PennyHow/GrIML: GrIML v0.0.1

The GrIML python package A GrIML workflow for classifying water bodies from satellite imagery using a multi-sensor, multi-method approach. This workflow is part of the ESA GrIML project . Quickstart The GrIML package can be installed using pip: pip install griml Or cloned from the Github repository:...

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Main Author: Penny How
Format: Software
Language:unknown
Published: 2022
Subjects:
Online Access:https://zenodo.org/record/6498007
https://doi.org/10.5281/zenodo.6498007
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spelling ftzenodo:oai:zenodo.org:6498007 2023-05-15T16:29:30+02:00 PennyHow/GrIML: GrIML v0.0.1 Penny How 2022-04-27 https://zenodo.org/record/6498007 https://doi.org/10.5281/zenodo.6498007 unknown https://github.com/PennyHow/GrIML/tree/v0.0.1 doi:10.5281/zenodo.6498006 https://zenodo.org/record/6498007 https://doi.org/10.5281/zenodo.6498007 oai:zenodo.org:6498007 info:eu-repo/semantics/openAccess info:eu-repo/semantics/other software 2022 ftzenodo https://doi.org/10.5281/zenodo.649800710.5281/zenodo.6498006 2023-03-10T19:35:01Z The GrIML python package A GrIML workflow for classifying water bodies from satellite imagery using a multi-sensor, multi-method approach. This workflow is part of the ESA GrIML project . Quickstart The GrIML package can be installed using pip: pip install griml Or cloned from the Github repository: git clone https://github.com/PennyHow/GrIML Workflow GrIML builds on the existing workflows from the ESA Glaciers CCI (Option 6, An Inventory of Ice-Marginal Lakes in Greenland), refined here to form a unified processing chain that is shared openly on Github and pip. Cloud processing Primary processing is performed using the Google Earth Engine Python API , including satellite data retrieval and binary classification from multiple sensors. By doing so, the workflow avoids the handling of heavy data downloads and operations. Subject to funding, it is intended to include add-on modules to the workflow, which take advantage of the cloud processing capabilities provided by the SentinelHub APIs . SentinelHub is a cloud processing platform that can be used to retrieve and process data from many satellite products. Offline processing Key Python packages that will be used in the offline components of the workflow: geopandas - for vector dataset handling numpy - for numerical operations pandas - for dataframe handling scipy - for matrix operations shapely - for geometric operations Software Greenland Zenodo Greenland
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
description The GrIML python package A GrIML workflow for classifying water bodies from satellite imagery using a multi-sensor, multi-method approach. This workflow is part of the ESA GrIML project . Quickstart The GrIML package can be installed using pip: pip install griml Or cloned from the Github repository: git clone https://github.com/PennyHow/GrIML Workflow GrIML builds on the existing workflows from the ESA Glaciers CCI (Option 6, An Inventory of Ice-Marginal Lakes in Greenland), refined here to form a unified processing chain that is shared openly on Github and pip. Cloud processing Primary processing is performed using the Google Earth Engine Python API , including satellite data retrieval and binary classification from multiple sensors. By doing so, the workflow avoids the handling of heavy data downloads and operations. Subject to funding, it is intended to include add-on modules to the workflow, which take advantage of the cloud processing capabilities provided by the SentinelHub APIs . SentinelHub is a cloud processing platform that can be used to retrieve and process data from many satellite products. Offline processing Key Python packages that will be used in the offline components of the workflow: geopandas - for vector dataset handling numpy - for numerical operations pandas - for dataframe handling scipy - for matrix operations shapely - for geometric operations
format Software
author Penny How
spellingShingle Penny How
PennyHow/GrIML: GrIML v0.0.1
author_facet Penny How
author_sort Penny How
title PennyHow/GrIML: GrIML v0.0.1
title_short PennyHow/GrIML: GrIML v0.0.1
title_full PennyHow/GrIML: GrIML v0.0.1
title_fullStr PennyHow/GrIML: GrIML v0.0.1
title_full_unstemmed PennyHow/GrIML: GrIML v0.0.1
title_sort pennyhow/griml: griml v0.0.1
publishDate 2022
url https://zenodo.org/record/6498007
https://doi.org/10.5281/zenodo.6498007
geographic Greenland
geographic_facet Greenland
genre Greenland
genre_facet Greenland
op_relation https://github.com/PennyHow/GrIML/tree/v0.0.1
doi:10.5281/zenodo.6498006
https://zenodo.org/record/6498007
https://doi.org/10.5281/zenodo.6498007
oai:zenodo.org:6498007
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.5281/zenodo.649800710.5281/zenodo.6498006
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