Ms. Junrong Liu Profile

Junrong Liu

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Proceedings Article | 19 January 2024 Paper

Monitoring and analysis of eco-environmental quality in Yulin City from 2000 to 2020 based on Remote Sensing Ecological Index (RSEI)

Xingcheng Wang, Kailei Xu, Shengjie Yang, Junrong Liu, Yu Li, Jiaqi Xiong

Proceedings Volume 12980, 129802N (2024) https://doi.org/10.1117/12.3020995

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Yulin City serves as an important coal industrial base in the Yellow River Basin，also a typical ecological fragile area in China, and its eco-environmental quality changes have attracted much attention in recent years. In order to effectively monitor the changes of eco-environmental quality in Yulin City and further assess the effectiveness of ecological restoration in Yulin City, the research integrated multi sensors including Landsat TM, ETM, OLI and MODIS land surface temperature products to construct long time-series Remote Sensing Ecological Index (RSEI) based on Google Earth Engine (GEE) platform. Then, patterns and changes of spatial-temporal distribution from 2000—2020 in Yulin City were revealed and driving force was discussed. Results show that: (1) The eco-environmental quality of Yulin City improved to a large extent from 2000 to 2020, with a significant improvement exceeding 56% of the whole study area which mainly occurred in the southeast of Yulin; Notably, the potential risk of eco-environmental quality degradation exists in the north and southwest; (2) The eco-environmental quality of Yulin City shows obvious geomorphological differences: the eco-environmental quality of Loess Plateau areas in the southeast is much better than that of the Windblown Sand Grassland areas in the north; (3) Transformation of land use types caused by the implementation of policies such as returning farmland to forests and grasslands and mine ecological restoration plays a leading role in the process of restoring the quality of the ecological environment, while extreme meteorological disasters such as droughts can lead to rapid deterioration of the eco-environmental quality.

Proceedings Article | 15 November 2023 Paper

Estimating and analyzing the spatiotemporal pattern of net primary productivity in Qinba area by combing remote sensing data and BIOME-BGC Model

Chuang Yang, Siyu Chen, Junrong Liu, Kailei Xu

Proceedings Volume 12815, 128150V (2023) https://doi.org/10.1117/12.3011202

KEYWORDS: Carbon, Vegetation, Data modeling, Atmospheric modeling, Ecosystems, Lithium, Remote sensing, Biological research, Meteorology, Climate change

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Studying the spatial and temporal changes of NPP in the Qinba area can provide scientific and technological data support for the realization of regional carbon neutrality goals. We use site parameters, geographical conditions monitoring data, MCD43A3 and a series of daily meteorological grid data to simulate daily NPP dataset at a spatial resolution of 500 m× 500 m during 2000-2020. The results show that the spatial distribution of NPP in the ecosystem of the Qinba area is significantly different. The NPP of the eastern part of the Qinba Mountains shows a decreasing trend, while the NPP in the western and southern parts shows an increasing trend. The significantly increased area accounts for 38.71% of the total area. Under the RCP4.5 scenario mode, it is predicted that the NPP in the Qinba Mountains will reach 337 gCm^-2a^-1 in the next 80 years. However, the positive effects of temperature, precipitation, and CO2 concentration on vegetation growth tend to flatten out in 2060. Climate change after 2060 may have a reverse inhibitory effect on vegetation growth.

Proceedings Article | 9 August 2023 Paper

Application of SBAS-INSAR technology in surface subsidence monitoring in Yanghuopan mining area

Junrong Liu, Kailei Xu, Xiaoguang Jiang, Siyu Chen, Jun Chen

Proceedings Volume 12782, 1278214 (2023) https://doi.org/10.1117/12.3000767

KEYWORDS: Mining, Deformation, Phase unwrapping, Interferograms

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With the underground mining in Yanghuopan mining area, the original stress balance state in the rock mass is broken, causing the rock strata and even the ground surface around the goaf to move and deform, resulting in land subsidence and deformation and damage of surface buildings, affecting industrial and agricultural construction and people's living environment. The application of small baseline Radar Interferometry Technology in land subsidence monitoring provides a new means for the monitoring and analysis of land subsidence in Yanghuopan mining area. In this manuscript, SBAS-INSAR technology is used to monitor the land subsidence caused by underground mining in Yanghuopan mining area. Based on 33 sentinel-1A images from June 2019 to August 2020, the surface deformation center, deformation rate, cumulative deformation variables and other information of Yanghuopan coal mine were obtained, and the surface deformation of the mining area was interpreted and analyzed. The main settlement area of the mining area is located in the east of the mining area. The maximum settlement rate in the mining area is -96mm/y, and the maximum cumulative deformation is -119mm.

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