Browsing by Author "Clarke, David"

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    Assessing the impacts of drought on UK wheat production
    (Cranfield University, 2017-01) Clarke, David; Knox, Jerry W.; Hess, Tim M.
    Water limitations typically reduce UK wheat yields on average by 1-2 t ha- 1 , although this can be considerably more in extreme drought years. With the frequency and intensity of droughts expected to increase under a changing climate, an improved understanding of the impacts of drought and better systems for agricultural drought monitoring are required. Previous studies, however, have found no significant relationship between UK wheat yields and commonly employed drought severity indices (DSI). Using historical (1911-2015) daily weather data for Cambridge the Standardized Precipitation Index (SPI), the Standardized Precipitation and Evapotranspiration Index (SPEI), the Palmer Drought Severity Index (PDSI) and the Potential Soil Moisture Deficit (PSMD) were calculated on various time steps (e.g. 1-12 months for SPI and SPEI) to provide a drought record for the site. A wheat crop growth simulation model (Sirius) was then used to simulate the effects of the identified historic droughts on wheat yields. The use of the Sirius crop model removed the non-drought related yield losses (e.g. disease, pests, and lodging) present in national yield records. Using the Spearman’s Rho correlation coefficient (r) the simulated yield record was then correlated against the different DSIs. The droughts of 1921, 1976 and 2010 were found to be the most extreme in term of yield reduction. In addition, there were also two noticeable periods of successive yield loss in the early 1940s and between 2009 and 2013. All DSIs showed significant (p = 0.05) correlations on monthly time steps between April and August. The SPI, SPEI and PSMD showed a strong correlation to wheat yields (r = 0.64 to 0.66) on time steps incorporating the end of the ‘construction’ and the entirety of the ‘production’ phases for wheat growth. The PDSI showed the weakest correlation (r = 0.55), although it may be helpful in identifying yield-limiting droughts earlier in the year. The research has contributed new scientific insights and understanding of the impacts of historic droughts on wheat productivity, and demonstrated the application of DSIs in monitoring potentially yield-limiting droughts. The research also provides new evidence to support developments in UK food security and drought management for agriculture.
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    Vehicle infrastructure cooperative localization using Factor Graphs
    (2016-10-03) Gulati, D.; Zhanh, F.; Clarke, David; Knoll, A.
    Highly assisted and Autonomous Driving is dependent on the accurate localization of both the vehicle and other targets within the environment. With increasing traffic on roads and wider proliferation of low cost sensors, a vehicle-infrastructure cooperative localization scenario can provide improved performance over traditional mono-platform localization. The paper highlights the various challenges in the process and proposes a solution based on Factor Graphs which utilizes the concept of topology of vehicles. A Factor Graph represents probabilistic graphical model as a bipartite graph. It is used to add the inter-vehicle distance as constraints while localizing the vehicle. The proposed solution is easily scalable for many vehicles without increasing the execution complexity. Finally simulation indicates that incorporating the topology information as a state estimate can improve performance over the traditional Kalman Filter approach