Feature extraction and analysis of reclaimed vegetation in ecological restoration area of abandoned mines based on hyperspectral remote sensing images

doi:10.1007/s40333-024-0109-9

Journal of Arid Land

2024, Vol. 16

Issue (10): 1409-1425 DOI: 10.1007/s40333-024-0109-9 CSTR: 32276.14.s40333-024-0109-9

Research article

Feature extraction and analysis of reclaimed vegetation in ecological restoration area of abandoned mines based on hyperspectral remote sensing images

MAO Zhengjun¹^,^*(

), WANG Munan¹, CHU Jiwei¹, SUN Jiewen², LIANG Wei², YU Haiyong¹

¹College of Geology and Environment, Xi'an University of Science and Technology, Xi'an 710054, China
²Ningxia Hui Autonomous Region Remote Sensing Survey Institute, Yinchuan 750021, China

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Abstract

The vegetation growth status largely represents the ecosystem function and environmental quality. Hyperspectral remote sensing data can effectively eliminate the effects of surface spectral reflectance and atmospheric scattering and directly reflect the vegetation parameter information. In this study, the abandoned mining area in the Helan Mountains, China was taken as the study area. Based on hyperspectral remote sensing images of Zhuhai No. 1 hyperspectral satellite, we used the pixel dichotomy model, which was constructed using the normalized difference vegetation index (NDVI), to estimate the vegetation coverage of the study area, and evaluated the vegetation growth status by five vegetation indices (NDVI, ratio vegetation index (RVI), photochemical vegetation index (PVI), red-green ratio index (RGI), and anthocyanin reflectance index 1 (ARI1)). According to the results, the reclaimed vegetation growth status in the study area can be divided into four levels (unhealthy, low healthy, healthy, and very healthy). The overall vegetation growth status in the study area was generally at low healthy level, indicating that the vegetation growth status in the study area was not good due to short-time period restoration and harsh damaged environment such as high and steep rock slopes. Furthermore, the unhealthy areas were mainly located in Dawukougou where abandoned mines were concentrated, indicating that the original mining activities have had a large effect on vegetation ecology. After ecological restoration of abandoned mines, the vegetation coverage in the study area has increased to a certain extent, but the amplitude was not large. The situation of vegetation coverage in the northern part of the study area was worse than that in the southern part, due to abandoned mines mainly concentrating in the northern part of the Helan Mountains. The combination of hyperspectral remote sensing data and vegetation indices can comprehensively extract the characteristics of vegetation, accurately analyze the plant growth status, and provide technical support for vegetation health evaluation.

Key words： hyperspectral remote sensing abandoned mine ecological restoration vegetation growth status vegetation index vegetation coverage

Received: 30 May 2024 Published: 31 October 2024

Corresponding Authors: * MAO Zhengjun (mzj@xust.edu.cn)

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Cite this article:

MAO Zhengjun, WANG Munan, CHU Jiwei, SUN Jiewen, LIANG Wei, YU Haiyong. Feature extraction and analysis of reclaimed vegetation in ecological restoration area of abandoned mines based on hyperspectral remote sensing images. Journal of Arid Land, 2024, 16(10): 1409-1425.

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http://jal.xjegi.com/10.1007/s40333-024-0109-9 OR http://jal.xjegi.com/Y2024/V16/I10/1409

Fig. 1 Geographical location of the study area. DEM, digital elevation model.

Fig. 2 Spatial distribution of vegetation coverage in the study area. FVC, fractional vegetation cover.

Table 1 Area and proportion of vegetation coverage at different levels in the study area

Table 2 Weight of each vegetation index based on the triangular fuzzy number analytic hierarchy process (TFN-AHP)

Fig. 3 Spatial distribution of vegetation growth status in the study area

Fig. 4 Landform type of abandoned mine after ecological restoration in the study area. (a), platform-slope system; (b), mine pit; (c), flat land.

Fig. 5 Typical high and steep rock slope


[1]	An D S, Yu D D, Liu Y, et al. 2022. A comparison of the LAI retrieval for subalpine meadows in Wuyishan by hyperspectral and simulated multispectral vegetation index. Ecological Science, 41(5): 187-196. (in Chinese)

[2]	Bai Z K, Zhou W, Wang J M, et al. 2018. Rethink on ecosystem restoration and rehabilitation of mining areas. China Land Science, 32(11): 1-9.

[3]	Bannari A, Morin D, Bonn F, et al. 1996. A review of vegetation indices. Remote Sensing Reviews, 13(1-2): 95-120.

[4]	Bi Y L. 2017. Research advance of application of arbuscular mycorrhizal fungi to ecological remediation in subsided land of coal mining areas. Mycosystema, 36(7): 800-806. (in Chinese)

[5]	Brown M E, McCarty J L. 2017. Is remote sensing useful for finding and monitoring urban farms? Applied Geography, 80: 23-33.

[6]	Campbell J B, Wynne R H. 1987. Introduction to Remote Sensing. New York: The Guilford Press, 551.

[7]	Cai S Y, Fan J M, Yang W, et al. 2021. Flooding risk assessment and analysis based on GIS and the TFN-AHP method: a case study of Chongqing, China. Atmosphere, 12(5): 623, doi: 10.3390/atmos12050623.

[8]	Chen C, Li S M, Wang Y Y, et al. 2022. Study on vegetation growth environment and spatial-temporal evolution in Wenshan Prefecture under high-resolution satellite monitoring. Journal of Yunnan University (Natural Sciences Edition), 44(6): 1183-1193. (in Chinese)

[9]	Du J Q, Quan Z J, Fang S F, et al. 2019. Spatiotemporal changes in vegetation coverage and its causes in China since the Chinese economic reform. Environmental Science and Pollution Research, 27: 1144-1159.

[10]	Fan Z Q, Wang Z G, Huang P P, et al. 2023. Inversion analysis of lake chlorophyll-a concentration based on hyperspectral images. Ecological Science, 42(1): 121-128. (in Chinese)

[11]	Feng J Z, Pan Y Q, Xiong Y S, et al. 2024. Rice key growth stage identification based on mRMR-XGBoost. Transactions of the Chinese Society of Agricultural Engineering, 40(15): 111-118. (in Chinese)

[12]	Goetz A F H, Vane G, Solomon J E, et al. 1985. Imaging spectrometry for earth remote sensing. Science, 228(4704): 1147-1153. doi: 10.1126/science.228.4704.1147 pmid: 17735325

[13]	Hao G C, Dong Z L, Guo H W. 2024. Some thoughts on ecological restoration of highway exposed slope under the background of "double carbon". Transportation Energy Saving and Environmental Protection, 20(4): 123-127. (in Chinese)

[14]	He L. 2023. Ecological restoration practice of high and steep rock slope in open-pit mine. China Metal Bulletin, 17: 116-118. (in Chinese)

[15]	He Y, Chen Y C, Talat A E, et al. 2024. Spatio-temporal pattern and trend prediction of soil erosion in Kuye River Basin. Journal of Soil and Water Conservation, doi: 10.13870/j.cnki.stbcxb.2024.05.028. (in Chinese)

[16]	Hong J, Shu Q T, Wu J J, et al. 2016. The health classification of Pinus densata typical forest ecosystem in alpine region of northwestern Yunnan based on hyperion data. Journal of Southwest Forestry University (Natural Sciences), 36(6): 79-86. (in Chinese)

[17]	Hu X W, Cao S, Zhao X F. 2012. Comparison of green space information extraction based on vegetation index. Journal of Nanjing University of Information Science & Technology, 4(5): 420-425. (in Chinese)

[18]	Hu Z Q, Wei Z Y, Qin P. 2005. The concept and method of soil reconstruction for mine reclamation. Soils, 37(1): 8-12. (in Chinese)

[19]	Hu Z Q. 2022. Theory and method of soil reconstruction of reclaimed mined land. Journal of China Coal Society, 47(7): 2499-2515. (in Chinese)

[20]	Jia K, Yao Y J, Wei X Q, et al. 2013. A review on fractional vegetation cover estimation using remote sensing. Advances in Earth Science, 28(7): 774-782. (in Chinese) doi: 10.11867/j.issn.1001-8166.2013.07.0774

[21]	Jin X Y. 2023. Study on the preparation and application effect of water-retaining material suitable for spray seeding substrate. MSc Thesis. Changchun: Jilin Agricultural University. (in Chinese)

[22]	Kang L F, Zhao R F, Lu H T, et al. 2024. Quantitative identification of the impact of climate change and human activities on the ecological quality of vegetation in the Shiyang River Basin over the past 20 years. Environmental Science, doi: 10.13227/j.hjkx.202404129. (in Chinese)

[23]	Ketema A, Dwarakish G S. 2021. Water erosion assessment methods: a review. ISH Journal of Hydraulic Engineering, 27(4): 434-441.

[24]	Kuang C P, Cong X, Han X J, et al. 2024. Review on hydrodynamic and sediment transport numerical models considering effects of coastal vegetation. Journal of Tongji University (Natural Science), 52(9): 1418-1427. (in Chinese)

[25]	Li S J, Yang X H. 2021. Analysis of hydrogeological conditions in Dawukou area of Shizuishan City, Ningxia. China Metal Bulletin, 9: 216-217. (in Chinese)

[26]	Li X S, Li Z Y, Gao Z H, et al. 2010. Estimation of sparse vegetation cover in arid regions based on vegetation indices derived from hyperion data. Journal of Beijing Forestry University, 32(3): 95-100. (in Chinese)

[27]	Li Z Y, Fang H Y. 2016. Impacts of climate change on water erosion: A review. Earth-Science Reviews, 163: 94-117.

[28]	Liu B R, Li G Q, Jiang X S. 2021. Countermeasures and evaluation of ecological restoration of mines in Helan Mountains Nature Reserve. Journal of Ningxia Agriculture and Forestry Science and Technology, 62(4): 40-43, 50. (in Chinese)

[29]	Liu D Y, Jia K, Wei X Q, et al. 2019. Spatiotemporal comparison and validation of three global-scale fractional vegetation cover products. Remote Sensing, 11(21): 2524, doi: 10.3390/rs11212524.

[30]	Liu Z, Liu D Y, Zhu D H, et al. 2018. Research progress and prospect of fine recognition and automatic mapping of crops by remote sensing. Transactions of Agricultural Machinery, 49(12): 1-12. (in Chinese)

[31]	Ma K. 2013. Research on the forest health evaluation of Qinling Huoditang based on the hyperspectral data. MSc Thesis. Xianyang: Northwest A & F University.

[32]	Ma K, Zhao P X, Ji F F, et al. 2013. Study on forest health assessment method based on vegetation index in Qinling Mountains. Journal of Northwest Forestry University, 28(6): 145-150. (in Chinese)

[33]	Mao Z J, Li C, Chen J P, et al. 2021. Present situation, environmental geological problems and countermeasures and suggestions of limestone open-pit mining area in Weibei. Coal Technology, 40(8): 91-94. (in Chinese)

[34]	Mao Z J, Shi S J, Li H, et al. 2022. Landslide susceptibility assessment using triangular fuzzy number-analytic hierarchy processing (TFN-AHP), contributing weight (CW) and random forest weighted frequency ratio (RF weighted FR) at the Pengyang County, Northwest China. Environmental Earth Sciences, 81: 86, doi: 10.1007/s12665-022-10193-3.

[35]	Ningxia Helan Mountain National Nature Reserve Management Bureau. 2022. Strengthen the Concept of Green Development to Build Harmony between Man and Nature—Ningxia Helan Mountain Ecological Protection and Restoration Has Achieved Remarkable Results—Harmonious Helan Mountain. [2024-03-01]. http://www.hlsbhq.com/index.php/shows/499/4817.html. (in Chinese)

[36]	Parmesan C, Yohe G. 2003. A globally coherent fingerprint of climate change impacts across natural systems. Nature, 421(6918): 37-42.

[37]	Peng Y, Mi K, Qin Y, et al. 2014. Spectral reflectance characteristics of dominant plant species at different eco-restoring stages in the semi-arid grassland. Spectroscopy and Spectral Analysis, 34(11): 3090-3094. (in Chinese) pmid: 25752064

[38]	Qiu D. 1991. Systematic Analysis of Multi-index Comprehensive Evaluation Method. Beijing: China Statistics Press, 123-124. (in Chinese)

[39]	Rui D H, Ji M C, Nakamur D, et al. 2018. Experimental study on gravitational erosion process of vegetation slope under freeze-thaw. Cold Regions Science and Technology, 151: 168-178.

[40]	Sun W Y, Song X Y, Mu X M, et al. 2015. Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau. Agricultural and Forest Meteorology, 209-210: 87-99.

[41]	Sun X F, Yuan L G, Zhou Y Z, et al. 2021. Spatiotemporal change of vegetation coverage recovery and its driving factors in the Wenchuan earthquake-hit areas. Journal of Mountain Science, 18(11): 2854-2869.

[42]	Singh M, Hartsch K. 2019. Basics of soil erosion. In: Yousuf A, Singh M. Watershed Hydrology, Management and Modeling. CRC Press, 9-121.

[43]	Tang H, Zhang L T. 2024. Analysis of urban vegetation changes and drivers in plateau and river valleys. Environmental Science, doi: 10.13227/j.hjkx.202401244. (in Chinese)

[44]	Wang C. 2019. The responds of vegetation to the groundwater depth in the grassland open-pit coal mine area. MSc Thesis. Hohhot: Inner Mongolia University.

[45]	Wang M L, Dai X A. 2018. Study on the relationship between vegetation coverage and temperature based on MODIS hyperspectral data. Science of Surveying and Mapping, 43(4): 138-143. (in Chinese)

[46]	Wu G J, Tan H P, Sun K, et al. 2020. Characteristics and tectonic significance of gravity anomalies in the Helanshan-Yinchuan Graben and adjacent areas. Chinese Journal of Geophysics, 63(3): 1002-1013. (in Chinese)

[47]	Xu Y N. 2006. Investigation and Evaluation of Mine Environmental Geological Problems in Northwest China. Beijing: Geological Publishing House, 27-28. (in Chinese)

[48]	Yan J. 2023. Urban forest based on multi-source and multi-temporal remote sensing. MSc Thesis. Nanjing: Nanjing Forestry University. (in Chinese)

[49]	Yu T, Pang Y, Meng S L, et al. 2023. Remote sensing estimation and change analysis of fractional vegetation coverage in natural forest resource protection project area. Journal of Beijing Forestry University, 45(5): doi: 10.12171/j.1000-1522.20220324. (in Chinese)

[50]	Yue Y F, Zhao W Z, Liu R T, et al. 2024. Study on spatio-temporal changes and driving mechanisms of ecological environment quality in desert steppe belt of Ningxia. Acta Ecologica Sinica, 44(20): 1-14. (in Chinese)

[51]	Yue Y M, Wang K L, Zhang B, et al. 2008. Advances in the application of hyperspectral remote sensing in ecosystem re-search. Remote Sensing Technology and Application, 23(4): 471-478. (in Chinese)

[52]	Zhang C Y, Li J, Lei S G, et al. 2022. Progress and prospect of the quantitative remote sensing for monitoring the eco-environment in mining area. Metal Mine, 549(3): 1-27. (in Chinese)

[53]	Zhang F R. 2022. Introduction to Rocks, Soils and Lands. Beijing: China Agricultural University Press, 97-98. (in Chinese)

[54]	Zhang G C, Lin Z L. 2020. Research on vegetation coverage extraction based on hyperion hyperspectral remote sensing image. Journal of Fujian Normal University (Natural Science Edition), 36(1): 79-86, 95. (in Chinese)

[55]	Zhang J D, Xi F R. 2020. Study on ecological restoration of abandoned mines in China. Acta Ecologica Sinica, 40(21): 7921-7930. (in Chinese)

[56]	Zhang L, Ren F P, Li H, et al. 2021. The influence mechanism of freeze-thaw on soil erosion: a review. Water, 13(8): 1010, doi: 10.3390/w13081010.

[57]	Zhang P Q, Sun Y F, Chang Q Q, et al. 2024. Solid waste identification of Zhuhai-1 hyperspectral satellite remote sensing data based on optical flow estimation: a case study of Jiyuan demonstration area in Henan Province. Bulletin of Surveying and Mapping, 1: 44-50. (in Chinese)

[58]	Zhang X Q, Hu M C, Guo X Y, et al. 2018. Effects of topographic factors on runoff and soil loss in Southwest China. Catena, 160: 394-402.

[59]	Zhang Y B, Du J M, Bi Y G, et al. 2023a. Research on desert grassland coverage extraction method based on UAV hyperspectral remote sensing. Journal of Optoelectronics·Laser, 34(8): 842-850. (in Chinese)

[60]	Zhang Y W, Guo Y P, Tang R, et al. 2023b. Progress and trends of application of hyperspectral remote sensing in plant diversity research. National Remote Sensing Bulletin, 27(11): 2467-2483. (in Chinese)

[61]	Zhong A Y, Bao C, Hu C M. 2024. Spatiotemporal dynamic change monitoring of NDVI in mining areas of Dexing City from the perspective of ecological restoration. Environmental Engineering, 42(5): 122-130. (in Chinese)

[62]	Zhou P, Luukkanen O, Tokola T, et al. 2008. Effect of vegetation cover on soil erosion in a mountainous watershed. Catena, 75(3): 319-325.

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