Development of a remote sensing-based rice yield forecasting model

Abstract

This study aimed to develop a remote sensing-based method for forecasting rice yield by considering vegetation greenness conditions during initial and peak greenness stages of the crop; and implemented for “boro” rice in Bangladeshi context. In this research, we used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived two 16-day composite of normalized difference vegetation index (NDVI) images at 250 m spatial resolution acquired during the initial (January 1 to January 16) and peak greenness (March 23/24 to April 6/7 depending on leap year) stages in conjunction with secondary datasets (i.e., boro suitability map, and ground-based information) during 2007-2012 period. The method consisted of two components: (i) developing a model for delineating area under rice cultivation before harvesting; and (ii) forecasting rice yield as a function of NDVI. Our results demonstrated strong agreements between the model (i.e., MODIS-based) and ground-based area estimates during 2010-2012 period, i.e., coefficient of determination (R2); root mean square error (RMSE); and relative error (RE) in between 0.93 to 0.95; 30,519 to 37,451 ha; and ±10% respectively at the 23 district-levels. We also found good agreements between forecasted (i.e., MODIS-based) and ground-based yields during 2010-2012 period (R2 between 0.76 and 0.86; RMSE between 0.21 and 0.29 Mton/ha, and RE between -5.45% and 6.65%) at the 23 district-levels. We believe that our developments of forecasting the boro rice yield would be useful for the decision makers in addressing food security in Bangladesh.

Estimation of Net Rice Production through Improved CASA Model by Addition of Soil Suitability Constant (ħα)

“…The results obtained through this improved CASA model, by addition of the constant likely to be useful for agronomists by providing more accurate estimates of NPP. rds: net primary production; biomass estimation; photosynthesis; respiration; rice ion period; net radiation uction ut three billion of the world's population consume rice (Oryza Sativa) as an essential p [1]. Almost 88% of global rice production is obtained from Asia [2].…”

“…About three billion of the world's population consume rice (Oryza Sativa) as an essential food/crop [1]. Almost 88% of global rice production is obtained from Asia [2].…”

“…About three billion of the world's population c food/crop [1]. Almost 88% of global rice production is producing countries in the world are China .…”

“…About three billion of the world's population consum food/crop [1]. Almost 88% of global rice production is obtain Abstract: Net primary production (NPP) is an important indicator of the supply of foo We used a hierarchy model and real time field observations to estimate NPP using satel Net radiation received by rice crop canopies was estimated as 27 , respect stress on rice crops varied between 0.5838 and 0.1218 from the start until the end of the R generation declined from 6.09-1.03 g/m 2 in the tillering and ripening stages, respectivel a soil suitability constant (ħα) into the Carnegie-Ames-Stanford Approach (CASA) mod a more precise estimate of yield.…”

Improving the UAV-based yield estimation of paddy rice by using the solar radiation of geostationary satellite Himawari-8

“…Additionally, the field sizes are small and variable, and the use of high-resolution spatial images is preferable, to avoid mixed pixels. Unmanned aerial vehicles (UAVs), also called drones, have a distinct advantage at this point: UAV-based yield estimation has been investigated as a means of estimating field-level crop yield (Stroppiana et al, 2015;Mosleh et al, 2016;Teoh et al, 2016). These studies apply a regression model between a spectral index and the observed yield, for yield estimation purposes.…”