Matches in SemOpenAlex for { <https://semopenalex.org/work/W2997448596> ?p ?o ?g. }
Showing items 1 to 56 of
56
with 100 items per page.
- W2997448596 abstract "Timely and accurate agricultural impact assessments for droughts are critical for designing appropriate interventions and policy. These assessments are often ad hoc, late, or spatially imprecise, with reporting at the zonal or regional level. This is problematic as we find substantial variability in losses at the village-level, which is missing when reporting at the zonal level. In this paper, we propose a new data fusion method—combining remotely sensed data with agricultural survey data—that might address these limitations. We apply the method to Ethiopia, which is regularly hit by droughts and is a substantial recipient of ad hoc imported food aid. We then utilize remotely sensed data obtained near mid-season to predict substantial crop losses of greater than or equal to 25% due to drought at the village level for five primary cereal crops. We train machine learning models to predict the likelihood of losses and explore the most influential variables. On independent samples, the models identify substantial drought loss cases with up to 81% accuracy by mid- to late-September. We believe the proposed models could be used to help monitor and predict yields for disaster response teams and policy makers, particularly with further development of the models and integration of soon-to-be available high-resolution, remotely sensed data such as the Harmonized Landsat Sentinel (HLS) data set." @default.
- W2997448596 created "2020-01-10" @default.
- W2997448596 creator A5017273011 @default.
- W2997448596 creator A5037577894 @default.
- W2997448596 creator A5087525754 @default.
- W2997448596 date "2018-12-01" @default.
- W2997448596 modified "2023-09-23" @default.
- W2997448596 title "Predicting High-Magnitude, Low-Frequency Crop Losses Using Machine Learning: An application to cereal crops in Ethiopia" @default.
- W2997448596 hasPublicationYear "2018" @default.
- W2997448596 type Work @default.
- W2997448596 sameAs 2997448596 @default.
- W2997448596 citedByCount "0" @default.
- W2997448596 crossrefType "journal-article" @default.
- W2997448596 hasAuthorship W2997448596A5017273011 @default.
- W2997448596 hasAuthorship W2997448596A5037577894 @default.
- W2997448596 hasAuthorship W2997448596A5087525754 @default.
- W2997448596 hasConcept C118518473 @default.
- W2997448596 hasConcept C119857082 @default.
- W2997448596 hasConcept C166957645 @default.
- W2997448596 hasConcept C205649164 @default.
- W2997448596 hasConcept C39432304 @default.
- W2997448596 hasConcept C41008148 @default.
- W2997448596 hasConceptScore W2997448596C118518473 @default.
- W2997448596 hasConceptScore W2997448596C119857082 @default.
- W2997448596 hasConceptScore W2997448596C166957645 @default.
- W2997448596 hasConceptScore W2997448596C205649164 @default.
- W2997448596 hasConceptScore W2997448596C39432304 @default.
- W2997448596 hasConceptScore W2997448596C41008148 @default.
- W2997448596 hasLocation W29974485961 @default.
- W2997448596 hasOpenAccess W2997448596 @default.
- W2997448596 hasPrimaryLocation W29974485961 @default.
- W2997448596 hasRelatedWork W103273443 @default.
- W2997448596 hasRelatedWork W1499549875 @default.
- W2997448596 hasRelatedWork W1997165048 @default.
- W2997448596 hasRelatedWork W2098011085 @default.
- W2997448596 hasRelatedWork W2123607173 @default.
- W2997448596 hasRelatedWork W2134583017 @default.
- W2997448596 hasRelatedWork W2165588550 @default.
- W2997448596 hasRelatedWork W2172213450 @default.
- W2997448596 hasRelatedWork W2185144032 @default.
- W2997448596 hasRelatedWork W2904994916 @default.
- W2997448596 hasRelatedWork W2940449802 @default.
- W2997448596 hasRelatedWork W3008552732 @default.
- W2997448596 hasRelatedWork W3020380966 @default.
- W2997448596 hasRelatedWork W3040573749 @default.
- W2997448596 hasRelatedWork W3048727648 @default.
- W2997448596 hasRelatedWork W3122287636 @default.
- W2997448596 hasRelatedWork W3128997621 @default.
- W2997448596 hasRelatedWork W3158874710 @default.
- W2997448596 hasRelatedWork W909715093 @default.
- W2997448596 hasRelatedWork W2183303098 @default.
- W2997448596 hasVolume "2018" @default.
- W2997448596 isParatext "false" @default.
- W2997448596 isRetracted "false" @default.
- W2997448596 magId "2997448596" @default.
- W2997448596 workType "article" @default.