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  1. 1821

    Adapting Cross-Sensor High-Resolution Remote Sensing Imagery for Land Use Classification by Wangbin Li, Kaimin Sun, Jinjiang Wei

    Published 2025-03-01
    “…Specifically, to address the discrepancies in spatial resolution, a novel positional encoding has been incorporated to capture the correlation between the spatial resolution details and the characteristics of ground objects. …”
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    Article
  2. 1822

    Spatio SLAM: An Integrated Strategy for Robot Autonomy in Variable Indoor Luminance by Rapti Chaudhuri, Suman Deb, Abhijit Das

    Published 2025-01-01
    “…To address these challenges, we propose a spatial-geometric SLAM (Spatio SLAM) solution that unifies the exiting connotations of long and short-term dynamics that constructs a real-time dense spatial-geometric map. …”
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    Article
  3. 1823

    STGATN: a wind speed forecasting method based on geospatial dependency by Xingtong Ge, Ling Peng, Yi Yang, Cang Qin, Jiahui Chen, Hongze Liu, Zhaobo Li

    Published 2025-08-01
    “…Accurate wind speed forecasting is crucial for power systems, but wind speed as a spatially continuous field presents high randomness, fluctuation, and spatial heterogeneity under complex geographical environments, leading to challenges for predictive modeling. …”
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    Article
  4. 1824

    Contamination, Ecotoxicological Risks, and Sources of Potentially Toxic Elements in Roadside Dust Along Lahore–Islamabad Motorway (M-2), Pakistan by Ibrar Hayat, Wajid Ali, Said Muhammad, Muhammad Nafees, Abdur Raziq, Imran Ud Din, Jehanzeb Khan, Shahid Iqbal

    Published 2025-06-01
    “…This study evaluates the concentration, spatial distribution, and ecological risks of PTEs (Mn, Ni, Cr, Cu, Pb, Zn, Cd, Ag, Fe) in road dust along the M-2. …”
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    Article
  5. 1825
  6. 1826

    Urban Thermal Archetype Classification in the Context of Urban Development Transformation Using Machine Learning Techniques by Yan Deng, Huimin Liu

    Published 2025-01-01
    “…In pursuit of urban climate resilience, it is crucial to characterize the spatial heterogeneity of urban thermal environments for spatially targeted mitigation, with the local climate zone (LCZ) framework emerging as a prevailing and powerful tool. …”
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    Article
  7. 1827

    Asymmetric effects of natural and socioeconomic factors on PM2.5 pollution in Chinese counties by Biao Sun, Jihong Li

    Published 2025-05-01
    “…Abstract With rapid urbanization intensifying air pollution, especially PM2.5, which poses a serious threat to public health, clarifying its spatial differentiation patterns and driving mechanisms is of great practical significance. …”
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    Article
  8. 1828
  9. 1829

    Seafloor surficial sediment variability across the abyssal plains of the central and eastern pacific ocean by Devin Harrison, Devin Harrison, Jessica L. Kolbusz, Todd Bond, Catriona Macdonald, Yakufu Niyazi, Alan J. Jamieson, Heather A. Stewart, Heather A. Stewart

    Published 2025-04-01
    “…However, it is also one of the least explored parts of the ocean due to the logistical challenges of exploring at great depths over vast spatial scales. This work presents the first results of the Trans-Pacific Transit (TPT), a six-leg expedition that collected remote imagery and video footage of the seafloor sediments and substrate habitats of the central and eastern Pacific Ocean. …”
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  10. 1830
  11. 1831
  12. 1832
  13. 1833

    Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes by Xuan Liu, Li Xu, Jianghua Zheng, Jun Lin, Xuan Li, Liang Liu, Ruikang Tian, Chen Mu

    Published 2024-11-01
    “…The results indicate that the ensemble model integrating Random Forest (RF), Gradient Boosting Machine (GBM), and Maximum Entropy Model (MaxEnt) performed best within the present climate context. The model predicted the potential distribution of R. opimus in Central Asia with an area under the curve (AUC) of 0.986 and a True Skill Statistic (TSS) of 0.899, demonstrating excellent statistical accuracy and spatial performance. …”
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  14. 1834
  15. 1835

    Feeding of walleye pollock and its feeding base in the Chukchi Sea in summer-autumn period by N. A. Kuznetsova, M. A. Shebanova

    Published 2023-04-01
    “…Data on feeding of walleye pollock <i>Gadus chalcogrammus</i> (3–70 cm long) in the Chukchi Sea in summer-autumn of 2017–2020 are presented. The food base includes zooplankton, benthic invertebrates and fish. …”
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  16. 1836

    Attention Residual Hybrid Network for Unmanned Aerial Vehicles Hyperspectral Image Classification by Zhen Zhang, Linhuan Jiang, Bo-Hui Tang, Jianchen Liu, Qingwang Wang, Yabin Hu, Liang Huang, Zhitao Fu

    Published 2025-01-01
    “…Unmanned aerial vehicle (UAV) hyperspectral images are endowed with abundant spectral information and spatial texture details, which are crucial for the precise classification and monitoring of terrestrial features. …”
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    Article
  17. 1837

    Investigation of the processes of regional convergence and divergence in the development of the higher education system by S. V. Avilkina

    Published 2021-10-01
    “…This article describes methodological approaches to the analysis of statistical data characterizing trends in the development of the higher education system in the constituent entities of the Russian Federation and presents the results of a study of changes that have occurred in the period from 1995 to 2019 in the Russian Federation in the spatial concentration of the number of university students. …”
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  18. 1838

    Variabilidade espacial de variáveis físico-hídricas do solo em um pomar de lima ácida Tahiti, irrigado por microaspersão Spatial variability of soil hydrophysical variables in a Ta... by Maurício A. Coelho Filho, Rubens D. Coelho, Antônio C.A. Gonçalves

    Published 2001-05-01
    “…The results showed medium variability for sand, silt, AWt and AWpwp. In the scope of the present work, the spatial independence was verified. …”
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  19. 1839

    Landscape Ecological Risk Assessment and Its Driving Factor Analysis in Ordos-Yulin Area by Ma Jun, Pei Yanru, Wang Huiyuan, Yu Qiang, Niu Teng, Yue Depeng

    Published 2022-04-01
    “…From 2010 to 2020, the areas with medium ecological risk, higher ecological risk, and low ecological risk showed a contraction trend, while areas with low ecological risk and lower ecological risk showed an expansion trend; ③ The global autocorrelation analysis of Moran's I index in 2000, 2010, 2020 was greater than 0.8, showing a significant positive correlation in spatial distribution. Most ecological risk units presented high-high and low-low distribution, and a small number of ecological risk units were high-high and low. …”
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  20. 1840

    An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

    Published 2025-08-01
    “…Abstract Spatial evaluation of the region is associated with the assessment of the quality of water. …”
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