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Mapping annual dynamics of surface mining disturbances in the northeastern Tibetan Plateau using Landsat imagery and LandTrendr algorithm

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Environmental Monitoring and Assessment
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The exploitation and utilization of coal resources have significantly contributed to global energy security. However, this mining activity has inflicted considerable damage on the ecological environment, particularly on the Tibetan Plateau, where the impact on ecosystems may be even more detrimental. The implementation of high-intensity mining activities leads to rapid changes in land cover/land use. Consequently, it is essential to accurately and effectively monitor mining disturbances. In this study, we propose an approach to capture surface mining disturbances using spatial–temporal rules and time series stacks of Landsat data. First, a time series of annual mining disturbance probability was generated based on Landsat temporal-spectral metrics and random forest. Second, the Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr) algorithm was employed to segment the time series and detect breakpoints. Finally, mining disturbances were captured by further restricting the output of LandTrendr based on spatial–temporal rules of mining disturbances. This approach was applied and evaluated in the Muli mining area of the northeastern Tibetan Plateau, which experienced large-scale and rapid mining disturbances from 2004 to 2014, and identified a disturbed mining area of 43.62 km². The mining sites have been reclaimed after mining, and all reclamation work was done after 2016, with a total reclaimed area of 22.28 km². The validation results indicated that the overall accuracy of mining disturbance and reclamation mapping ranges from 0.7333 to 0.8667, and the F1 scores for mining disturbances and reclamation range from 0.7551 to 0.8723. This study provides a reliable framework for monitoring mining disturbances and reclamation in surface mines, promising to be useful in realizing disturbance monitoring in surface mines for a wide range of mineral types.
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Vol.: (0123456789)
Environ Monit Assess (2024) 196:934
https://doi.org/10.1007/s10661-024-13095-y
RESEARCH
Mapping annual dynamics ofsurface mining disturbances
inthenortheastern Tibetan Plateau using Landsat imagery
andLandTrendr algorithm
HangXu· XuWang· JianweiZhou· LeiXu·
LiyanYang
Received: 11 April 2024 / Accepted: 6 September 2024 / Published online: 15 September 2024
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024
Abstract The exploitation and utilization of coal
resources have significantly contributed to global
energy security. However, this mining activity has
inflicted considerable damage on the ecological envi-
ronment, particularly on the Tibetan Plateau, where
the impact on ecosystems may be even more detri-
mental. The implementation of high-intensity mining
activities leads to rapid changes in land cover/land
use. Consequently, it is essential to accurately and
effectively monitor mining disturbances. In this study,
we propose an approach to capture surface mining
disturbances using spatial–temporal rules and time
series stacks of Landsat data. First, a time series of
annual mining disturbance probability was generated
based on Landsat temporal-spectral metrics and ran-
dom forest. Second, the Landsat-based detection of
Trends in Disturbance and Recovery (LandTrendr)
algorithm was employed to segment the time series
and detect breakpoints. Finally, mining disturbances
were captured by further restricting the output of
LandTrendr based on spatial–temporal rules of min-
ing disturbances. This approach was applied and
evaluated in the Muli mining area of the northeast-
ern Tibetan Plateau, which experienced large-scale
and rapid mining disturbances from 2004 to 2014,
and identified a disturbed mining area of 43.62 km2.
The mining sites have been reclaimed after mining,
and all reclamation work was done after 2016, with
a total reclaimed area of 22.28 km2. The validation
results indicated that the overall accuracy of mining
disturbance and reclamation mapping ranges from
0.7333 to 0.8667, and the F1 scores for mining distur-
bances and reclamation range from 0.7551 to 0.8723.
This study provides a reliable framework for monitor-
ing mining disturbances and reclamation in surface
mines, promising to be useful in realizing disturbance
monitoring in surface mines for a wide range of min-
eral types.
Keywords Mining disturbances· Time series·
Random forest· Spatial–temporal rules· LandTrendr
H.Xu· X.Wang(*)· L.Yang
School ofGeography andInformation Engineering, China
University ofGeosciences, Wuhan430074, China
e-mail: wangxu@cug.edu.cn
H. Xu
e-mail: hangxucug@gmail.com
L. Yang
e-mail: yangliyan0048@sina.com
J.Zhou
School ofEnvironmental Studies, China University
ofGeosciences, Wuhan430074, China
e-mail: jw.zhou@cug.edu.cn
L.Xu
School ofRemote Sensing andInformation Engineering,
Wuhan University, Wuhan430000, China
e-mail: llxuwhu@gmail.com
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