Planning theories and environmental impact assessment

Lawrence, David P.

doi:10.1016/s0195-9255(00)00036-6

Cited by 137 publications

(82 citation statements)

References 50 publications

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“…Planning capacity is rooted in the theory of rationalism, which emphasizes building an idealized model pursuing a simple, explicit, adaptable, logical, consistent, and systematic planning process (Lawrence, 2000;Richardson, 2005). The rational planning theory supports using an adequate number of qualified planners, regular updating of plans, and improving technical skills to build strong planning capacity in local environmental planning.…”

Section: Planning Capacitymentioning

confidence: 99%

“…The rational planning theory supports using an adequate number of qualified planners, regular updating of plans, and improving technical skills to build strong planning capacity in local environmental planning. In addition, the theory of pragmatism suggests that an efficient pragmatic planning process can eventually improve plan effectiveness (Lawrence, 2000). Local land-use planning is a complex process involving geographic, social, and economic settings, which can be affected by jurisdictional frameworks and planners' values and experiences (Forester, 1984).…”

Section: Planning Capacitymentioning

confidence: 99%

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Linking Planning Theories with Factors Influencing Local Environmental-Plan Quality

Tang

Brody

2009

Environ Plann B Plann Des

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The major planning theories provide a theoretical foundation for environmental planning. This study extends the major planning theories and develops a robust conceptual framework to measure the key factors influencing local environmental-plan quality. A random sample of forty Californian local comprehensive land-use plans and associated planning processes is analyzed to identify the critical factors influencing environmental-plan quality. Results from multiple regression analysis indicate that regular updating, environmental-information management and sharing, and planners contribute significantly to local environmental-plan quality. The findings expand established planning theories and practice by suggesting ways to improve local environmental-plan quality.

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Section: Planning Capacitymentioning

confidence: 99%

Section: Planning Capacitymentioning

confidence: 99%

Linking Planning Theories with Factors Influencing Local Environmental-Plan Quality

Tang

Brody

2009

Environ Plann B Plann Des

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“…Taking the first of these assumptions, the evidence that objective information is transferred via IA into policy is somewhat limited (Wood and Jones, 1997;Cashmore et al, 2004;Cashmore et al, 2009;Elling, 2009;Van Buuren and Nooteboom, 2009;Eales and Sheate, 2011). More and more authors argue that decision-making is not rational and that IA, for example, has considerably more roles than simply information provision (see, for example, Lawrence, 2000;Leknes, 2001;Bond, 2003;Bekker et al, 2004;Cashmore, 2004;Owens et al, 2004). Bartlett and Kurian (1999) detail six separate models explaining the role of environmental impact assessment in decision-making, in which the information processing (rational) model is just one end of the spectrum of influence; other models include the symbolic politics model, the political economy model, the organisational politics model, the pluralist politics model and the institutionalist model.…”

Section: Impact Assessment Theory and Uncertaintymentioning

confidence: 99%

Managing uncertainty, ambiguity and ignorance in impact assessment by embedding evolutionary resilience, participatory modelling and adaptive management

Bond

Morrison‐Saunders

Gunn

et al. 2015

Journal of Environmental Management

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In the context of continuing uncertainty, ambiguity and ignorance in impact assessment (IA) prediction, the case is made that existing IA processes are based on false 'normal' assumptions that science can solve problems and transfer knowledge into policy. Instead, a 'post-normal science' approach is needed that acknowledges the limits of current levels of scientific understanding. We argue that this can be achieved through embedding evolutionary resilience into IA; using participatory workshops; and emphasizing adaptive management. The goal is an IA process capable of informing policy choices in the face of uncertain influences acting on socio-ecological systems. We propose a specific set of process steps to operationalise this post-normal science approach which draws on work undertaken by the Resilience Alliance. This process differs significantly from current models of IA, as it has a far greater focus on avoidance of, or adaptation to (through incorporating adaptive management subsequent to decisions), unwanted future scenarios rather than a focus on the identification of the implications of a single preferred vision. Implementing such a process * corresponding author 2 would represent a culture change in IA practice as a lack of knowledge is assumed and explicit, and forms the basis of future planning activity, rather than being ignored.

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“…Researchers within the IA literature criticise the dominant planning paradigm 2 for failing to take into account the cognitive limits of the planner, the collective nature of planning and the central role of dialogue [30]. The complexity and controversial nature of decision making requires a collaborative learning approach where different parties define the problems and generate alternative solutions [3,31].…”

Section: Stakeholder Involvementmentioning

confidence: 99%

Key criteria for sustainable wind energy planning—lessons from an institutional perspective on the impact assessment literature

Thygesen

Agarwal

2014

Renewable and Sustainable Energy Reviews

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Citation for the version of the work held in 'OpenAIR@RGU"NOTICE: this is the author's version of a work that was accepted for publication in Renewable and Sustainable Energy Reviews. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Renewable and Sustainable Energy Reviews, [VOL 39, November 2014 Abstract 1 : An increasing number of researchers stress the importance of the national planning institution's role with respect to promoting an "effective" decision-making process in terms of bringing about sustainable energy. Impact assessment (IA) procedures are seen as having strong potential in supporting environmentally conscious energy production. This article discusses criteria for sustainable wind power planning and compares the centralised planning systems for wind energy in two countries -Norway and Scotland -as illustrating cases. We ask the following: What key criteria should be present to secure sustainable wind energy planning, and what are the critical institutional conditions to fulfil these criteria? A review of relevant IA literature reveals four key criteria for promoting sustainable wind planning: (i) clear and integrated political priorities, (ii) stakeholder involvement, (iii) strategic environmental assessment (SEA) and (iv) stringent permission and assessment requirements. We also determined that critical institutional conditions exist that effectively promote sustainable energy production: (a) coordinated energy policy institutions, (b) legitimate planning procedures, (c) that SEAs are followed in the decision-making process and (d) statutory planning regulations.

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Planning theories and environmental impact assessment

Cited by 137 publications

References 50 publications

Linking Planning Theories with Factors Influencing Local Environmental-Plan Quality

Linking Planning Theories with Factors Influencing Local Environmental-Plan Quality

Managing uncertainty, ambiguity and ignorance in impact assessment by embedding evolutionary resilience, participatory modelling and adaptive management

Key criteria for sustainable wind energy planning—lessons from an institutional perspective on the impact assessment literature

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