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between 2017 and 2023, developed by [Farmerline](https://farmerline.co/), [Spatial Collective](https://spatialcollective.com/),
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and the [Agricultural Impacts Research Group](https://agroimpacts.info/) at [Clark University](https://www.clarku.edu/), with support from the
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[Lacuna Fund](https://lacunafund.org/) ([Estes et al, 2024](https://arxiv.org/abs/2412.18483); [Wussah et al. (2023)](https://zenodo.org/records/11060871)). This dataset has been
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further supplemented by additional labels collected primarily for
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for 2018 over a subset of countries, which provide an example of their
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application in training and validating a CNN-based cropland mapping model
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[(Khallaghi et al. 2025)](https://www.mdpi.com/2072-4292/17/3/474).
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Documentation: Information on the primary dataset can be found [here](https://github.com/agroimpacts/lacunalabels/).
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Documentation for added labels is available [here](https://github.com/agroimpacts/cnn-generalization-enhancement).
AG-LOAM dataset has been released to facilitate the evaluation of LiDAR-based odometry algorithms in agricultural environments.
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1) It was collected by a wheeled mobile robot at the Agricultural Experimental Station of the University of California, Riverside, during Winter 2022 and Winter 2023.
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2) It provides LiDAR point cloud data captured using a Velodyne VLP-16 sensor, along with ground-truth trajectories obtained from an RTK-GPS system.
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3) It consists of 18 sequences collected over three phases, covering diverse planting environments, terrain conditions, path patterns, and robot motion profiles.
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4) It spans a total operation time of 3 hours, covers a total distance of 7.5 km, and constitutes 150 GB of data.
Copy file name to clipboardexpand all lines: datasets/geoschem-input-data.yaml
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Name: GEOS-Chem Input Data
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Description: Input data for the GEOS-Chem Chemical Transport Model, includes NASA/GMAO MERRA-2 and GEOS-FP [meteorological products](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/input-overview.html#met), [chemistry input data](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/input-overview.html#chemistry-input-data), [emissions input data](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/input-overview.html#emis-inputs), and other smaller datasets such as model [initial conditions](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/input-overview.html#initial-conditions-input-data>).
- Title: "Enabling Immediate Access to Earth Science Models through Cloud Computing: Application to the GEOS-Chem Model"
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AuthorName: Jiawei Zhuang et al.
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- Title: "Improved advection, resolution, performance, and community access in the new generation (version 13) of the high-performance GEOS-Chem global atmospheric chemistry model (GCHP)"
Copy file name to clipboardexpand all lines: datasets/geoschem-nested-input-data.yaml
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Name: GEOS-Chem Nested Input Data
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Description: Input data for nested-grid simulations using the GEOS-Chem Chemical Transport Model. This includes the NASA/GMAO MERRA-2 and GEOS-FP [meteorological products](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/input-overview.html#met), the [HEMCO emission inventories](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/input-overview.html#emis-inputs), and other small data such as [model initial conditions](https://geos-chem.readthedocs.io/en/latest/gcclassic-user-guide/restart-files.html).
Copy file name to clipboardexpand all lines: datasets/noaa-gk2a-pds.yaml
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- meteorological
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- disaster response
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- satellite imagery
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License: NOAA data disseminated through NODD is made available under the [Creative Commons 1.0 Universal Public Domain Dedication (CC0-1.0) license](https://creativecommons.org/publicdomain/zero/1.0/?ref=chooser-v1\), which is well-known and internationally recognized. There are no restrictions on the use of the data. The data are open to the public and can be used as desired. <br/><br/> NOAA has adopted the Creative Commons license to ensure maximum use of our data, to spur and encourage exploration and innovation throughout the industry. This license is applicable to each of the NOAA datasets made available by NODD. NOAA requests attribution for the use or dissemination of unaltered NOAA data. However, it is not permissible to state or imply endorsement by or affiliation with NOAA. If you modify NOAA data, you may not state or imply that it is original, unaltered NOAA data.
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License: Open Data ; Refer to [KMA Site](https://nmsc.kma.go.kr/enhome/html/base/cmm/selectPage.do?page=satellite.gk2a.fact) for more information.
Copy file name to clipboardexpand all lines: datasets/noaa-goes.yaml
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NEW GOES-19 Data!!! GOES-19 products at the Provisional maturity level have begun streaming. Data files will be available between Provisional and the Operational Declaration of the satellite, however, these data are subject to the caveat that they are "GOES-19 Preliminary, Non-Operational Data".
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NEW GOES 16 Reprocess Data!! The reprocessed GOES-16 ABI L1b data mitigates systematic data issues (including data gaps and image artifacts) seen in the Operational products, and improves the stability of both the radiometric and geometric calibration over the course of the entire mission life. These data were produced by recomputing the L1b radiance products from input raw L0 data using improved calibration algorithms and look-up tables, derived from data analysis of the NIST-traceable, on-board sources. In addition, the reprocessed data products contain enhancements to the L1b file format, including limb pixels and pixel timestamps, while maintaining compatibility with the operational products. The datasets currently available span the operational life of GOES-16 ABI, from early 2018 through the end of 2024. The Reprocessed L1b dataset shows improvement over the Operational L1b products but may still contain data gaps or discrepancies. Please provide feedback to Dan Lindsey ([email protected]) and Gary Lin ([email protected]).
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NEW GOES 16 Reprocess Data!! The reprocessed GOES-16 ABI L1b data mitigates systematic data issues (including data gaps and image artifacts) seen in the Operational products, and improves the stability of both the radiometric and geometric calibration over the course of the entire mission life. These data were produced by recomputing the L1b radiance products from input raw L0 data using improved calibration algorithms and look-up tables, derived from data analysis of the NIST-traceable, on-board sources. In addition, the reprocessed data products contain enhancements to the L1b file format, including limb pixels and pixel timestamps, while maintaining compatibility with the operational products. The datasets currently available span the operational life of GOES-16 ABI, from early 2018 through the end of 2024. The Reprocessed L1b dataset shows improvement over the Operational L1b products but may still contain data gaps or discrepancies. Please provide feedback to Dan Lindsey ([email protected]) and Gary Lin ([email protected]). More information can be found in the [GOES-R ABI Reprocess User Guide](https://github.com/NOAA-Big-Data-Program/nodd-data-docs/blob/main/GOES/GOES-R_ABI_Reprocessed_L1b_User_Guide-v1.1.pdf).
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NOTICE: As of January 10th 2023, GOES-18 assumed the GOES-West position and all data files are deemed both operational and provisional, so no ‘preliminary, non-operational’ caveat is needed. GOES-17 is now offline, shifted approximately 105 degree West, where it will be in on-orbit storage. GOES-17 data will no longer flow into the GOES-17 bucket. Operational GOES-West products can be found in the GOES-18 bucket.
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