Dynamic Monitoring of Winter Wheat Health in Mining Subsidence Areas by Combined Active and Passive Remote Sensing Technology

Zhang, Haobin; Ma, Chao; Guo, Wenbing; Li, Tingting

doi:10.3390/land12112079

Cited by 2 publications

(1 citation statement)

References 49 publications

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“…The stress of rock mass is redistributed, and this contributes to rock mass fracture and movement. The fracture and movement of rock mass eventually form the ground surface deformation, soil subsidence, cracks, and fractures, and then the condition for crop habitats on the surface has been changed [50]. Previous studies reported that terrain changes caused by mining influence the physical and chemical properties of soil [11,25,51,52], and the phenotype and biomass of above-ground vegetation [12,53].…”

Section: Modeling Of Winter Wheat Agb Estimation In Coal Mining Areamentioning

confidence: 99%

Winter Wheat Aboveground-Biomass Estimation and Its Dynamic Variation during Coal Mining—Assessing by Unmanned Aerial Vehicle-Based Remote Sensing

Lyu,

Zhang,

Chen

et al. 2024

Agronomy

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Underground coal mining in coal-grain overlapped areas leads to land subsidence and deformation above the goaf, damaging cultivated land. Understanding the influencing process of coal mining on cultivated land and crops is important for carrying out timely land reclamation and stabilizing crop yield. Research has been carried out by using crop growth parameters to evaluate the damaging degree of cultivated land when the mining subsidence is stable, but few studies focus on the influence of land damage on crop growth when the subsidence is unstable during coal mining. Therefore, this study tracked the three growth stages of winter wheat by using UAV multispectral imagery to explore the dynamic influence of underground mining on winter wheat aboveground biomass (AGB). Firstly, a winter-wheat-AGB estimation model (R2 = 0.89, RMSE = 2.18 t/ha) was developed by using vegetation indexes (VIs), textures, and terrain data extracted from UAV imagery. Secondly, based on the winter-wheat-AGB estimation model, the winter wheat AGB was successfully estimated and mapped at different growth stages. The AGB of winter wheat in the coal mining-affected area was approximately 5.59 t/ha at the reviving stage, 8.2 t/ha at the jointing stage, and 15.6 t/ha at the flowering stage. Finally, combined with the progress of coal mining, the dynamic changing process of crops during underground mining can be inferred by analyzing the spatiotemporal variation in winter wheat AGB. Results showed that, in the dip direction, winter wheat AGB at the flowering stage was the highest at the compression zone, followed by the inner stretch zone, outer stretch zone, and neutral zone. The distance from the waterlogged area and the existence of cracks were found to be the important moderating variables affecting the crop growth status in the mining subsidence area. In the strike direction, there were significant differences in the wheat AGB-affected area as the mining proceeded. Even areas where AGB had previously significantly increased gradually transitioned to significant decreases with the end of mining. The research explores the dynamic changes in winter wheat AGB and land damage status during coal mining. It provides a rapid and non-destructive land-damage-monitoring method to protect cultivated land in mining areas.

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Section: Modeling Of Winter Wheat Agb Estimation In Coal Mining Areamentioning

confidence: 99%

Winter Wheat Aboveground-Biomass Estimation and Its Dynamic Variation during Coal Mining—Assessing by Unmanned Aerial Vehicle-Based Remote Sensing

Lyu,

Zhang,

Chen

et al. 2024

Agronomy

View full text Add to dashboard Cite

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Reconstruction of Coal Mining Subsidence Field by Fusion of SAR and UAV LiDAR Deformation Data

Yang,

Du,

Zou

et al. 2024

Remote Sensing

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The geological environment damage caused by coal mining subsidence has become an important factor affecting the sustainable development of mining areas. Reconstruction of the Coal Mining Subsidence Field (CMSF) is the key to preventing geological disasters, and the needs of CMSF reconstruction cannot be met by solely relying on a single remote sensing technology. The combination of Unmanned Aerial Vehicle (UAV) and Synthetic Aperture Radar (SAR) has complementary advantages; however, the data fusion strategy by refining the SAR deformation field through UAV still needs to be updated constantly. This paper proposed a Prior Weighting (PW) method based on Satellite Aerial (SA) heterogeneous remote sensing. The method can be used to fuse SAR and UAV Light Detection and Ranging (LiDAR) data for ground subsidence parameter inversion. Firstly, the subsidence boundary of Differential Interferometric SAR (DInSAR) combined with the large gradient subsidence of Pixel Offset Tracking (POT) was developed to initialize the SAR preliminary CMSF. Secondly, the SAR preliminary CMSF was refined by UAV LiDAR data; the weights of SAR and UAV LiDAR data are 0.4 and 0.6 iteratively. After the data fusion, the subsidence field was reconstructed. The results showed that the overall CMSF accuracy improved from ±144 mm to ±51 mm. The relative errors of the surface subsidence factor and main influence angle tangent calculated by the physical model and in situ measured data are 1.3% and 1.7%. It shows that the proposed SAR/UAV fusion method has significant advantages in the reconstruction of CMSF, and the PW method contributes to the prevention and control of mining subsidence.

show abstract

Dynamic Monitoring of Winter Wheat Health in Mining Subsidence Areas by Combined Active and Passive Remote Sensing Technology

Cited by 2 publications

References 49 publications

Winter Wheat Aboveground-Biomass Estimation and Its Dynamic Variation during Coal Mining—Assessing by Unmanned Aerial Vehicle-Based Remote Sensing

Winter Wheat Aboveground-Biomass Estimation and Its Dynamic Variation during Coal Mining—Assessing by Unmanned Aerial Vehicle-Based Remote Sensing

Reconstruction of Coal Mining Subsidence Field by Fusion of SAR and UAV LiDAR Deformation Data

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