Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine (English)

To overcome the constraints for policy and practice posed by limited availability of data on crop rotation, this paper applies machine learning to freely available satellite imagery to identify the rotational practices of more than 7,000 villages in Ukraine. Rotation effects estimated based on combining these data with survey-based yield information point toward statistically significant and economically meaningful effects that differ from what has...

DETAILS

Author

Deininger,Klaus W.;

Ali,Daniel Ayalew;

Kussul,Nataliia;

Lavreniuk,Mykola;

Nivievskyi,Oleg;
Document Date
2020/06/29
Document Type
Policy Research Working Paper
Report Number
WPS9306
Volume No
1
Total Volume(s)
1
Country
Ukraine,
Region
Europe and Central Asia,
Disclosure Date
2020/06/29
Disclosure Status
Disclosed
Doc Name
Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine
Keywords
Crop

DOWNLOADS

COMPLETE REPORT

Official version of document (may contain signatures, etc)

Official PDF
TXT*
Total Downloads** : 1209
Download Stats
*The text version is uncorrected OCR text and is included solely to benefit users with slow connectivity.

Citation

Deininger,Klaus W.; Ali,Daniel Ayalew; Kussul,Nataliia; Lavreniuk,Mykola; Nivievskyi,Oleg.

Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine (English). Policy Research working paper|no. WPS 9306 Washington, D.C. : World Bank Group. http://documents.worldbank.org/curated/en/459481593442273789

Using Machine Learning to Assess Yield Impacts of Crop Rotation : Combining Satellite and Statistical Data for Ukraine (English)

DETAILS

DOWNLOADS

COMPLETE REPORT

Citation

SUBSCRIBE TO EMAIL ALERTS