cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17872056
title: YOLOv8-Detected Gravity Wave Event Catalog from VIIRS Day-Night Band Imagery (NOAA-21, 2023–2024)

description: This dataset contains gravity wave event lists detected by a YOLOv8 machine-learning model applied to VIIRS Day/Night Band (DNB) imagery acquired by the NOAA-21 satellite from 2023 to 2024.

 

The detailed methodology is described in a manuscript being prepared for submission to Journal of Geophysical Research: Machine Learning and Computation:

Yuta Hozumi, Jia Yue, Seraj Al Mahmud Mostafa, Chenxi Wang, Jianwu Wang, Sanjay Purushotham, and Steven D. Miller,

“Localization and Classification of Gravity Wave Events from VIIRS Day/Night Band Satellite Imagery Using Machine Learning Techniques.”

 

Dataset 1: wave_event_VJ202DNB.csv

This file provides the catalog of detected wave events in CSV format. The event list is the result of a survey of moonless NOAA-21 VIIRS/DNB images from 2023 to 2024 using the trained YOLOv8 model.

 

The columns are:

1. Satellite name.

2–3. Intensity and geolocation data file names, respectively. The original data files can be downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5201/VJ202DNB/ and https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5201/VJ203DNB/.

4. Observation time of the granule in UTC. The format is “YYYY-MM-DD hh:mm:ss,” where YYYY, MM, DD, hh, mm, and ss denote year, month, day, hour, minute, and second, respectively.

5. Total number of detected objects in the granule.

6. Object index within the granule.

7–8. Class ID and class name of the detected wave event, respectively. The class IDs are: 0 for concentric gravity waves (cgw), 1 for frontal waves, 2 for ripples, and 3 for other gravity waves (gw).

9. Detection confidence score, ranging from 0.3 to 1.0.

10–13. Normalized coordinates of the center of the bounding box (x_center, y_center), followed by the normalized width and height of the bounding box.

14–15. Latitude and longitude of the center of the bounding box.

16–23. Latitudes and longitudes of the four corners of the bounding box.

 

Dataset 2: YYYYMM.zip

Monthly zip archives of DNB images with detected wave events annotated by bounding boxes. 

 

Dataset 3: map_figs.zip

Monthly global maps of detected wave events for each wave class.
DOI: 10.5281/zenodo.17872057
title: YOLOv8-Detected Gravity Wave Event Catalog from VIIRS Day-Night Band Imagery (NOAA-21, 2023–2024)

description: This dataset contains gravity wave event lists detected by a YOLOv8 machine-learning model applied to VIIRS Day/Night Band (DNB) imagery acquired by the NOAA-21 satellite from 2023 to 2024.

 

The detailed methodology is described in a manuscript being prepared for submission to Journal of Geophysical Research: Machine Learning and Computation:

Yuta Hozumi, Jia Yue, Seraj Al Mahmud Mostafa, Chenxi Wang, Jianwu Wang, Sanjay Purushotham, and Steven D. Miller,

“Localization and Classification of Gravity Wave Events from VIIRS Day/Night Band Satellite Imagery Using Machine Learning Techniques.”

 

Dataset 1: wave_event_VJ202DNB.csv

This file provides the catalog of detected wave events in CSV format. The event list is the result of a survey of moonless NOAA-21 VIIRS/DNB images from 2023 to 2024 using the trained YOLOv8 model.

 

The columns are:

1. Satellite name.

2–3. Intensity and geolocation data file names, respectively. The original data files can be downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5201/VJ202DNB/ and https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/5201/VJ203DNB/.

4. Observation time of the granule in UTC. The format is “YYYY-MM-DD hh:mm:ss,” where YYYY, MM, DD, hh, mm, and ss denote year, month, day, hour, minute, and second, respectively.

5. Total number of detected objects in the granule.

6. Object index within the granule.

7–8. Class ID and class name of the detected wave event, respectively. The class IDs are: 0 for concentric gravity waves (cgw), 1 for frontal waves, 2 for ripples, and 3 for other gravity waves (gw).

9. Detection confidence score, ranging from 0.3 to 1.0.

10–13. Normalized coordinates of the center of the bounding box (x_center, y_center), followed by the normalized width and height of the bounding box.

14–15. Latitude and longitude of the center of the bounding box.

16–23. Latitudes and longitudes of the four corners of the bounding box.

 

Dataset 2: YYYYMM.zip

Monthly zip archives of DNB images with detected wave events annotated by bounding boxes. 

 

Dataset 3: map_figs.zip

Monthly global maps of detected wave events for each wave class.
DOI: 10.4211/hs.dfa02b83bbde4ae3888ffafeb4446a5bcrossrefsubmissionstatus.pending
title: NHG Synthetic Forecast generation dataset

description: Pre-processed subset of raw HEFS hindcast data for New Hogan lake (NHG) configured for compatibility with the repository structure of the versions 1 and 2 synthetic forecast model contained here: https://github.com/zpb4/Synthetic-Forecast-v1-FIRO-DISES  and here: https://github.com/zpb4/Synthetic-Forecast-v2-FIRO-DISES. The data are pre-structured for the repository setup and instructions are included in README files for both GitHub repos on how to setup the data contained in this resource.

Contains HEFS hindcast .csv files and observed full-natural-flow files for the following sites:
NHGC1 - main reservoir inflow to New Hogan lake
MSGC1L - downstream local flows from Mud Slough 

Data also contains R scripts used to preprocess the raw HEFS data contained in the associated public Hydroshare resource here: https://www.hydroshare.org/resource/f63ead2d62414940a7d90acdc234a5d1/
DOI: 10.4211/hs.05a0490e971f491fa64c62cbde499a6acrossrefsubmissionstatus.pending
title: "Landscape controls on water availability limit revegetation after artisanal gold mining in the Peruvian Amazon" (Atwood et al. 2025)datasets

description: Deforestation from artisanal and small-scale gold mining is transforming large regions of the tropics, from lush rainforest to barren collections of tailings and ponds. Natural forest regeneration is slow due to dramatic soil changes and existing reforestation strategies are failing. Here we combine remote sensing, electrical resistivity imaging, and measurements of soil properties to characterize post-mining areas in the Madre de Dios region, Peru. We find that the post-mining landscape has dramatically changed water infiltration dynamics, driving decreases in subsurface water availability and presenting a major barrier to revegetation. Mining tailings are extremely hydraulically conductive, allowing for 14.7 m/day infiltration relative to 0.074 m/day in primary forest soils, leading to lower average soil moisture and extreme temperatures (<60C). Electrical resistivity imaging reveals a highly resistive, 1.5-2m deep layer of dry sand across the mining landscape. Areas close to the water table (e.g. pond edges) show higher soil moisture, lower temperatures, and greater natural regeneration compared to elevated tailings. Our results suggest that access to water should be prioritized when targeting reforestation sites, potentially requiring large-scale geomorphological reconfiguration. As gold mining is expected to expand, responsible practices and remediation strategies must account for the critical yet often overlooked role of water.
DOI: 10.4211/hs.8230f8e442f047379f3c8cb2b87bdb2a
title: Testing Resource for Testing Published Purposes Only!!!!!!!

description: Testing Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes OnlyTesting Resource for Testing Published Purposes Only for testing duplicate entries.
DOI: 10.18126/x0xf-9q27
title: Front Speed Measurements of the Frontal Polymerization of Cyclooctadiene/Grubbs Catalyst M202/Tributyl Phosphite Resins
DOI: 10.4211/hs.e51d9821c8d84682b642eb0818ac3137crossrefsubmissionstatus.pending
title: LAM Synthetic Forecast Generation Dataset

description: Pre-processed subset of raw HEFS hindcast data for Lake Mendocino (LAM) configured for compatibility with the repository structure of the versions 1 and 2 synthetic forecast model contained here: https://github.com/zpb4/Synthetic-Forecast-v1-FIRO-DISES  and here: https://github.com/zpb4/Synthetic-Forecast-v2-FIRO-DISES. The data are pre-structured for the repository setup and instructions are included in README files for both GitHub repos on how to setup the data contained in this resource.

Contains HEFS hindcast .csv files and observed full-natural-flow files for the following sites:
LAMC1 - main reservoir inflow to Lake Mendocino
UKAC1 - downstream flows at Ukiah junction
HOPC1L - downstream local flows at Hopland junction

Data also contains R scripts used to preprocess the raw HEFS data contained in the associated public Hydroshare resource here: https://www.hydroshare.org/resource/ccffddde118f4145854c960295f520cb/
DOI: 10.4211/hs.64ea6734e97647c1ab34d169424b2896
title: Hello From JupyterHub
DOI: 10.4211/hs.9612dfd6a50c4a9194d9ed7e8956f555
title: Model files for PyTOPKAPI simulation of SantaCruzdemo
DOI: 10.4211/hs.b6c9d06b471043699b5cecbbfa292909
title: resource generated on www1 with a long title
DOI: 10.4211/hs.b6788237717c41e0bcc69bcaa851694fcrossrefsubmissionstatus.pending
title: ADO Synthetic Forecast Generation Dataset

description: Pre-processed subset of raw HEFS hindcast data for Prado Dam system (ADO) configured for compatibility with the repository structure of the versions 1 and 2 synthetic forecast model contained here: https://github.com/zpb4/Synthetic-Forecast-v1-FIRO-DISES  and here: https://github.com/zpb4/Synthetic-Forecast-v2-FIRO-DISES. The data are pre-structured for the repository setup and instructions are included in README files for both GitHub repos on how to setup the data contained in this resource.

Contains HEFS hindcast .csv files and observed full-natural-flow files for the following sites:
ADOC1 - main reservoir inflow to Prado Dam (ADOC1)

Data also contains R scripts used to preprocess the raw HEFS data contained in the associated public Hydroshare resource here: https://www.hydroshare.org/resource/3b665049965c4a2b88f6f6c1abb0ff94/
DOI: 10.25574/30495
title: Chandra X-ray Observatory ObsId 30495

description: Studying the Si K-edge of Cygnus X-2
DOI: 10.4211/hs.bd3452a1b6134428b37915ca03d4c29d
title: TW Daniels Experimental Forest (TWDEF) Lidar
DOI: 10.4211/hs.a9509a59540c470cb9888ccab662a363
title: TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL.

description: TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. TEST PUBLICATION EMAIL. Modified
DOI: 10.4211/hs.9ce349208f4f452b83e0b719803bd260
title: TEST Hydrodynamics control nitrous oxide production in eutrophic coastal permeable sediments

description: This is the raw data from the paper with the same title published in JGR Biogeosciences by Fowdar et al, 2024.  The data includes experimental results, model outputs and wave data used in the model simulations.  The File 'N2O experimental data' contains the data from flow through reactor experiments as described in the linked publication in Figure 1.  The file 'model outputs' give the data from the model outputs shown in Figures 2 and 3.  The file 'Werribee wave data' shows the Wave Data used in the model and was sourced from https://vicwaves.com.au.
DOI: 10.25574/30532
title: Chandra X-ray Observatory ObsId 30532

description: Studying the Si K-edge of Cygnus X-2
DOI: 10.4211/hs.0c6519de865c4ce78c28c9fae54b82c8
title: Model files for PyTOPKAPI simulation of Plungedemo
DOI: 10.4211/hs.eeb83411f7ed401db7d018a60cfc3a79
title: HAND
DOI: 10.4211/hs.9bb283fb474a48ff91de9a417ad62c91
title: CUSTOM LICENSE publication test -- testing deposit to Crossref with no URL

description: License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test. License publication test.
DOI: 10.25574/30533
title: Chandra X-ray Observatory ObsId 30533

description: Studying the Si K-edge of Cygnus X-2
DOI: 10.4211/hs.61dbf283189c457185ea16bc629d9db4
title: Water Point Data Exchange global dataset failures, joined to original data
DOI: 10.4211/hs.b314bb2c089744a8bc0dca01a31c9ee8
title: Data supporting the geomorphology of the Humadal Creek, Doña Juana Volcanic Complex, Colombia
DOI: 10.4211/hs.1696a3a949a84c26957ffcf24a57d1fd
title: Publication
DOI: 10.25574/30534
title: Chandra X-ray Observatory ObsId 30534

description: Studying the Si K-edge of Cygnus X-2
DOI: 10.4211/hs.d08b5e45c1b8426aabcf90fb9ad128ed
title: R scripts for joint return period estimations
DOI: 10.4211/hs.2e0821c5140b4e34a93486aec90fee7c
title: HEC-HMS Modeling for Ruckersville Watershed
DOI: 10.4211/hs.cb1e4d52b44f4d9ab1187162456ba04ccrossrefsubmissionstatus.pending
title: Effects of future increases in tidal flooding on salinity and groundwater dynamics in coastal aquifers

description: This resource contains the data required to reproduce the results of Heiss et al. (2022).

Heiss, J. W., Mase, B., & Shen, C. (2022). Effects of Future Increases in Tidal Flooding on Salinity and Groundwater Dynamics in Coastal Aquifers. Water Resources Research, 58. https://doi.org/10.1029/2022WR033195
DOI: 10.4211/hs.b7c64d75870b41ebbf99c31683c7863f
title: How You Can Avail The Benefits Of Alaska Airlines frequent Flyer Program?
DOI: 10.4211/hs.55b8cfd3b133425689b2f7edae3abcff
title: Main Judi Slot Shopeepay 5000 Tanpa Potongan Besar Super Hoki dan Cuan Terbaru 2022 &gt; Rajabola

description: Main Judi Slot Shopeepay 5000 Tanpa Potongan Besar Super Hoki dan Cuan Terbaru 2022 > Rajabola, tentunya kalian pasti mau menemukan keberuntungan dalam setiap permainan yang disediakan oleh agen Slot Deposit Shopeepay yakni Rajabola. Akan ada banyak keseruan yang dapat kalian rasakan bila berhasil bergabung bersama agen permainan ini. Karena kalian hanya akan membutuhkan 3 langkah mudah untuk dapat mulai bermain di situs Rajabola.
DOI: 10.4211/hs.fd7af4fbf5444a2e828fa5e837da752ccrossrefsubmissionstatus.pending
title: Data for "Contact Angle Impacts on Multiphase Displacement in Fractured Porous Media: A Microfluidic Study"

description: Multiphase displacement in fractured porous media is critical for various subsurface processes. Recent studies have demonstrated the significant role of contact angle in determining displacement regimes in homogenous porous media, yet the understanding of its impacts on flow in fractured porous media remains insufficient. We conduct microfluidics experiments to study the combined impacts of contact angle, fracture aperture, and capillary number on displacement patterns in fractured micromodels. Results show transitions from matrix-preferential flow to fracture-preferential flow and finally to fracture flow even when contact angles are much smaller than 90. Aperture-dependent phase diagrams are proposed to predict the displacement patterns at varying capillary numbers and contact angles. Pore-scale observations suggest that the transition of flow regimes is controlled by pore-scale mechanisms which constrain the crossflow from the fracture to the matrix. This study provides physical insights on incorporating contact angle into the prediction of flow in complex fractured porous media.
DOI: 10.4211/hs.4b2e130625464232bd3a58c886eb8fc6
title: Input-files for TOPNET model of topnet_demo
DOI: 10.4211/hs.4b455c9ac1864e1ba7a3bc90e91e8e0ecrossrefsubmissionstatus.pending
title: Parameters of multi-linear regressions for reconstructing peak flow in Contiguous United States (CONUS)

description: This dataset contains multi-regressions for 672 gauges across Contiguous United States (CONUS) to extend the peak dataset for enhanced Flood Frequency Analysis (FFA).

Flooding is a recurrent natural disaster causing substantial damage and casualties worldwide. A critical task to prevent and mitigate the negative impacts of these natural hazards is to characterize the frequency of flood peaks – a process known as flood frequency analysis (FFA). However, the short records of peak flow observations often limit the FFA accuracy. Here, we developed a statistical method to expand peak flow records at 672 undisturbed gauges across the United States using observations of daily mean flow, available over relatively long periods. We also quantified how FFA reliability improves by adding these expanded datasets of peak flows. This work provides datasets and benchmarks for increasing FFA accuracy, which are helpful for practitioners and government agencies responsible for flood mitigation, infrastructure design, and water management in the United States.
DOI: 10.4211/hs.e8fca21817964efc87314ac01660c227
title: On-Road Tailpipe Characterization of Exhaust Ammonia Emissions from in-use Light-Duty Gasoline Motor Vehicles
DOI: 10.15468/dl.9h6b2t
title: Occurrence Download

description: A dataset containing 133 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Machine Observation, Human Observation, Occurrence evidence)",
 "GadmGid is IDN.7_1",
 "TaxonKey is Mammalia"
 ]
}

 The dataset includes 133 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050038-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4211/hs.a2ffdd737c5046babb80069af72be817
title: Six Hydrology Basics Every Homeowner Should Know
DOI: 10.4211/hs.99f3b6362d4b4549b0902464623124b1
title: Cheap Flights
DOI: 10.4211/hs.24668d4c588743d8a5691766e4319365
title: Test Pequea 4
DOI: 10.4211/hs.c40d9567678740dab868f35440a69b30
title: Charlie's Test Resource
DOI: 10.4211/hs.9ab39f00a04d48c49359bd9cdf8b2b2e
title: A blog about Frontier Airlines kidzone
DOI: 10.4211/hs.d5738711343a46d190f7e43e02e3683a
title: How to reset Hotmail password
DOI: 10.4211/hs.1156a5746415457290e90db23cabafe1
title: Test Publication
DOI: 10.4211/hs.6f1a21204ee045bc86e59d856918b137
title: Sandia Mountains 10K Site
DOI: 10.4211/hs.4058253204f44d5680ccd7f7ae4b1fdecrossrefsubmissionstatus.pending
title: Sources of organic matter to salt marshes: Insights from Oregon, USA

description: Salt marshes are important blue carbon sinks; however, identification of the drivers of carbon burial rates is challenging because estuaries sit at terrestrial and marine interfaces. Here, we address the questions: what are the sources of organic matter (OM) sequestered in Oregon salt marshes, and how do sources change through time? We characterized down-core sediment biogeochemistry (C:N, δ13C, δ15N) for the last century in seven Oregon high marshes and used a mixing model to elucidate differences in OM sources across estuaries and through time. Autochthonous biomass production consistently accounted for half of overall OM accumulation, and the remainder was allochthonous, originating from a combination of estuarine and terrestrial sources. Salt marshes with high sediment loads buried more terrestrial OM, whereas those with low loads and substantial subtidal habitat buried more estuarine-derived OM. When assessed through depth/time, stable isotope trends indicated that decomposition is not the major control. Instead, OM became increasingly more terrestrial in recent decades, especially in salt marshes with low fluvial loads. We hypothesize that salt marshes with low loads took longer to regain lost elevation following coseismic subsidence of the 1700 Cascadia earthquake than salt marshes with higher loads. This result magnifies the role of river floods in sediment and carbon accumulation on the marsh surface. Ultimately, the highest carbon burial rates coincided with highest fractions of terrestrially-sourced OM, though spatiotemporal complexities obscured any potentially significant trends. While the term “blue” typically excludes allochthonous carbon, salt marshes still perform the important ecosystem function of burying OM.