歸一化植被指數（NDVI）在草原露天煤礦區的適用性分析

惠嘉偉; 白中科; 劉凱杰; 王子昊

doi:10.13374/j.issn2095-9389.2021.08.03.002

歸一化植被指數（NDVI）在草原露天煤礦區的適用性分析

doi: 10.13374/j.issn2095-9389.2021.08.03.002

惠嘉偉¹,
白中科^{1, 2, 3, ,},
劉凱杰¹,
王子昊¹

1.
中國地質大學（北京）土地科學技術學院，北京 100083
2.
自然資源部土地整治重點實驗室，北京 100035
3.
自然資源部礦區生態修復工程技術創新中心，北京 100083

基金項目: 內蒙古典型礦區生態修復技術集成與示范（2020ZD0020）

詳細信息

通訊作者:
E-mail: baizk@cugb.edu.cn

中圖分類號: TG142.71
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- 文章訪問數: 535
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- PDF下載量: 57
- 被引次數: 0
出版歷程
- 收稿日期: 2021-08-03
- 網絡出版日期: 2021-12-18
- 刊出日期: 2023-01-01

Applicability analysis of normalized difference vegetative index (NDVI) in grassland open-pit coal mine

1.
School of Land Science and Technology, China University of Geosciences, Beijing 100083, China
2.
Key Lab of Land Consolidation and Rehabilitation, the Ministry of Natural Resources, Beijing 100035, China
3.
Technology Innovation Center of Ecological Restoration Engineering in Mining Area, the Ministry of Natural Resources, Beijing 100083, China

More Information

Corresponding author: E-mail: baizk@cugb.edu.cn

摘要

摘要: 煤炭生產不可避免地會對生態環境造成影響，在煤炭生產中，生態環境監測是經濟可持續發展的重要環節。目前煤礦生態監測的最常見的方法是基于歸一化植被指數（NDVI）的植被覆蓋度計算，但在對露天礦的植被監測實驗中，基于NDVI的植被覆蓋度計算結果出現了的誤差。為了給草原礦區生態監測提供合適的方法，本文利用Sentinel-2數據采取遙感波段反演的方法計算了研究區的NDVI。并采取實證對比的方法對勝利、平朔礦區的NDVI分布特征進行了研究。結果表明：NDVI在具有一定植被覆蓋的區域能夠良好的反映地表植被覆蓋情況，但在礦區內部被煤炭覆蓋的區域可能會出現一定程度的誤差。誤差現象在兩個研究區均會出現，且在勝利礦區影響更加嚴重。推測誤差現象出現的原因是由于NDVI歸一化算法的不足導致僅使用NDVI為參數無法區分光譜曲線具有相似特征的煤炭覆蓋區域和中低覆蓋草地，因而建議在礦區植被監測中將相關區域進行掩膜處理或更換植被指數以避免此現象的影響。
- NDVI /
- 遙感植被監測 /
- 勝利礦區 /
- 平朔礦區 /
- Sentinel-2
Abstract: Coal production will inevitably have an impact on the ecological environment. It has become the consensus of all major countries that vegetation restoration should be carried out in coal mining areas. Monitoring the vegetation in the mining area is an important part of the vegetation restoration work in the mining area, and plays an important role in the design, implementation, management and maintenance of the vegetation work in the mining area. The calculation of vegetation coverage based on NDVI is currently the most common method of coal mine ecological monitoring. It was discovered during is the process that calculating vegetation coverage based on NDVI would cause serious errors. Sentinel-2 data was used to calculate the NDVI of the study area using the remote sensing band inversion method tostudy the reasons for the formation of the error zone and provide a suitable method for ecological monitoring of grassland mining areas. Furthermore, the empirical comparison method was used to investigate the NDVI distribution characteristics of the Shengli and Pingshuo mining areas. This phenomenon has also appeared in other research results. The results show that NDVI can accurately reflect the surface vegetation coverage in areas with specific vegetation coverage, but there will be significant error areas in coal-covered areas in the mining area. The error phenomenon will appear in both study areas, with a greater impact in the Shengli mining area. This error phenomenon is caused by the inadequacy of the NDVI’s normalization algorithm, which makes distinguishingbetween coal-covered areas and low-to-medium-covered grasslands with similar characteristics in spectral curves impossible. To avoid the impact of this phenomenon, we propose to mask the relevant areas or replace the vegetation index in the mining area’s vegetation monitoring.
- NDVI /
- remote sensing ecological monitoring /
- Shengli Coal Mine /
- Pingshuo Coal Mine /
- Sentinel-2

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圖 1 研究區位置

Figure 1. Location of the study area

下載: 全尺寸圖片幻燈片

圖 2 勝利礦區2019、2020年夏季植被覆蓋度分布.（a）2019年7月；（b）2019年8月；（c）2019年9月；（d）2020年7月；（e）2020年8月；（f）2020年9月

Figure 2. Distribution of vegetation coverage in the summer of 2019 and 2020 in Shengli Coal Mine: (a) July 2019; (b) August 2019; (c) September 2019; (d) July 2020; (e) August 2020; (f) September 2020

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圖 3 基于NDVI的植被覆蓋度誤差區域. (a)植被覆蓋度分布；（b）遙感影像(2020年9月19日，真彩色合成)

Figure 3. Vegetation coverage error area based on NDVI: (a) vegetation coverage distribution; (b) remote sensing image (September 19, 2020, true color synthesis)

下載: 全尺寸圖片幻燈片

圖 4 勝利礦區各區域抽樣光譜曲線.（a）誤差區域；（b）人工恢復區域；（c）自然植被區域

Figure 4. Sampling spectrum curve of each area in Shengli mining area: (a) error area; (b) artificial restoration area; (c) natural vegetation area

下載: 全尺寸圖片幻燈片

圖 5 平朔礦區NDVI分布.（a）2019年；（b）2020年

Figure 5. NDVI distribution in Pingshuo mining area: (a) 2019; (b) 2020

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圖 6 2020年平朔礦區NDVI誤差區域與人工修復區域對比.（a）2020年平朔礦區NDVI分布；（b）近期植被恢復區域；（c）誤差區域示例1；（d）誤差區域示例2；（e）誤差區域示例3

Figure 6. Comparison of NDVI error area and manual restoration area in Pingshuo mining area in 2020: (a) NDVI distribution in Pingshuo mining area in 2020; (b) recent vegetation restoration area; (c) error area example 1; (d) error area example 2; (e) error Area example 3

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圖 7 平朔礦區各區域抽樣光譜曲線.（a）誤差區域；（b）植被恢復完成區域；（c）近期植被恢復區域；（d）自然植被區域

Figure 7. Sampling spectrum curve of each area in Pingshuo mining area: (a) error area; (b) vegetation restoration completed area; (c) recent vegetation restoration area; (d) natural vegetation area

下載: 全尺寸圖片幻燈片

圖 8 其他研究成果中的“NDVI的礦區歸一化誤差”現象^[2].（a）原文研究地區；（b）Landsat 8OLI影像（2019年6月1日，真彩色合成）；（c）Google Earth高清影像（2019年8月27日）；（d）原文植被覆蓋度分布（2019年）；（e）NDVI

Figure 8. Phenomenon of "NDVI mining area normalization error" in other research results^[2]: (a) research area in the citation; (b) landsat 8OLI image (June 1, 2019, true color composite); (c) Google earth image (August 27, 2019); (d) distribution of vegetation coverage in citations (2019); (e) NDVI

下載: 全尺寸圖片幻燈片

表 1 遙感數據信息

Table 1. Remote sensing data information

Study area	Satellite	Imaging time	Spatial resolution/m
Shengli Coal Mine	Sentinel-2A	7, July, 2019	10
Shengli Coal Mine	Sentinel-2B	21, August, 2019	10
Shengli Coal Mine	Sentinel-2A	15, September, 2019	10
Shengli Coal Mine	Sentinel-2A	14, July, 2020	10
Shengli Coal Mine	Sentinel-2A	25, August, 2020	10
Shengli Coal Mine	Sentinel-2A	19, September, 2020	10
Pingshuo Coal Mine	Sentinel-2B	17, September, 2020	10
Pingshuo Coal Mine	Sentinel-2A	8, October, 2019	10

下載: 導出CSV

表 2 不同區域NDVI計算參數均值

Table 2. Calculation parameters of NDVI in different areas

Parameters	Error zone		Artificial recovery area		Natural vegetation
Parameters	2020	2019	2020	2019	2020	2019
NIR	0.030	0.050	0.195	0.360	0.321	0.461
R	0.016	0.014	0.065	0.153	0.207	0.095
NIR–R	0.014	0.018	0.130	0.104	0.114	0.183
NIR+R	0.046	0.032	0.259	0.257	0.527	0.278
NDVI	0.313	0.287	0.501	0.432	0.216	0.206

下載: 導出CSV

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