Nepal Rice Crop Cut & Survey Data 2016
Version: 4– Released: Tue Nov 07 22:51:47 CST 2017
Cataloging Information
Data & Analysis
Data Citation
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Data Citation Details
Study Global IDhdl:11529/10968
AuthorsGokul Paudel (CIMMYT); Shashish Maharjan (CIMMYT); David Guerena (CIMMYT); Ashok Rai (CIMMYT); Andrew James McDonald (CIMMYT)
ProducerInternational Maize and Wheat Improvement Center (CIMMYT) Logo; International Rice Research Institute (IRRI) Logo; International Food Policy Research Institute (IFPRI) Logo
Production Date2017
Production PlaceNepal
Software Stata; Open Data Kit (ODK)
Funding AgencyUSAID and Bill & Melinda Gates Foundation (BMGF)
DistributorInternational Maize and Wheat Improvement Center (CIMMYT) Logo; International Rice Research Institute (IRRI) Logo; International Food Policy Research Institute (IFPRI) Logo
Distributor ContactGokul Paudel (CIMMYT),
Distribution DateJune 10, 2017
DepositorAshok Rai
Deposit DateJune 22, 2017
Description and Scope

The major objectives of this rice crop cuts and survey were to:

(i) identify major rice yield determinants in western terai districts of Nepal and

(ii) to identify major determinants that describe the variability in rice yield across farms thereby linking with farm characteristics and socio-economic gradients.

This study uses Remote Sensing (RS) data particularly the NDVI (Normalized Difference Vegetative Index) value extracted from LandSat satellite images in each of the six districts (Kanchanpur, Kailali, Bardyia, Banke, Kapilbastu and Rupendhai). Since the resolution of LandSat satellite was better than MODIS; we used LandSat derived NDVI values to capture the variability in standing green biomass (a proxy for yield) so that sample selected will represent this variability in NDVI values. In each of the districts we saw a normal distribution of NDVI and samples were selected randomly by stratifying the NDVI values into four quartiles of bell curve, so that selected sample will represent proportionally the bell curve quartiles.

The study contains several optional modules questions and mandatory modules. The mandatory modules give the broader insights on input uses across farms while the optional module provides better insight on each input uses for example; fertilizer use details, irrigation dynamics, weed management and socio-economics gradients particularly based on income and expenditure of households. The optional module is accompanied by the crop cuts data which was done in three quadrants of each plot with 2*2=4 meter square area.

The sample size for this survey is 1052 households and the inputs use were asked for largest rice grown plots as farms may have multiple plots and inputs use might be different in different plots. Out of the total samples of 1052; a set of (~12%; 126 samples) households participated in optional modules to get the detail data on irrigation dynamics, weed management and socio-economics parameters.

Description Date2017
KeywordsNepal (Global Agricultural Concept Scheme Core (GACS)); rice (Global Agricultural Concept Scheme Core (GACS)); surveys (Global Agricultural Concept Scheme Core (GACS)); remote sensing (Global Agricultural Concept Scheme Core (GACS)); data,agricultural (Global Agricultural Concept Scheme Core (GACS)); NDVI (Global Agricultural Concept Scheme Core (GACS)); landsat (Global Agricultural Concept Scheme Core (GACS)); landsat images (Global Agricultural Concept Scheme Core (GACS)); socioeconomics (Global Agricultural Concept Scheme Core (GACS)); yield factors (Global Agricultural Concept Scheme Core (GACS))
Time Period CoveredSeptember, 2016 - April, 2017
Date of CollectionNovember, 2016 - February, 2017
Geographic CoverageSix terai districts of mid, west and far-west (Rupandehi, Kapilbastu, Banke, Bardiya, Kailali, Kanchanpur)
Geographic Unitdistrict
Kind of Datacrop cut and survey data
Data Availability
Number of Files 30
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"Nepal Rice Crop Cut & Survey Data 2016", hdl:11529/10968