Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods

Irrigation expansion is a critical development intervention to address food security challenges in Ethiopia. However, only a fraction of the country’s irrigation potential has been utilized so far. Information about the location and spatial extent of irrigated and rainfed areas is an important requi...

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Autores principales: Chandrasekharan, Kiran M., Subasinghe, Chandima, Haileslassie, Amare
Formato: Artículo preliminar
Lenguaje:Inglés
Publicado: International Water Management Institute 2021
Materias:
Acceso en línea:https://hdl.handle.net/10568/116872
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author Chandrasekharan, Kiran M.
Subasinghe, Chandima
Haileslassie, Amare
author_browse Chandrasekharan, Kiran M.
Haileslassie, Amare
Subasinghe, Chandima
author_facet Chandrasekharan, Kiran M.
Subasinghe, Chandima
Haileslassie, Amare
author_sort Chandrasekharan, Kiran M.
collection Repository of Agricultural Research Outputs (CGSpace)
description Irrigation expansion is a critical development intervention to address food security challenges in Ethiopia. However, only a fraction of the country’s irrigation potential has been utilized so far. Information about the location and spatial extent of irrigated and rainfed areas is an important requirement for sustainable water resources development and agricultural planning. Currently, considerable variations exist in the irrigated area estimates made by different government agencies. In addition, irrigated area maps created as part of global mapping efforts have a spatial resolution of anywhere between 10 kilometers and 250 meters, making them too coarse for planning and management at a subnational scale. This study aims to develop an irrigated area map of Ethiopia using satellite images to support agricultural water management practices in the country, using multi-temporal, multi-resolution data sets from 2015 to 2016 with a spatial resolution of 30 m. The total area of croplands was estimated as 21.8 million hectares (Mha), of which only 1.11 Mha were mapped as the irrigated area. This is only around 5% of the estimated total agricultural area. The accuracy of the results was evaluated using geographic coordinates of irrigated areas provided by the Ethiopian Ministry of Agriculture. The results confirmed that irrigated areas can be identified reasonably well by analyzing seasonal trends in vegetation and moisture levels.
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spelling CGSpace1168722025-11-07T08:02:52Z Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods Chandrasekharan, Kiran M. Subasinghe, Chandima Haileslassie, Amare irrigated farming rainfed agriculture mapping remote sensing irrigated land farmland water management biomass dry season moisture content land cover satellite imagery landsat weather data rainfall patterns datasets normalized difference vegetation index moderate resolution imaging spectroradiometer time series analysis Irrigation expansion is a critical development intervention to address food security challenges in Ethiopia. However, only a fraction of the country’s irrigation potential has been utilized so far. Information about the location and spatial extent of irrigated and rainfed areas is an important requirement for sustainable water resources development and agricultural planning. Currently, considerable variations exist in the irrigated area estimates made by different government agencies. In addition, irrigated area maps created as part of global mapping efforts have a spatial resolution of anywhere between 10 kilometers and 250 meters, making them too coarse for planning and management at a subnational scale. This study aims to develop an irrigated area map of Ethiopia using satellite images to support agricultural water management practices in the country, using multi-temporal, multi-resolution data sets from 2015 to 2016 with a spatial resolution of 30 m. The total area of croplands was estimated as 21.8 million hectares (Mha), of which only 1.11 Mha were mapped as the irrigated area. This is only around 5% of the estimated total agricultural area. The accuracy of the results was evaluated using geographic coordinates of irrigated areas provided by the Ethiopian Ministry of Agriculture. The results confirmed that irrigated areas can be identified reasonably well by analyzing seasonal trends in vegetation and moisture levels. 2021-12-13 2021-12-20T07:31:27Z 2021-12-20T07:31:27Z Working Paper https://hdl.handle.net/10568/116872 en Open Access application/pdf International Water Management Institute Chandrasekharan, Kiran M.; Subasinghe, Chandima; Haileslassie, Amare. 2021. Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods. Colombo, Sri Lanka: International Water Management Institute (IWMI). 31p. (IWMI Working Paper 196) [doi: https://doi.org/10.5337/2021.206]
spellingShingle irrigated farming
rainfed agriculture
mapping
remote sensing
irrigated land
farmland
water management
biomass
dry season
moisture content
land cover
satellite imagery
landsat
weather data
rainfall patterns
datasets
normalized difference vegetation index
moderate resolution imaging spectroradiometer
time series analysis
Chandrasekharan, Kiran M.
Subasinghe, Chandima
Haileslassie, Amare
Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods
title Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods
title_full Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods
title_fullStr Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods
title_full_unstemmed Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods
title_short Mapping irrigated and rainfed agriculture in Ethiopia (2015-2016) using remote sensing methods
title_sort mapping irrigated and rainfed agriculture in ethiopia 2015 2016 using remote sensing methods
topic irrigated farming
rainfed agriculture
mapping
remote sensing
irrigated land
farmland
water management
biomass
dry season
moisture content
land cover
satellite imagery
landsat
weather data
rainfall patterns
datasets
normalized difference vegetation index
moderate resolution imaging spectroradiometer
time series analysis
url https://hdl.handle.net/10568/116872
work_keys_str_mv AT chandrasekharankiranm mappingirrigatedandrainfedagricultureinethiopia20152016usingremotesensingmethods
AT subasinghechandima mappingirrigatedandrainfedagricultureinethiopia20152016usingremotesensingmethods
AT haileslassieamare mappingirrigatedandrainfedagricultureinethiopia20152016usingremotesensingmethods