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6 та иш

Иш: Do adaptive policy adjustments deliver ecosystem-agriculture-economy co-benefits in land degradation neutrality efforts? Evidence from southeast coast of China

  1. Potential effects of projected global sea level rise on Sundarbans mangrove wetland ecosystem: insights from SLAMM and hybrid machine learning models

    Ismail Mondal, SK Ariful Hossain, Jatisankar Bandyopadhyay +5

    МақолаCoastal wetland ecosystem dynamicsEnvironment Development and Sustainability20257 иқтибос
    ABI

  2. Evaluating the effects of rapid urbanization on the encroachment of the east Kolkata Wetland ecosystem: a remote sensing and hybrid machine learning approach

    Ismail Mondal, Jatisankar Bandyopadhyay, SK Ariful Hossain +5

    МақолаLand Use and Ecosystem ServicesEnvironment Development and Sustainability20245 иқтибос
    ABI

  3. Coastal vulnerability assessment for the Sundarbans mangrove ecosystem using InVEST and machine learning-based empirical models

    Anirjita Das, Ismail Mondal, SK Ariful Hossain +5

    МақолаAgricultural and Environmental ManagementEnvironment Development and Sustainability20254 иқтибос
    ABI

  4. Assessing cropping system dynamics over three decades: remote sensing and GIS insights in Murshidabad-Jiaganj Block

    Lal Mohammad, Jatisankar Bandyopadhyay, Ismail Mondal +4

    МақолаRemote Sensing in AgricultureEnvironmental Monitoring and Assessment20252 иқтибос
    ABI

  5. Digital economy-driven decarbonization pathways: analyzing how digital economy and globalization impact climate change in the top-10 digital economies

    Muhammad Farhan Bashir, Adeb Qaid, Madiha Bashir +1

    МақолаEnergy, Environment, Economic GrowthFrontiers in Environmental Science20261 иқтибос
    ABI

  6. Spatio-Temporal Assessment of Land Cover Change and Cropping Pattern Variation Using Cloud-Based Earth Observation Analytics

    Lal Mohammad, Jatisankar Bandyopadhyay, Ismail Mondal +3

    МақолаRemote Sensing in AgricultureJournal of the Indian Society of Remote Sensing20260 иқтибос
    ABI