Showing 81 - 100 results of 6,296 for search '(( significant spatial decrease ) OR ( significantly ((longer decrease) OR (larger decrease)) ))', query time: 2.19s Refine Results
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    Spatial variation of water availability in Hebi. by Shaolei Guo (3146259)

    Published 2024
    “…The results indicate that: (1) During the study period, the overall land use type in Hebi City has been constantly changing, with the most significant conversion from arable land to other land types; combined with its landscape pattern index, Hebi City has a general characteristic of significant landscape fragmentation and complexity in land use. (2) Habitat quality in Hebi shows an overall trend towards better development, with water availability decreasing and then increasing; the zoning of ecosystem services in Hebi is divided into three classes: superior, good and general, with the area covered by the superior and general classes expanding year by year. (3) Correlation analysis by SPSS software shows that the correlation between habitat quality and landscape pattern index is greater than the correlation between habitat quality and climate change. …”
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    Spatial distribution of ESs. by Bao Zhou (20670850)

    Published 2025
    “…In future scenarios, the SDG index increases in the southern part while decreasing in the eastern part, indicating significant differences in regional sustainable development potential. …”
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    Detailed information of the observation datasets. by Weidong Ji (129916)

    Published 2025
    “…Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
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    General technical specification for GW154/6700. by Weidong Ji (129916)

    Published 2025
    “…Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”
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