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From national to global: Mapping global center-pivot irrigated cropland with knowledge-guided data augmentation

https://doi.org/10.2139/ssrn.6210413
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Annual Irrigation Dynamics in the U.S. Northern High Plains Derived from Landsat Satellite Data
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Center Pivot Irrigation Systems
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WHYMAP and the Groundwater Resources Map of the World 1:25,000,000
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Environmental impacts of groundwater overdraft: selected case studies in the southwestern United States
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Development of soil moisture indices from differences in water absorption between shortwave-infrared bands
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Center pivot field delineation and mapping: A satellite-driven object-based image analysis approach for national scale accounting
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Seamless and automated rapeseed mapping for large cloudy regions using time-series optical satellite imagery
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Mapping three decades of annual irrigation across the US High Plains Aquifer using Landsat and Google Earth Engine
inferredcites →https://doi.org/10.1016/j.rse.2023.113760openalex-snapshot
Mapping center pivot irrigation systems in global arid regions using instance segmentation and analyzing their spatial relationship with freshwater resources
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NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space
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A comparison of vegetation indices over a global set of TM images for EOS-MODIS
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High-resolution mapping of global surface water and its long-term changes
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Version 3 of the Global Aridity Index and Potential Evapotranspiration Database
inferredcites →https://doi.org/10.1038/s41598-024-75323-2openalex-snapshot
Dike-induced aquifer models derived from high-resolution multi-spectral satellite imagery
inferredcites →https://doi.org/10.1038/sdata.2015.66openalex-snapshot
The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes
inferredcites →https://doi.org/10.1073/pnas.1200311109openalex-snapshot
Groundwater depletion and sustainability of irrigation in the US High Plains and Central Valley
inferredcites →https://doi.org/10.1080/15481603.2023.2165256openalex-snapshot
A shape-attention Pivot-Net for identifying central pivot irrigation systems from satellite images using a cloud computing platform: an application in the contiguous US
inferredcites →https://doi.org/10.1109/jstars.2021.3104726openalex-snapshot
Dealing With Clouds and Seasonal Changes for Center Pivot Irrigation Systems Detection Using Instance Segmentation in Sentinel-2 Time Series
inferredcites →https://doi.org/10.1109/mgrs.2025.3628194openalex-snapshot
PANGAEA: Assessing Geospatial Foundation Models Capabilities through a Global and Inclusive Benchmark
inferredcites →https://doi.org/10.1109/tgrs.2024.3352662openalex-snapshot
SOSSF: Landsat-8 Image Synthesis on the Blending of Sentinel-1 and MODIS Data
inferredcites →https://doi.org/10.1109/tnnls.2022.3152527openalex-snapshot
Learning From Noisy Labels With Deep Neural Networks: A Survey
inferredcites →https://doi.org/10.1111/gcb.13298openalex-snapshot
Land‐use change affects water recycling in Brazil's last agricultural frontier
inferredcites →https://doi.org/10.1126/sciadv.aaz6031openalex-snapshot
Global agricultural economic water scarcity
inferredcites →https://doi.org/10.1126/science.1244693openalex-snapshot
High-Resolution Global Maps of 21st-Century Forest Cover Change
inferredcites →https://doi.org/10.1186/s40537-021-00444-8openalex-snapshot
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
inferredcites →https://doi.org/10.13031/aea.14693openalex-snapshot
A Geographical Survey of Center Pivot Irrigation Systems in the Central and Southern High Plains Aquifer Region of the United States
inferredcites →https://doi.org/10.3390/agriculture8100147openalex-snapshot
Automatic Identification of Center Pivot Irrigation Systems from Landsat Images Using Convolutional Neural Networks
inferredcites →https://doi.org/10.3390/rs12030558openalex-snapshot
Automatic Mapping of Center Pivot Irrigation Systems from Satellite Images Using Deep Learning
inferredcites →https://doi.org/10.5194/essd-16-5449-2024openalex-snapshot
Global 30 m seamless data cube (2000–2022) of land surface reflectance generated from Landsat 5, 7, 8, and 9 and MODIS Terra constellations
inferredcites →https://doi.org/10.5194/essd-17-855-2025openalex-snapshot
GMIE: a global maximum irrigation extent and central pivot irrigation system dataset derived via irrigation performance during drought stress and deep learning methods
inferredcites →https://doi.org/10.5194/soil-6-565-2020openalex-snapshot
The influence of training sample size on the accuracy of deep learning models for the prediction of soil properties with near-infrared spectroscopy data
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