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  • MDPI AG  (3)
  • Hai, Hongxin  (3)
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  • MDPI AG  (3)
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  • 1
    Online Resource
    Online Resource
    Evaluating Environmental Quality and Its Driving Force in Northeastern China Using the Remote Sensing Ecological Index
    MDPI AG ; 2022
    In:  Sustainability Vol. 14, No. 23 ( 2022-12-06), p. 16304-
    Details
    In: Sustainability, MDPI AG, Vol. 14, No. 23 ( 2022-12-06), p. 16304-
    Abstract: As one of the three major black soil regions in the world, northeastern China has an important strategic position there. Since the 20th century, the local environment has undergone great changes under the influence of the natural economy, and it is particularly important to quantitatively assess the degree of change. However, there have been few long-term quantitative studies of environmental spatial-temporal variances in the three northeastern provinces. Therefore, in this study, four typical remote sensing indices of the normalized difference vegetation index (NDVI), land surface temperature (LST), normalized differential building–soil index (NDBSI) and wetness (WET) were employed to construct the remote sensing ecological index (RSEI) using a principal component analysis (PCA) method based on the Google Earth Engine (GEE) platform in northeastern China. The spatiotemporal variations in the eco-environmental quality were detected using linear slope and M–K test, and the direct and interactive effects of different influencing factors on the RSEI changes during 2000–2020 were explored based on geographic detection. The results show that the interannual variations in the RSEI show a fluctuating upward trend, with an increase percentage of 12.45% in the last two decades, indicating that the ecological quality of northeast China has gradually improved. Furthermore, that the western and eastern Heilongjiang provinces and western Jilin provinces contributed substantially to the improvement of environmental quality, while the environmental quality of Jilin provinces and central Liaoning provinces decreased to varying degrees. Compared with 2000, the area with a fair environmental quality grade had the greatest change, and had decreased by 60.69%. This was followed by the area with an excellent quality grade, which increased by 117%. Land-use type had the greatest impact on environmental changes in northeastern China, but the impact degree gradually decreased, while the impact of socioeconomic factors such as the gross production of agriculture, forestry, animal husbandry and fishery and population density on environmental quality gradually increased. The major reason for the decline of environmental quality in central Jilin and central Liaoning is that urbanization development had occupied a large amount of cropland. This shows that taking into account the virtuous cycle of an ecological environment while promoting urban and rural development may be an important task for northeastern China in the future.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su142316304
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518383-7
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Research on Soil Moisture Inversion Method for Canal Slope of the Middle Route Project of the South to North Water Transfer Based on GNSS-R and Deep Learning
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 17 ( 2023-09-03), p. 4340-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 17 ( 2023-09-03), p. 4340-
    Abstract: The soil moisture from the South-to-North Water Diversion Middle Route Project is assessed in this study. Complex and variable geological conditions complicate the prediction of soil moisture in the study area. To achieve this aim, we carried out research on soil moisture inversion methods for channel slopes in the study area using massive monitoring data from multiple GNSS observatories on channel slopes, incorporating GNSS-R techniques and deep learning algorithms. To address the issue of low accuracy in linear inversion when using a single satellite, this study proposes a multi-satellite and multi-frequency data fusion technique. Furthermore, three soil moisture inversion models, namely, the linear model, BP neural network model, and GA-BP neural network model, are established by incorporating deep learning techniques. In comparison with single-satellite data inversion, with the data fusion technique proposed in this study, the correlation is improved by 12.7%, the root mean square error is reduced by 0.217, the mean square error is decreased by 0.884, and the mean absolute error is decreased by 0.243 with the linear model. With the BP neural network model, the correlation is increased by 15.4%, the root mean square error is decreased by 0.395, the mean square error is decreased by 0.465, and the mean absolute error is reduced by 0.353. Moreover, with the GA-BP neural network model, the correlation is improved by 6.3%, the root mean square error is decreased by 1.207, the mean square error is decreased by 0.196, and the mean absolute error is reduced by 0.155. The results indicate that performing data fusion by using multiple satellites and multi-frequency bands is a feasible approach for improving the accuracy of soil moisture inversion. These research findings provide new technical means for the risk analysis of deformation disasters in the expansive soil channel slopes of the South-to-North Water Diversion Middle Route Project.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15174340
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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    Online Resource
  • 3
    Online Resource
    Online Resource
    TerraSAR-X and GNSS Data for Deformation Detection and Mechanism Analysis of a Deep Excavation Channel Section of the China South–North Water-Diversion Project
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 15 ( 2023-07-29), p. 3777-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 15 ( 2023-07-29), p. 3777-
    Abstract: Due to expansive soils and high slopes, the deep excavated channel section of the China South–North Water-Diversion Middle-Route Project has a certain risk of landslide disaster. Therefore, examining the deformation law and mechanism of the channel slope in the middle-route section of the project is an extreme necessity for safe operation. However, the outdated monitoring method limits research on the surface deformation law and mechanism of the entire deep excavation channel section. For these reasons, we introduced a novel approach that combines SBAS-InSAR and GNSS, enabling the surface domain monitoring of the study area at a regional scale as well as real-time monitoring of specific target regions. By using SBAS-InSAR technology and leveraging 11-view high-resolution TerraSAR-X data, we revealed the spatiotemporal evolution law of surface deformations in the channel slopes within the study area. The results demonstrate that the predominant deformation in the study area was uplifted, with limited evidence of subsidence deformation. Moreover, there is a distinct region of significant uplift deformation, with the highest annual uplift rate reaching 19 mm/y. Incorporating GNSS and soil-moisture-monitoring timeseries data, we conducted a study on the correlation between soil moisture and the three-dimensional deformation of the ground surface, revealing a positive correlation between the soil moisture content and vertical displacement of the channel slope. Furthermore, combining field investigations on surface uplift deformation characteristics, we identified that the main cause of surface deformation in the study area was attributed to the expansion of the soil due to water absorption in expansive soils. The research results not only revealed the spatiotemporal evolution law and mechanism of the channel slope deformation in the studied section of the deep excavation channel but also provide successful guidance for the prevention and control of channel slope-deformation disasters in the study area. Furthermore, they offer effective technical means for the safe monitoring of the entire South–North Water-Diversion Middle-Route Project and similar long-distance water-conveyance canal projects.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15153777
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
    Location Call Number Limitation Availability
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    Online Resource
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