Towards improving the accuracy of opium yield estimates with remote sensing

Abstract

Yearly estimates of illicit opium production are key metrics for assessing the effectiveness of counter narcotics policy in Afghanistan. Poor security often prevents access to sample locations and puts pressure on field surveyors, resulting in biased sampling and errors in data recording. Supportive methods using aerial digital photography for improving yield estimates were investigated in the UK in 2004, 2005 and 2010. There were good empirical relationships between NDVI and poppy yield indicators (mature capsule volume and dry capsule yield) for individual fields. The results suggested a good generalised relationship across all sampled fields and years (R 2 >0.70) during the 3-4 week period including poppy flowering. Regression estimates using this relationship with the imagery counteracted bias in the sample estimate of yield, reduced sample error and enabled the production of detailed maps showing the poppy yield distribution. The application of this approach using VHR satellite imagery was investigated in the context of the annual opium survey in Afghanistan. Initial results indicated the potential for bias correction of yield estimates using a smaller and targeted collection of ground observations as an alternative to random sampling.

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

“…The coefficient of determination at the flowering stage was found to be low, as plant development was not uniform (i.e., some plants had progressed to the flowering stage while others remained at the stem elongation stage). This shows that at intermediate developmental stages of the crop the accuracy of the relationship between PH and CV is limited, as reported previously [7].…”

“…Several studies have highlighted this phenomenon based on field observation of poppy crops grown under controlled conditions [43,45,[48][49][50]. Few studies have used remote sensing technologies for poppy yield estimation [7,21]. Data collected from field measurements, particularly physical measurements of the crop, provide reference information on crop growth.…”

“…In earlier studies, different physiological indicators, such as plant height, have been assessed to predict opium yield [20,21,[43][44][45][46][47][48]. Spectral indices have been reported to estimate capsule volume and showed a significant correlation between NDVI and capsule volume from flowering till harvesting stage [7]. In most fields, poppy crop growth is spatially highly heterogeneous and requires a substantial amount of data collection to develop models for yield estimation [45].…”

“…In precision agriculture, remote sensing has been used to monitor crop growth and health by computing a range of spectral vegetation indices [2][3][4][5][6][7][8][9]. However, recently more attention has been given to the use of crop height modelling for yield estimation [10][11][12].…”

Yield estimation and forecasting for winter wheat in Hungary using time series of MODIS data

“…Anderson et al 2016), for potato (e.g. Rahman et al 2012), or even for opium (Waine et al 2014). Among all these, wheat is the most widely-grown food crop type in the world and the most important cereal crop traded on international markets (Becker-Reshef et al 2010).…”