Browsing by Author "Wood, G. A."
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Item Open Access The application of remote sensing to identify and measure sealed soil and vegetated surfaces in urban environments(Cranfield University, 2010-12) Kampouraki, Maria; Wood, G. A.; Brewer, Timothy R.Soil is an important non-renewable source. Its protection and allocation is critical to sustainable development goals. Urban development presents an important drive of soil loss due to sealing over by buildings, pavements and transport infrastructure. Monitoring sealed soil surfaces in urban environments is gaining increasing interest not only for scientific research studies but also for local planning and national authorities. The aim of this research was to investigate the extent to which automated classification methods can detect soil sealing in UK urban environments, by remote sensing. The objectives include development of object-based classification methods, using two types of earth observation data, and evaluation by comparison with manual aerial photo interpretation techniques. Four sample areas within the city of Cambridge were used for the development of an object-based classification model. The acquired data was a true-colour aerial photography (0.125 m resolution) and a QuickBird satellite imagery (2.8 multi-spectral resolution). The classification scheme included the following land cover classes: sealed surfaces, vegetated surfaces, trees, bare soil and rail tracks. Shadowed areas were also identified as an initial class and attempts were made to reclassify them into the actual land cover type. The accuracy of the thematic maps was determined by comparison with polygons derived from manual air-photo interpretation; the average overall accuracy was 84%. The creation of simple binary maps of sealed vs. vegetated surfaces resulted in a statistically significant accuracy increase to 92%. The integration of ancillary data (OS MasterMap) into the object-based model did not improve the performance of the model (overall accuracy of 91%). The use of satellite data in the object-based model gave an overall accuracy of 80%, a 7% decrease compared to the aerial photography. Future investigation will explore whether the integration of elevation data will aid to discriminate features such as trees from other vegetation types. The use of colour infrared aerial photography should also be tested. Finally, the application of the object- based classification model into a different study area would test its transferability.Item Open Access Calibration methodology for mapping within-field crop variability using remote sensing(Elsevier, 2003-04) Wood, G. A.; Taylor, John C.; Godwin, R. J.A successful method of mapping within-field crop variability of shoot populations in wheat (Triticum aestivum) and barley (Hordeum vulgare L.) is demonstrated. The approach is extended to include a measure of green area index (GAI). These crop parameters and airborne remote sensing measures of the normalised difference vegetation index (NDVI) are shown to be linearly correlated. Measurements were made at key agronomic growth stages up to the period of anthesis and correlated using statistical linear regression based on a series of field calibration sites. Spatial averaging improves the estimation of the regression parameters and is best achieved by sub-sampling at each calibration site using three 0·25 m2 quadrats. Using the NDVI image to target the location of calibration sites, eight sites are shown to be sufficient, but they must be representative of the range in NDVI present in the field, and have a representative spatial distribution. Sampling the NDVI range is achieved by stratifying the NDVI image and then randomly selecting within each of the strata; ensuring a good spatial distribution is determined by visual interpretation of the image. Similarly, a block of adjacent fields can be successfully calibrated to provide multiple maps of within-field variability in each field using only eight points per block representative of the NDVI range and constraining the sampling to one calibration site per field. Compared to using 30 or more calibration sites, restricting samples to eight does not affect the estimation of the regression parameters as long as the criteria for selection outlined in this paper is adhered to. In repeated tests, the technique provided regression results with a value for the coefficient of determination of 0·7 in over 85% of cases. At farm scale, the results indicate an 80–90% probability of producing a map of within crop field variability with an accuracy of 75–99%. This approach provides a rapid tool for providing accurate and valuable management information in near real-time to the grower for better management and for immediate adoption in precision farming practices, and for determining variable rates of nitrogen, fungicide or plant growth regulators.Item Open Access Developing strategies for spatially variable nitrogen application in cereals II: wheat(Elsevier , 2003-04) Welsh, J. P.; Wood, G. A.; Godwin, R. J.; Taylor, John C.; Earl, R.; Blackmore, S.; Knight, S. M.For precision agriculture to provide both economic and environmental benefits over conventional farm practice, management strategies must be developed to accommodate the spatial variability in crop performance that occurs within fields. Experiments were established in crops of winter barley (Hordeum vulgare L.) over three seasons. The aim of which was to evaluate a set of variable rate nitrogen strategies and examining the spatial variation in crop response to applied N. The optimum N application rate varied from 90 to in excess of 160 kg [N] ha−1 in different parts of the field, which supports the case for applying spatially variable rates of N. This, however, is highly dependent on seasonal variations, e.g. the quantity and distribution of rainfall and the effect that this has on soil moisture deficits and crop growth. Estimates of yield potential, produced from either historic yield data or shoot density maps derived from airborne digital photographic images, were used to divide experimental strips into management zones. These zones were then managed according to two N application strategies. The results from the historic yield approach, based on 3 yr of yield data, were inconsistent, and it was concluded that that this approach, which is currently the most practical commercial system, does not provide a suitable basis for varying N rates. The shoot density approach, however, offered considerably greater potential as it takes account of variation in the current crop. Using this approach, it was found that applying additional N to areas with a low shoot population and reducing N to areas with a high shoot population resulted in an average strategy benefit of up to 0·36 t ha−1 compared with standard farm practice.Item Open Access Developing Strategies for spatially variable nitrogen application in cereals, I: Winter barley(Elsevier , 2003-04) Welsh, J. P.; Wood, G. A.; Godwin, R. J.; Taylor, John C.; Earl, R.; Blackmore, S.; Knight, S. M.For precision agriculture to provide both economic and environmental benefits over conventional farm practice, management strategies must be developed to accommodate the spatial variability in crop performance that occurs within fields. Experiments were established in crops of winter barley (Hordeum vulgare L.) over three seasons. The aim of which was to evaluate a set of variable rate nitrogen strategies and examining the spatial variation in crop response to applied N. The optimum N application rate varied from 90 to in excess of 160 kg [N] ha−1 in different parts of the field, which supports the case for applying spatially variable rates of N. This, however, is highly dependent on seasonal variations, e.g. the quantity and distribution of rainfall and the effect that this has on soil moisture deficits and crop growth. Estimates of yield potential, produced from either historic yield data or shoot density maps derived from airborne digital photographic images, were used to divide experimental strips into management zones. These zones were then managed according to two N application strategies. The results from the historic yield approach, based on 3 yr of yield data, were inconsistent, and it was concluded that that this approach, which is currently the most practical commercial system, does not provide a suitable basis for varying N rates. The shoot density approach, however, offered considerably greater potential as it takes account of variation in the current crop. Using this approach, it was found that applying additional N to areas with a low shoot population and reducing N to areas with a high shoot population resulted in an average strategy benefit of up to 0·36 t ha−1 compared with standard farm practice.Item Open Access An Economic analysis of the potential for precision farming in UK cereal production(Elsevier , 2003-04) Godwin, R. J.; Richards, Terence E.; Wood, G. A.; Welsh, J. P.; Knight, S. M.The results from alternative spatial nitrogen application studies are analysed in economic terms and compared to the costs of precision farming hardware, software and other services for cereal crops in the UK. At current prices, the benefits of variable rate application of nitrogen exceed the returns from a uniform application by an average of £22 ha−1 The cost of the precision farming systems range from £5 to £18 ha−1 depending upon the system chosen for an area of 250 ha. The benefits outweigh the associated costs for cereal farms in excess of 80 ha for the lowest price system to 200–300 ha for the more sophisticated systems. The scale of benefits obtained depends upon the magnitude of the response to the treatment and the proportion of the field that will respond. To be cost effective, a farmed area of 250 ha of cereals, where 30% of the area will respond to variable treatment, requires an increase in crop yield in the responsive areas of between 0·25 and 1.00 t ha−1 (at £65 t−1) for the basic and most expensive precision farming systems, respectively.Item Open Access The evaluation of ground based remote sensing systems for canopy nitrogen management in winter wheat(Cranfield University, 2007-04) Havránková, Jana; Godwin, R. J.; Wood, G. A.Nitrogen management is a crucial issue in terms of environmental and economical efficiency for winter wheat husbandry. Precision Agriculture in particular Remote Sensing, has been used to determine the variability of the crop. However, to be able to apply the required rate of nitrogen, the calibration of the data with the crop characteristics is critical. Satellite, airborne and ground based platforms are possible to use. Despite the presence of some commercial applications of the satellite and airborne techniques, the ground based systems offer advantages in terms of availability. The most common passive ground based remote sensing system in Europe is the Yara N sensor which has limitations in poor light conditions. Active sensors, using their own energy sources, are now available in the market e.g. the Crop Circle (Holland Scientific) and the Yara N sensor ALS. The aim of this work was to evaluate the active and passive ground based remote sensing systems for canopy nitrogen management in winter wheat. The work was divided into three sub-experiments. Two were conducted in Wilstead (UK) in 2005 and 2006, with the objective to determine the relationship between sensors output (NDVI) and crop (wheat) characteristics during the growing season and to evaluate their application in field management of winter wheat. The field experiment carried out in Oponice (Slovakia) in 2006 assessed three different management strategies (the real time, near real time and traditional nitrogen management). The results showed that both the active and the passive sensors determine the variability in shoot numbers and total nitrogen content of plants particularly in the early growth stages. The application of Nitrogen using these sensors in the UK saved 15kg N/ha (UK). The nitrogen saved in Slovakia was small (1.5 kg/ha). Use of the sensors enabled a reduction in nitrogen without a negative influence on yield, which increased the Nitrogen use efficiency. In addition to this there were potential environmental benefits through a 52% reduction of the residual Nitrogen in the soil in the UK. In Slovakia there was no significant overall reduction in the total nitrogen used; however, a different application rates was applied to 80% of the field. The overall cost of production in Slovakia using the sensors was increased by 5%. The cost of sensing in the UK was £11/ha which could be offset by the 15 kgN/ha reduction and a potential small increase of yield by 1%.Item Open Access Real-time measures of canopy size as a basis for spatially varying nitrogen applications to winter wheat sown at different seed rates(Elsevier, 2003-04) Wood, G. A.; Welsh, J. P.; Godwin, R. J.; Taylor, John C.; Earl, R.; Knight, S. M.Experiments at two sites growing winter wheat show that in order to manage a wheat canopy more effectively, the use of specific remote sensing techniques both to monitor crop canopy expansion, and to determine variable nitrogen applications at key timings is required. Variations in seed rate were used to achieve a range of initial crop structures, and treatments were compared to standard farm practice. In the first year, the effect of varying seed rate (250, 350 and 450 seeds m−2) on crop structure, yield components and grain yield, was compared to the effects of underlying spatial variation. Plant populations increased up to the highest rate, but shoot and ear populations peaked at 350 seeds m−2. Compensation through an increased number of grains per ear and thousand grain weight resulted in the highest yield and gross margin at the lowest seed rate. In later experiments, the range of seed rates was extended to include 150 seeds m−2, each sown in 24 m wide strips split into 12 m wide halves. One half received a standard nitrogen dose of 200 kg [N] ha−1, the other a variable treatment based on near ‘real-time’ maps of crop growth. Both were split into three applications, targeted at mid-late tillering (early March), growth stages GS30-31 (mid April) and GS33 (mid May). At each timing, calibrated aerial digital photography was used to assess crop growth in terms of shoot population at tillering, and canopy green area index at GS30-31 and GS33. These were compared to current agronomic guidelines. Application rates were then varied below or above the planned amount where growth was above- or below-target, respectively. In the first field, total nitrogen doses in the variable treatments ranged from 188 to 243 kg [N] ha−1, which gave higher yields than the standards at all seed rates in the range 0·36–0·78 t ha−1 and gross margins of £17 to £60 ha−1. In the second field, variable treatments ranged from 135 to 197 kg [N] ha−1 that resulted in lower yields of −0·32 to +0·30 t ha−1. However, in three out of the four seed rates, variable treatments produced higher gross margins than the standard, which ranged from £2 to £20 ha−1. In both fields, the greatest benefits were obtained where the total amount of applied nitrogen was similar to the standard, but was applied variably rather than uniformly along the strips. Simple nitrogen balance calculations have shown that variable application of nitrogen can have an overall effect on reducing the nitrogen surplus by one-third.Item Open Access Soil factors and their influence on within-field crop variability II: spatial analysis and determination of management zones(Elsevier, 2003-04) Taylor, John C.; Wood, G. A.; Earl, R.; Godwin, R. J.Spatial variation of crop yields was examined in three trial cereal fields in England from 1994 through 1997. The fields were managed with uniform inputs but there were considerable differences in the spatial patterns and magnitudes of variation between fields and seasons. Up to 50% of the yield variation was within the tramline spacing distance (20â 24 m) and this appeared to relate to crop management practices rather than underlying soil factors. Longer-range variation generally increased up to field scale but was not constant between seasons. Longer-range variation was more apparent in dry years and was attributable to soil variation. Soil series differences coincided with yield differences in dry years when the soil series differences could be expected to create large differences in soilâ water relationships. Soil electrical conductivity, measured by electromagnetic induction (EMI), was investigated as a surrogate for detailed soil coring. Field zones created by EMI also coincided with yield differences and zones were similar to those delineated by soil series with expected differences in soilâ water relationships. The EMI observations were found to be a useful and cost-effective surrogate for representing soil variability in fields likely to create yield variations. Subdivision of fields into management zones using multi-variate K-means cluster analysis of historical yield and EMI observations formed an objective basis for targeting soil samples for nutrient analysis and development of site-specific application strategies. The appropriateness of site-specific management has to be assessed annually because magnitude and pattern of variation changes from season to season.Item Open Access Soil Factors and their Influence on Within-Field Crop Variability, I: Field Observation of Soil Variation(Elsevier Science B.V., Amsterdam, 2003-04-01T00:00:00Z) Earl, R.; Taylor, John C.; Wood, G. A.; Bradley, I.; James, Iain T.; Waine, Toby W.; Welsh, J. P.; Godwin, R. J.; Knight, S. M.A fundamental component of adopting the concept of precision farming in practice is the ability to measure spatial variation in soil factors and assess the influence of this on crop variability in order to apply appropriate management strategies. The aim of this study was to appraise potential methods for measuring spatial variability in soil type, nutrient status and physical properties in practical farming situations. Five fields that are representative of more than 30% of soils used for arable production in England and Wales were selected for use as case studies. Maps of soil type were generated from a conventional hand auger survey on a 100 m grid and the excavation of targeted soil profile pits. These were compared with those refined using a mechanised soil coring device and scans of electromagnetic inductance (EMI) carried out while the soil could reasonably be considered to be at, or near, field capacity moisture content. In addition, soil sampling for nutrient analyses was conducted on a 50 m grid to examine the spatial variation in nutrient status. Conventional methods for sampling soil were found to be appropriate for identifying soil types at specific locations within the field sites, however, they were time- consuming to perform which placed an economic and therefore a practical limitation on the sampling density possible. The resulting data were considered to be too sparse for demarcating soil type boundaries for use in the context of precision farming. The location of soil boundaries were refined by using the mechanised soil corer, however, the limitation of this was found to be the time required to analyse the soil cores produced. Maps of soil variation generated from EMI scans conducted at field capacity appear to reflect the underlying variation in soil type observed in maps generated using the mechanised soil corer. and, therefore, this approach has potential as a cost-effective, data- rich, surrogate for measures of soil variability. Results from analyses of soil samples for measurement of nutrient status indicated that whilst there was considerable variation in macro- and micro-nutrient levels in each field, with the exception of pH, these levels were above commonly accepted agronomic limits. Results did however demonstrate the potential for addressing variation in critical factors such as pH at specific locations, however, there is a need to develop protocols for targeting sampling in order to reduce costs.Item Open Access Spatio-temporal modelling of crop co-existence in European agricultural landscapes(Cranfield University, 2007-08) Castellazzi, M. S.; Wood, G. A.; Burgess, Paul J.The environmental risk of growing genetically modified (GM) crops and particularly the spreading of GM genes to related non-GM crops is currently a concern in European agriculture. Because the risks of contamination are linked to the spatial and temporal arrangements of crops within the landscape, scenarios of crop arrangement are required to investigate the risks and potential coexistence measures. However, until recently, only manual methods were available to create scenarios. This thesis aims to provide a flexible referenced tool to create such scenarios. The model, called LandSFACTS, is a scientific research tool which allocates crops into fields, to meet user-defined crop spatio-temporal arrangements, using an empirical and statistical approach. The control of the crop arrangements is divided into two main sections: (i) the temporal arrangement of crops: encompassing crop rotations as transition matrices (specifically-developed methodology), temporal constraints (return period of crops, forbidden crop sequences), initial crops in fields regulated by temporal patterns (specifically-developed statistical analyses) and yearly crop proportions; and (ii) the spatial arrangements of crops: encompassing possible crops in fields, crop rotation in fields regulated by spatial patterns (specifically-developed statistical analyses), and spatial constraints (separation distances between crops). The limitations imposed by the model include the size of the smallest spatial and temporal unit: only one crop is allocated per field and per year. The model has been designed to be used by researchers with agronomic knowledge of the landscape. An assessment of the model did not lead to the detection of any significant flaws and therefore the model is considered valid for the stated specifications. Following this evaluation, the model is being used to fill incomplete datasets, build up and compare scenarios of crop allocations. Within the GM coexistence context, the model could provide useful support to investigate the impact of crop arrangement and potential coexistence measures on the risk of GM contamination of crops. More informed advice could therefore be provided to decision makers on the feasibility and efficiency of coexistence measures for GM cultivation.Item Open Access A systematic representation of crop rotations.(Elsevier Science B.V., Amsterdam., 2008-04-01T00:00:00Z) Castellazzi, M. S.; Wood, G. A.; Burgess, Paul J.; Morris, Joe; Conrad, K. F.; Perry, J. N.Crop rotations are allocations by growers of crop types to specific fields through time. This paper aims at presenting (i) a systematic and rigorous mathematical representation of crops rotations; and (ii) a concise mathematical framework to model crop rotations, which is useable on landscape scale modelling of agronomical practices. Rotations can be defined as temporal arrangements of crops and can be classified systematically according to their internal variability and cyclical pattern. Crop sequences in a rotation can be quantified as a transition matrix, with the Markovian property that the allocation in a given year depends on the crop allocated in the previous year. Such transition matrices can represent stochastic processes and thus facilitate modelling uncertainty in rotations, and forecasting of the long-term proportions of each crop in a rotation, such as changes in climate or economics. The matrices also permit modelling transitions between rotations due to external variables. Computer software was developed that incorporates these techniques and was used to simulate landscape scale agronomic processes over decadal periods.Item Open Access Towards guidance for the design and placement of vegetated filter strips(Cranfield University, 2008-01) Duzant , Julia H.; Wood, G. A.A combined field, laboratory and modelling approach to the study of vegetated filter strips (VFSs) was carried out in order to provide guidance on optimum design and placement for trapping sediment from overland flow. Monitoring of fifteen established filter strips in the Parrett Catchment, England, informed on the complexity of intercepting flow pathways to optimise filter strip performance. Results suggest that a 6 m VFS will trap an average of 1.74 t year -1 of material from a field of 1 ha, but this is highly variable depending on design, placement and management factors. In most cases the majority of coarse sediment is trapped at the upslope edge of the VFS and is typically >85% sand. A revised Morgan-Morgan-Finney model was tested against a range of field and laboratory datasets and an efficiency coefficient of 0.7 was achieved. When testing the model against the field results from the Parrett Catchment, an active filter strip area was used. This took into account only the area of the filter strip effective in trapping sediment due to the convergence and bypassing of flow pathways. In the field, filter strip performance will be improved by reducing concentrated flow reaching the strip and ensuring that flow does not bypass the strip through burrows and gateways, using in field erosion control, maintaining level ground between the field and filter strip edge and managing the strip to maximise the density of vegetative material, particularly the number of vegetative stems. Potential applications for the research include a field based Decision Support System, design of filter strip biophysical architecture and catchment planning.