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ENTITY Normalized Difference Vegetation Index

Normalized Difference Vegetation Index

PulseAugur coverage of Normalized Difference Vegetation Index — every cluster mentioning Normalized Difference Vegetation Index across labs, papers, and developer communities, ranked by signal.

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RECENT · PAGE 1/1 · 7 TOTAL
  1. TOOL · CL_121176 ·

    Study links urbanization and land cover to bird diversity in Sri Lanka

    A new study published on arXiv analyzes bird diversity in Sri Lanka, integrating spatial, temporal, and environmental data to understand the factors influencing species richness. The research combined bird observation r…

  2. TOOL · CL_111811 ·

    New UAV dataset captures Indian paddy crop growth stages

    Researchers have released a comprehensive dataset of multispectral and RGB images captured by a UAV over Indian paddy fields. This dataset covers all growth stages of the crop, from nursery to harvest, and includes high…

  3. RESEARCH · CL_111570 ·

    New EO-WM model improves Earth observation forecasting with physics-informed AI · 3 sources tracked

    Researchers have developed EO-WM, a novel video diffusion transformer designed for probabilistic Earth Observation forecasting. This model incorporates a physically informed conditioning framework to better represent me…

  4. RESEARCH · CL_72592 ·

    GMBFormer improves urban green-space extraction with NDVI-guided memory bank

    Researchers have developed GMBFormer, a new Transformer-based framework designed to improve the extraction of urban green spaces from ultra-high-resolution imagery. This model utilizes Normalized Difference Vegetation I…

  5. RESEARCH · CL_72594 ·

    Deep learning frameworks compared for rice disease mapping

    Researchers compared various deep learning frameworks for mapping rice disease severity using UAV multispectral imagery. The study evaluated architectures like U-Net, U-Net++, DeepLabV3+, and SegFormer, testing them wit…

  6. TOOL · CL_22105 ·

    AI model forecasts vegetation health from sparse satellite data

    Researchers have developed a new probabilistic forecasting framework to predict vegetation dynamics using sparse satellite data and weather information. This approach addresses challenges posed by irregular satellite sa…

  7. RESEARCH · CL_06819 ·

    Machine learning model maps soil salinity in Bangladesh

    Researchers have developed a machine-learning framework to map and predict soil salinity in Satkhira, Bangladesh, using field data and satellite imagery. An Extreme Gradient Boosting model, trained on 205 soil samples, …