Re-evaluating the place of urban planning history

This commentary seeks to prompt new discussion about the place of urban planning history in the era of contemporary globalisation. Given the deep historic engagement of urban planning thought and practice with ‘place’ shaping and thus with the constitution of society, culture and politics, we ask how relevant is planning's legacy to the shaping of present day cities. Late twentieth century urban sociology, cultural and economic geography have demonstrated the increasing significance of intercity relations and the functional porosity of metropolitan boundaries in the network society, however statutory urban planning systems remain tied to the administrative geographies of states. This ‘territorial fixing’ of practice constrains the operational space of planning and, we argue, also limits its vision to geopolitical scales and agendas that have receding relevance for emerging urban relations. We propose that a re-evaluation of planning history could have an important part to play in addressing this spatial conundrum.

Financial viability appraisals for site-specific planning decisions in England

In England, appraisals of the financial viability of development schemes have become an integral part of planning policy-making, initially in determining the amount of planning obligations that might be obtained via legal agreements (known as Section 106 agreements) and latterly as a basis for establishing charging schedules for the Community Infrastructure Levy (CIL). Local planning authorities set these policies on an area-wide basis but ultimately development proposals require consent on a site-by-site basis. It is at this site-specific level that issues of viability are hotly contested. This paper examines case documents, proofs of evidence and decisions from a sample of planning disputes in order to address major issues within development viability, the application of the models and the distribution of the development gain between the developer, landowner and community. The results have specific application to viability assessment in England and should impact on future policy and practice guidance in this field. They also have relevance to other countries that incorporate assessments of economic viability in their planning systems.

Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Towards improving the framework for probabilistic forecast evaluation

The evaluation of forecast performance plays a central role both in the interpretation and use of forecast systems and in their development. Different evaluation measures (scores) are available, often quantifying different characteristics of forecast performance. The properties of several proper scores for probabilistic forecast evaluation are contrasted and then used to interpret decadal probability hindcasts of global mean temperature. The Continuous Ranked Probability Score (CRPS), Proper Linear (PL) score, and IJ Good’s logarithmic score (also referred to as Ignorance) are compared; although information from all three may be useful, the logarithmic score has an immediate interpretation and is not insensitive to forecast busts. Neither CRPS nor PL is local; this is shown to produce counter intuitive evaluations by CRPS. Benchmark forecasts from empirical models like Dynamic Climatology place the scores in context. Comparing scores for forecast systems based on physical models (in this case HadCM3, from the CMIP5 decadal archive) against such benchmarks is more informative than internal comparison systems based on similar physical simulation models with each other. It is shown that a forecast system based on HadCM3 out performs Dynamic Climatology in decadal global mean temperature hindcasts; Dynamic Climatology previously outperformed a forecast system based upon HadGEM2 and reasons for these results are suggested. Forecasts of aggregate data (5-year means of global mean temperature) are, of course, narrower than forecasts of annual averages due to the suppression of variance; while the average “distance” between the forecasts and a target may be expected to decrease, little if any discernible improvement in probabilistic skill is achieved.

The new localism, anti-political development machines, and the role of planning consultants: lessons from London's South Bank

This paper draws on a study of the politics of development planning in London’s South Bank to examine wider trends in the governance of contemporary cities. It assesses the impacts and outcomes of so-called new localist reforms and argues that we are witnessing two principal trends. First, governance processes are increasingly dominated by anti-democratic development machines, characterized by new assemblages of public- and private-sector experts. These machines reflect and reproduce a type of development politics in which there is a greater emphasis on a pragmatic realism and a politics of delivery. Second, the presence of these machines is having a significant impact on the politics of planning. Democratic engagement is not seen as the basis for new forms of localism and community control. Instead, it is presented as a potentially disruptive force that needs to be managed by a new breed of skilled private-sector consultant. The paper examines these wider shifts in urban politics before focusing on the connections between emerging development machines and local residential and business communities. It ends by highlighting some of the wider implications of change for democratic modes of engagement and nodes of resistance in urban politics.

Governing calculative practices: An investigation of development viability modelling in the English planning system

Over the last decade the English planning system has placed greater emphasis on the financial viability of development. ‘Calculative’ practices have been used to quantify and capture land value uplifts. Development viability appraisal (DVA) has become a key part of the evidence base used in planning decision-making and informs both ‘site-specific’ negotiations about the level of land value capture for individual schemes and ‘area-wide’ planning policy formation. This paper investigates how implementation of DVA is governed in planning policy formation. It is argued that the increased use of DVA raises important questions about how planning decisions are made and operationalised, not least because DVA is often poorly understood by some key stakeholders. The paper uses the concept of governance to thematically analyse semi-structured interviews conducted with the producers of DVAs and considers key procedural issues including (in)consistencies in appraisal practices, levels of stakeholder consultation and the potential for client and producer bias. Whilst stakeholder consultation is shown to be integral to the appraisal process in order to improve the quality of the appraisals and to legitimise the outputs, participation is restricted to industry experts and excludes some interest groups, including local communities. It is concluded that, largely because of its recent adoption and knowledge asymmetries between local planning authorities and appraisers, DVA is a weakly governed process characterised by emerging and contested guidance and is therefore ‘up for grabs’.

Sticking to the script? The co-production of Neighbourhood Planning in England

Efforts to engage with communities in spatial planning have been criticised as being tokenistic, vehicles for co-option or designed to promote neo-liberal agendas. The introduction of neighbourhood planning (NP) in England under the Localism Act (2011) is claimed by proponents to be a step change in the way that local communities are involved in planning their own areas. However, little empirical evidence has yet emerged to substantiate such claims, or provide details about the practices and experiences of NP. The paper highlights that there are numerous parties involved in the co-production of Neighbourhood Development Plans and there are numerous instances where ideas, policies and priorities that emerge from within neighbourhoods are being ‘rescripted’ to ensure conformity to a bounded form of collaboration.

The take-up of Neighbourhood Planning in England 2011-2015

Exploration of how neighbourhoods and others have responded to the UK government’s localism agenda in England, and specifically towards Neighbourhood Planning (NP), is important given that NP is a prominent part of that policy agenda. It is also of interest as the ramifications emerge for planning practice in the formal introduction of statutory plans which are ostensibly led by communities (Parker et al, 2015; Gallent, 2013). There is a necessary task to provide critical commentary on the socio-economic impact of localist policy. The paper explores the issues arising from experience thus far and highlights the take-up of Neighbourhood Planning since 2011. This assessment shows how a vast majority of those active have been in parished areas and in less-deprived areas. This indicates that government needs to do more to ensure that NP is accessible and worthwhile for a wider range of communities.

Assessing the reliability of probabilistic flood inundation model predictions

An ability to quantify the reliability of probabilistic flood inundation predictions is a requirement not only for guiding model development but also for their successful application. Probabilistic flood inundation predictions are usually produced by choosing a method of weighting the model parameter space, but previous study suggests that this choice leads to clear differences in inundation probabilities. This study aims to address the evaluation of the reliability of these probabilistic predictions. However, a lack of an adequate number of observations of flood inundation for a catchment limits the application of conventional methods of evaluating predictive reliability. Consequently, attempts have been made to assess the reliability of probabilistic predictions using multiple observations from a single flood event. Here, a LISFLOOD-FP hydraulic model of an extreme (>1 in 1000 years) flood event in Cockermouth, UK, is constructed and calibrated using multiple performance measures from both peak flood wrack mark data and aerial photography captured post-peak. These measures are used in weighting the parameter space to produce multiple probabilistic predictions for the event. Two methods of assessing the reliability of these probabilistic predictions using limited observations are utilized; an existing method assessing the binary pattern of flooding, and a method developed in this paper to assess predictions of water surface elevation. This study finds that the water surface elevation method has both a better diagnostic and discriminatory ability, but this result is likely to be sensitive to the unknown uncertainties in the upstream boundary condition

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

The role of Planning Aid England in supporting communities’ engagement in planning

In considering the position of community engagement within planning in a time of neo-liberalism and a context of ‘neo-communitarian localism’ (cf. Jessop, 2002; DeFilippis, 2004), this paper reviews the role and relevance of Planning Aid in terms of its performance and aspirations in guiding and transforming planning practice (Friedmann, 1973; 1987; 2011) since its inception in 1973. In doing this we reflect on the critiques of Planning Aid performance provided by Allmendinger (2004) and bring the account up-to-date following on from past considerations (e.g. Bidwell and Edgar, 1982; Thomas, 1992; Brownill and Carpenter, 2007a,b; Carpenter and Brownill, 2008) and prompted by the 35 years since the University of Reading produced the first published work reviewing Planning Aid (Curtis and Edwards, 1980). Our paper is timely given renewed attacks on planning, the implementation of a form of localism and reductions in funding for planning in a time of austerity. Our view is that the need for forms of ‘neo-advocacy’ planning and community development are perhaps even more necessary now, given the continuing under-representation of lower income groups, minority groups and to allow for the expression of alternative planning futures. Thus further consideration of how to ensure that Planning Aid functions are sustained and understood requires the attention of policymakers and the planning profession more widely.

A global empirical system for probabilistic seasonal climate prediction

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Data Assimilation and Inverse Methods in Terms of a Probabilistic Formulation

The weak-constraint inverse for nonlinear dynamical models is discussed and derived in terms of a probabilistic formulation. The well-known result that for Gaussian error statistics the minimum of the weak-constraint inverse is equal to the maximum-likelihood estimate is rederived. Then several methods based on ensemble statistics that can be used to find the smoother (as opposed to the filter) solution are introduced and compared to traditional methods. A strong point of the new methods is that they avoid the integration of adjoint equations, which is a complex task for real oceanographic or atmospheric applications. they also avoid iterative searches in a Hilbert space, and error estimates can be obtained without much additional computational effort. the feasibility of the new methods is illustrated in a two-layer quasigeostrophic model.