Toby W. Waine

Survey and monitoring of opium poppy and wheat in Afghanistan: 2003–2009

An integrated application of remote-sensing technology was devised and applied in Afghanistan during 2003–2009 providing critical information on cereal and poppy cultivation and poppy eradication. The results influenced UK and international policy and counter-narcotics actions in Afghanistan.

The application of time-series MODIS NDVI profiles for the acquisition of crop information across Afghanistan

We investigated and developed a prototype crop information system integrating 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data with other available remotely sensed imagery, field data, and knowledge as part of a wider project monitoring opium and cereal crops. NDVI profiles exhibited large geographical variations in timing, height, shape, and number of peaks, with characteristics determined by underlying crop mixes, growth cycles, and agricultural practices. MODIS pixels were typically bigger than the field sizes, but profiles were indicators of crop phenology as the growth stages of the main first-cycle crops (opium poppy and cereals) were in phase. Profiles were used to investigate crop rotations, areas of newly exploited agriculture, localized variation in land management, and environmental factors such as water availability and disease. Near-real-time tracking of the current years’ profile provided forecasts of crop growth stages, early warning of drought, and mapping of affected areas. Derived data products and bulletins provided timely crop information to the UK Government and other international stakeholders to assist the development of counter-narcotic policy, plan activity, and measure progress. Results show the potential for transferring these techniques to other agricultural systems.

Towards improving the accuracy of opium yield estimates with remote sensing

Yearly estimates of illicit opium production are key metrics for assessing the effectiveness of the 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 normalized difference vegetation index and poppy yield indicators (mature capsule volume and dry capsule yield) for individual fields. The results suggested a good generalized relationship across all sampled fields and years (R2 > 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 very-high-resolution 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.

In-channel 3D models of riverine environments for hydromorphological characterization

Recent legislative approaches to improve the quality of rivers have resulted in the design and implementation of extensive and intensive monitoring programmes that are costly and time consuming. An important component of assessing the ecological status of a water body as required by the Water Framework Directive is characterising the hydromorphology. Recent advances in autonomous operation and the spatial coverage of monitoring systems enables more rapid 3D models of the river environment to be produced. This study presents a Structure from Motion (SfM) semi-autonomous based framework for the estimation of key reach hydromorphological measures such as water surface area, wetted water width, bank height, bank slope and bank-full width, using in-channel stereo-imagery. The framework relies on a stereo-camera that could be positioned on an autonomous boat. The proposed approach is demonstrated along three 40 m long reaches with differing hydromorphological characteristics. Results indicated that optimal stereo-camera settings need to be selected based on the river appearance. Results also indicated that the characteristics of the reach have an impact on the estimation of the hydromorphological measures; densely vegetated banks, presence of debris and sinuosity along the reach increased the overall error in hydromorphological measure estimation. The results obtained highlight a potential way forward towards the autonomous monitoring of freshwater ecosystems.

Evaluating management zone maps for variable rate fungicide application and selective harvest

Abstract Currently the majority of crop protection approaches are based on homogeneous rate fungicide application (HRFA) over the entire field area. With the increasing pressures on fungicide applications, associated with increased environmental impact and cost, an alternative approach based on variable rate fungicide application (VRFA) and selective harvest (SH) is needed. This study was undertaken to evaluate the economic viability of adopting VRSA and SH in winter wheat and the environmental benefit in terms of chemical reduction is also discussed. High resolution data of crop canopy properties, yellow rust, fusarium head blight (FHB), soil properties and yield were subjected to k-means cluster analysis to develop management zone (MZ) maps for one field in Bedfordshire, UK. Virtual cost-benefit analysis for VRFA was performed on three fungicide application timings, namely, T1 and T2 focused on yellow rust, and T3 focused on FHB. Cost-benefit analysis was also applied to SH, which assumed different selling prices between healthy and grain downgraded due to mycotoxin infection. Results showed that in this study VRFA allowed for fungicide reductions of 22.24% at T1 and T2 and 25.93% at T3 when compared to HRFA. SH reduced the risk of market rejection due to low quality and high mycotoxin content. Gross profit of combining SH and VRFA was £83.35 per hectare per year, divided into SH £48.04 ha−1, and VRFA £8.8 ha−1 for T1 and T2 and £17.7 ha−1 for T3. Total profit when considering soil and crop scanning costs would be £66.85 ha−1 per year, which is roughly equivalent to €80 or

Improved estimates of opium cultivation in Afghanistan using imagery-based stratification

90 ha−1 per year. This study was restricted to a single field but demonstrates the potential of fungicide reductions and economic viability of this MZ concept.

A multi sensor data fusion approach for creating variable depth tillage zones

ABSTRACT The United Nations Office on Drugs and Crime and the US Government make extensive use of remote sensing to quantify and monitor trends in Afghanistan’s illicit opium production. Cultivation figures from their independent annual surveys can vary because of systematic differences in survey methodologies relating to spectral stratification and the addition of a pixel buffer to the agricultural area. We investigated the effect of stratification and buffering on area estimates of opium poppy using SPOT5 imagery covering the main opium cultivation area of Helmand province and sample data of poppy fields interpreted from very high resolution satellite imagery. The effect of resolution was investigated by resampling the original 10 m pixels to 20, 30, and 60 m, representing the range of available imagery. The number of strata (1, 4, 8, 13, 23, 40) and sample fraction (0.2–2%) used in the estimate were also investigated. Stratification reduced the confidence interval by improving the precision of estimates. Cultivation estimates of poppy using 40 spectral strata and a sample fraction of 1.1% had a similar precision to direct expansion estimates using a 2% sample fraction. Stratified estimates were more robust to changes in sample size and distribution. The mapping of the agricultural area had a significant effect on poppy cultivation estimates in Afghanistan, where the area of total agricultural production can vary significantly between years. The findings of this research explain differences in cultivation figures of the opium monitoring programmes in Afghanistan and recommendations can be applied to improve resource monitoring in other geographic areas.

Physical soil quality indicators for monitoring British soils

In this research a multi-sensor and data fusion approach was developed to create variable depth tillage zones. Data collected with an electromagnetic sensor was fused with measurements taken with a hydraulic penetrometer and conventionally acquired soil bulk density (BD) and moisture content (MC) measurements. Packing density values were then calculated for eight soil layers to determine the need to cultivate or not. From the results 62% of the site required the deepest tillage at 38 cm, 16% required tillage at 33 cm and 22% required no tillage at all. The resultant maps of packing density were shown to be a useful approach to map layered soil compaction and guide VDT operations.

Image segmentation for improved consistency in image-interpretation of opium poppy

Soil condition or quality determines its ability to deliver a range of functions that support ecosystem services, human health and wellbeing. The increasing policy imperative to implement successful soil monitoring programmes has resulted in the demand for reliable soil quality indicators (SQIs) for physical, biological and chemical soil properties. The selection of these indicators needs to ensure that they are sensitive and responsive to pressure and change, e.g. they change across space and time in relation to natural perturbations and land management practices. Using a logical sieve approach based on key policy-related soil functions, this research assessed whether physical soil properties can be used to indicate the quality of British soils in terms of their capacity to deliver ecosystem goods and services. The resultant prioritised list of physical SQIs was tested for robustness, spatial and temporal variability, and expected rate of change using statistical analysis and modelling. Seven SQIs were prioritised: soil packing density, soil water retention characteristics, aggregate stability, rate of soil erosion, depth of soil, soil structure (assessed by visual soil evaluation) and soil sealing. These all have direct relevance to current and likely future soil and environmental policy and are appropriate for implementation in soil monitoring programmes.

Fusion of data from multiple soil sensors for the delineation of water holding capacity zones

ABSTRACT The image-interpretation of opium poppy crops from very high resolution satellite imagery forms part of the annual Afghanistan opium surveys conducted by the United Nations Office on Drugs and Crime and the United States Government. We tested the effect of generalization of field delineations on the final estimates of poppy cultivation using survey data from Helmand province in 2009 and an area frame sampling approach. The sample data was reinterpreted from pan-sharpened IKONOS scenes using two increasing levels of generalization consistent with observed practice. Samples were also generated from manual labelling of image segmentation and from a digital object classification. Generalization was found to bias the cultivation estimate between 6.6% and 13.9%, which is greater than the sample error for the highest level. Object classification of image-segmented samples increased the cultivation estimate by 30.2% because of systematic labelling error. Manual labelling of image-segmented samples gave a similar estimate to the original interpretation. The research demonstrates that small changes in poppy interpretation can result in systematic differences in final estimates that are not included within confidence intervals. Segmented parcels were similar to manually digitized fields and could provide increased consistency in field delineation at a reduced cost. The results are significant for Afghanistan’s opium monitoring programmes and other surveys where sample data are collected by remote sensing.