Ethiopian Crop Type 2020 (EthCT2020) dataset
A detailed description of the EthCT2020 dataset is provided in the journal (Data in Brief) article "Ethiopian Crop Type 2020 (EthCT2020) dataset: Crop type data for environmental and agricultural remote sensing applications in complex Ethiopian smallholder wheat-based farming systems (Meher sea...
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| creator | Blasch, Gerald |
| description | A detailed description of the EthCT2020 dataset is provided in the journal (Data in Brief) article "Ethiopian Crop Type 2020 (EthCT2020) dataset: Crop type data for environmental and agricultural remote sensing applications in complex Ethiopian smallholder wheat-based farming systems (Meher season 2020/21)".
For the 2020/21 main cropping season, the Ethiopian Crop Type 2020 (EthCT2020) dataset compiled from multiple sources provides 2,793 harmonized, quality-controlled, and georeferenced in-situ samples on annual crop types (7 crop groups; 22 crop classes) at smallholder field level across the complex and highly fragmented agricultural landscape of Ethiopia. The focus was on rainfed, wheat-based farming systems.
Sources:
a) Nationwide ground data collection campaign using ODK and GPS (GDCC),
b) Wheat Rust Toolbox, a database for field disease surveillance and monitoring using ODK (WRTB), and
c) CIMMYT farm household survey database (FHSD). |
| doi_str_mv | 10.17632/mfpvmk8cnm.1 |
| format | Dataset |
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For the 2020/21 main cropping season, the Ethiopian Crop Type 2020 (EthCT2020) dataset compiled from multiple sources provides 2,793 harmonized, quality-controlled, and georeferenced in-situ samples on annual crop types (7 crop groups; 22 crop classes) at smallholder field level across the complex and highly fragmented agricultural landscape of Ethiopia. The focus was on rainfed, wheat-based farming systems.
Sources:
a) Nationwide ground data collection campaign using ODK and GPS (GDCC),
b) Wheat Rust Toolbox, a database for field disease surveillance and monitoring using ODK (WRTB), and
c) CIMMYT farm household survey database (FHSD).</description><identifier>DOI: 10.17632/mfpvmk8cnm.1</identifier><language>eng</language><publisher>Mendeley Data</publisher><subject>Agricultural Spatial Modeling ; Agriculture Land Use ; Earth Observation ; Machine Learning ; Monitoring in Agriculture</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0002-8265-0052</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>781,1895</link.rule.ids><linktorsrc>$$Uhttps://commons.datacite.org/doi.org/10.17632/mfpvmk8cnm.1$$EView_record_in_DataCite.org$$FView_record_in_$$GDataCite.org$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Blasch, Gerald</creatorcontrib><title>Ethiopian Crop Type 2020 (EthCT2020) dataset</title><description>A detailed description of the EthCT2020 dataset is provided in the journal (Data in Brief) article "Ethiopian Crop Type 2020 (EthCT2020) dataset: Crop type data for environmental and agricultural remote sensing applications in complex Ethiopian smallholder wheat-based farming systems (Meher season 2020/21)".
For the 2020/21 main cropping season, the Ethiopian Crop Type 2020 (EthCT2020) dataset compiled from multiple sources provides 2,793 harmonized, quality-controlled, and georeferenced in-situ samples on annual crop types (7 crop groups; 22 crop classes) at smallholder field level across the complex and highly fragmented agricultural landscape of Ethiopia. The focus was on rainfed, wheat-based farming systems.
Sources:
a) Nationwide ground data collection campaign using ODK and GPS (GDCC),
b) Wheat Rust Toolbox, a database for field disease surveillance and monitoring using ODK (WRTB), and
c) CIMMYT farm household survey database (FHSD).</description><subject>Agricultural Spatial Modeling</subject><subject>Agriculture Land Use</subject><subject>Earth Observation</subject><subject>Machine Learning</subject><subject>Monitoring in Agriculture</subject><fulltext>true</fulltext><rsrctype>dataset</rsrctype><creationdate>2024</creationdate><recordtype>dataset</recordtype><sourceid>PQ8</sourceid><recordid>eNpjYBA1NNAzNDczNtLPTSsoy822SM7L1TPkZNBxLcnIzC_ITMxTcC7KL1AIqSxIVTAyMDJQ0ADKOIeAmJoKKYklicWpJTwMrGmJOcWpvFCam0HXzTXE2UMXJJ-cWZIaX1CUmZtYVBlvaBAPti0eYVu8oTGp6gElXDgR</recordid><startdate>20240129</startdate><enddate>20240129</enddate><creator>Blasch, Gerald</creator><general>Mendeley Data</general><scope>DYCCY</scope><scope>PQ8</scope><orcidid>https://orcid.org/0000-0002-8265-0052</orcidid></search><sort><creationdate>20240129</creationdate><title>Ethiopian Crop Type 2020 (EthCT2020) dataset</title><author>Blasch, Gerald</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-datacite_primary_10_17632_mfpvmk8cnm_13</frbrgroupid><rsrctype>datasets</rsrctype><prefilter>datasets</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Agricultural Spatial Modeling</topic><topic>Agriculture Land Use</topic><topic>Earth Observation</topic><topic>Machine Learning</topic><topic>Monitoring in Agriculture</topic><toplevel>online_resources</toplevel><creatorcontrib>Blasch, Gerald</creatorcontrib><collection>DataCite (Open Access)</collection><collection>DataCite</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Blasch, Gerald</au><format>book</format><genre>unknown</genre><ristype>DATA</ristype><title>Ethiopian Crop Type 2020 (EthCT2020) dataset</title><date>2024-01-29</date><risdate>2024</risdate><abstract>A detailed description of the EthCT2020 dataset is provided in the journal (Data in Brief) article "Ethiopian Crop Type 2020 (EthCT2020) dataset: Crop type data for environmental and agricultural remote sensing applications in complex Ethiopian smallholder wheat-based farming systems (Meher season 2020/21)".
For the 2020/21 main cropping season, the Ethiopian Crop Type 2020 (EthCT2020) dataset compiled from multiple sources provides 2,793 harmonized, quality-controlled, and georeferenced in-situ samples on annual crop types (7 crop groups; 22 crop classes) at smallholder field level across the complex and highly fragmented agricultural landscape of Ethiopia. The focus was on rainfed, wheat-based farming systems.
Sources:
a) Nationwide ground data collection campaign using ODK and GPS (GDCC),
b) Wheat Rust Toolbox, a database for field disease surveillance and monitoring using ODK (WRTB), and
c) CIMMYT farm household survey database (FHSD).</abstract><pub>Mendeley Data</pub><doi>10.17632/mfpvmk8cnm.1</doi><orcidid>https://orcid.org/0000-0002-8265-0052</orcidid><oa>free_for_read</oa></addata></record> |
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| identifier | DOI: 10.17632/mfpvmk8cnm.1 |
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| language | eng |
| recordid | cdi_datacite_primary_10_17632_mfpvmk8cnm_1 |
| source | DataCite |
| subjects | Agricultural Spatial Modeling Agriculture Land Use Earth Observation Machine Learning Monitoring in Agriculture |
| title | Ethiopian Crop Type 2020 (EthCT2020) dataset |
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