 703
[10] Hu Z, Fu Y, Xiao W, et al. International Journal of Surface Mining, Rectamation and Environment, 2015, 29(4): 15.
[11] PENG Jian, XU Fei-xiong, DENG Kai, et al(彭 建,徐飞雄,邓 凯,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2018, 38(6): 1839. |
[1] |
ZHOU Qi1, 2, WANG Jian-jun1, 2*, HUO Zhong-yang1, 2*, LIU Chang1, 2, WANG Wei-ling1, 2, DING Lin3. UAV Multi-Spectral Remote Sensing Estimation of Wheat Canopy SPAD Value in Different Growth Periods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1912-1920. |
[2] |
Nigela Tuerxun1, Sulei Naibi2, GAO Jian3, SHEN Jiang-long1, ZHENG Jiang-hua1*, YU Dan-lin4. Chlorophyll Content Estimation of Jujube Leaves Based on GWLS-SVR Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(06): 1730-1736. |
[3] |
ZHANG Hao-dan1,SUN Xiao-lin1, 2*,WANG Xiao-qing1,WANG Hui-li3. Analyzing Errors due to Measurement Positions and Sampling Locations for In Situ Measurements of Soil Organic Matter Using Vis-NIR Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(11): 3499-3507. |
[4] |
FENG Rui1,2, WU Jin-wen1,2, WANG Hong-bo1,2, HU Wei3, ZHANG Yu-shu1,2, YU Wen-ying1,2, JI Rui-peng1,2, LIN Yi4. Influence of Drought Stress on Maize in the Seedling Stage on Spectral Characteristics at the Critical Developmental Stage[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(07): 2222-2228. |
[5] |
LEI Xiang-xiang1, ZHAO Jing1, LIU Hou-cheng2, ZHANG Ji-ye2, LIANG Wen-yue1, TIAN Jia-ling2, LONG Yong-bing1*. Inversion of Chlorophyll Content and SPAD Value of Vegetable Leaves Based on PROSPECT Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2019, 39(10): 3256-3260. |
[6] |
LIU Ming1, ZHAO Jing2*, WU Tai-xia4, ZHANG Li-fu4, TANG Hong-ying5, LU Xiao-zuo2, LI Gang3. Separation of Tongue Coat and Tongue Proper Based on Optical Spectrum Dissimilarity Index Using Double-Wavelength Ratio[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1798-1803. |
[7] |
PENG Jian1, 2, XU Fei-xiong1* , DENG Kai2, WU Jian2, LI Wei-tao2, WANG Ni2, LIU Min-shi2. Spectral Differences of Tree Leaves at Different Chlorophyll Relative Content in Langya Mountain[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1839-1849. |
[8] |
ZHANG Jian1, 2, MENG Jin1, 2, ZHAO Bi-quan1, 2, ZHANG Dong-yan3, XIE Jing4*. Research on the Chlorophyll Content (SPAD) Distribution Based on the Consumer-Grade Modified Near-Infrared Camera[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(03): 737-744. |
[9] |
ZHANG Jian1, LI Yong1, XIE Jing2*, LI Zong-nan1. Research on Optimal Near-Infrared Band Selection of Chlorophyll (SPAD) 3D Distribution about Rice Plant[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(12): 3749-3757. |
[10] |
ZHAO Heng-qian1, ZHAO Xue-sheng1*, CEN Yi2, YANG Hang2 . Research on the Impact of Absorption Feature Extraction on Spectral Difference Between Similar Minerals [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(03): 869-874. |
[11] |
WANG Xiao-qiao1,2,4, WANG Fang1,3, LIAO Gui-ping1,3*, GUAN Chun-yun1,2 . Multifractal Analysis of Rapeseed Spectrum for Chlorophyll Diagnosis Modeling [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(11): 3657-3663. |
[12] |
CEN Yi1, 2, ZHANG Gen-zhong1, 3, ZHANG Li-fu1, LU Xu-hui4, ZHANG Fei-zhou5* . Spectral Uncertainty of Terrestrial Objects and the Applicability of Spectral Angle Mapper Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(10): 2841-2845. |
[13] |
WU Jian, CHEN Tai-sheng, PAN Li-xin* . Spectrum Variance Analysis of Tree Leaves under the Condition of Different Leaf water Content[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35(07): 1961-1966. |
[14] |
ZHANG Bing1, SHA Jian-jun1,2, WANG Xiang-wei1, GAO Lian-ru1 . Impact Analysis of Atmospheric State for Target Detection in Hyperspectral Radiance Image [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(08): 2043-2049. |
[15] |
GAO Fei1, XIAO Jing1, GU Yun-hong1*, JIAO Zhen1, JIN Qing-sheng2 . Study on Predicting Protein Content of Wheat Seeds by Using Wheat Leaves SPAD Value[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2012, 32(05): 1350-1354. |
|
|
|
|