hyperspectral-soilmoisture-dataset
Hyperspectral and soil-moisture data from a field campaign based on a soil sample. Karlsruhe (Germany), 2017.
https://github.com/felixriese/hyperspectral-soilmoisture-dataset
Science Score: 77.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 13 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
✓Committers with academic emails
1 of 2 committers (50.0%) from academic institutions -
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (8.0%) to scientific vocabulary
Keywords
Repository
Hyperspectral and soil-moisture data from a field campaign based on a soil sample. Karlsruhe (Germany), 2017.
Basic Info
- Host: GitHub
- Owner: felixriese
- License: cc-by-4.0
- Language: Jupyter Notebook
- Default Branch: master
- Homepage: https://doi.org/10.5281/zenodo.1227837
- Size: 737 KB
Statistics
- Stars: 48
- Watchers: 2
- Forks: 13
- Open Issues: 0
- Releases: 4
Topics
Metadata Files
README.md
Hyperspectral benchmark dataset on soil moisture
Hyperspectral and soil-moisture data from a lysimeter field campaign based on a soil sample. Karlsruhe (Germany), 2017.
Abbreviation: KarLy (Karlsruhe Lysimeter)
License: CC BY 4.0
Authors:
Affiliation: Karlsruhe Institute of Technology, Institute of Photogrammetry and Remote Sensing (Link)
Citation: see Citation and bibliography.bib.
Example script: example.ipynb
Description
This dataset was measured in a five-day field campaign in May 2017 in Karlsruhe, Germany. An undisturbed soil sample is the centerpiece of the measurement setup. The soil sample consists of bare soil without any vegetation and was taken in the area near Waldbronn, Germany.
The following sensors were deployed:
- Cubert UHD 285 hyperspectral snapshot camera recording 50 by 50 images with 125 spectral bands ranging from 450 nm to 950 nm and a spectral resolution of 4 nm.
- TRIME-PICO time-domain reflectometry (TDR) sensor in a depth of 2 cm measuring the soil moisture in percent.
The raw sensor data was processed with the Hyperspectral Processing Scripts for the HydReSGeo Dataset beforehand.
Variables
- datetime: date and time (CEST) of the measurement
- soil_moisture: soil moisture in %
- soil_temperature: soil temperature in °C
- 454, 458, … 946, 950: hyperspectral bands in nm
Citation
The bibtex file including both references is available in bibliography.bib.
Paper
Felix M. Riese and Sina Keller, “Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data,” in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 2018, pp. 6151-6154. (Link)
@inproceedings{riese2018introducing,
author = {Riese, Felix~M. and Keller, Sina},
title = {{Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data}},
booktitle = {IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium},
year = {2018},
month = {July},
address = {Valencia, Spain},
doi = {10.1109/IGARSS.2018.8517812},
ISSN = {2153-7003},
pages = {6151--6154},
}
Code
Felix M. Riese and Sina Keller, "Hyperspectral benchmark dataset on soil moisture", Dataset, Zenodo, 2018. (Link)
@misc{riesekeller2018,
author = {Riese, Felix~M. and Keller, Sina},
title = {Hyperspectral benchmark dataset on soil moisture},
year = {2018},
DOI = {10.5281/zenodo.1227837},
publisher = {Zenodo},
howpublished = {\href{https://doi.org/10.5281/zenodo.1227837}{doi.org/10.5281/zenodo.1227837}}
}
Owner
- Name: Dr. Felix Riese
- Login: felixriese
- Kind: user
- Location: Munich, Germany
- Company: @Peter-Park-Systems-GmbH
- Website: felixriese.de
- Repositories: 17
- Profile: https://github.com/felixriese
Ph.D. & MBA | Head of Product | Physicist with 9+ Years in Data Science and Machine Learning | First-Principles Thinking
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite both the article from preferred-citation and the software itself."
authors:
- family-names: Riese
given-names: Felix M.
orcid: https://orcid.org/0000-0003-0596-9585
- family-names: Keller
given-names: Sina
orcid: https://orcid.org/0000-0002-7710-5316
title: "Hyperspectral benchmark dataset on soil moisture"
version: 1.0.3
doi: "10.5281/zenodo.1227837"
date-released: 2019-01-03
repository-code: https://github.com/felixriese/hyperspectral-soilmoisture-dataset
license: BSD-3-Clause
preferred-citation:
authors:
- family-names: Riese
given-names: Felix M.
- family-names: Keller
given-names: Sina
title: "Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data"
collection-title: "IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium"
collection-type: proceedings
conference:
name: "IGARSS 2018"
year: 2018
doi: "10.1109/IGARSS.2018.8517812"
start: 6151
end: 6154
GitHub Events
Total
- Watch event: 3
- Fork event: 1
Last Year
- Watch event: 3
- Fork event: 1
Committers
Last synced: 7 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Felix M. Riese | f****e@k****u | 10 |
| Felix M. Riese | m****l@f****e | 7 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
- Total downloads: unknown
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 4
proxy.golang.org: github.com/felixriese/hyperspectral-soilmoisture-dataset
- Documentation: https://pkg.go.dev/github.com/felixriese/hyperspectral-soilmoisture-dataset#section-documentation
- License: cc-by-4.0
-
Latest release: v1.0.3
published about 7 years ago
Rankings
Dependencies
- matplotlib
- numpy
- pandas
- scikit-learn