The Spatial Development Framework

Today, many countries are faced with rapid urbanization. This phenomenon creates problems for spatial planning, especially in places with weak planning systems. This can hinder the implemention of sound spatial development strategies according to a predefined policy discourse or approved development strategy. Tackling – preferably even preventing – such problems requires strategic spatial planning methods tailored to countries’ specific conditions. The Spatial Development Framework (SDF), first developed in 2011 by the United Nations Human Settlements Programme (UN-Habitat), was designed to do just that. 

The SDF method was based on relevant scientific and theoretical knowledge and several years of practical working experience in developing countries. It can help us understand the roles and interlinkages of various urban settlements in a certain territory. Particularly in countries where uncontrolled urbanization leads to fluidity and uncertainty, the SDF method can be instrumental in establishing the sense of territorial structure needed for sensible spatial planning. 

Dealing with weak planning systems

Weak planning systems are often the outcome of numerous factors, such as insufficient human and financial resources, poor institutional capacities, lack of equipment, data and information, and absent or ineffective regulations. As a result, approved policies or strategies cannot be effectively implemented, especially in institutional set-ups that are characterized by central decision-making or, in some cases, beset by corruption. Practices of planning may not be based on formal consensus-building and participatory approaches, or legal and regulatory frameworks may not be responsive to the current and future needs of the population.

While the SDF method doesn't pretend to address all problems associated with weak planning systems, it considers many of them. The method is simple enough to be practical, without losing sight of the complexity of the territory where it's being applied. It involves central and local governments in the planning process and it allows establishing a clear link between the territorial reality and policies that are often spatially blind. Because of these policies, those responsible for implementing them tend to find difficulties in translating policy objectives to local conditions, and cannot take advantage of local data and knowledge at their disposal.

First applications and optimization

The SDF method was applied for the first time in Darfur, Sudan, between 2011 and 2013. On that occasion, the method provided an overall picture of the spatial structure of a complex territory suffering from several years of continuous conflict. The method’s application allowed for defining concrete spatial actions to be carried out in the different states of the region. 

Between 2014 and 2016, the SDF method was further improved and applied in Rwanda. Here, the application of the method indicated the necessity to add some secondary cities to the six already defined in the government’s Second Economic Development and Poverty Reduction Strategy (EDPRS 2). It also evaluated the degree of implementation of the National Urbanization Policy in all the country’s settlements, and it'll soon serve as an interface between national strategic spatial plans and local development plans.

Regional planners discussing location choice of dairy factory between districts using the outputs of the Spatial Development Framework methodology

Three methodologies combined

The SDF method is based on the combination of three methodologies:

• The Matrix of Functions (MoF), conceived by Spaliviero (1989, 2004) is used to analyse and categorize existing settlements based on the mere availability or non-availability of key functions, and to identify clusters of settlements strategically interconnected within a given region. The MoF is a strong methodology for data scarce areas and provides an unbiased and overall vision of the actual distribution of functions in the analysed territory. To learn more, read our article on the Matrix of Functions. 
• Consultative Workshops, which take place in the different parts of the analysed region, and help ensuring a participatory approach during the regional planning process by allowing stakeholders to discuss their opinions.
• The Spatial Multi-Criteria Evaluation (SMCE), a spatial decision support system used to refine the spatial analysis and assess the performance of key themes against existing development policies within the identified network of urban settlements. This helps to formulate planning recommendations for the short, medium and long term. The SMCE can provide good results if sufficient and reliable data is available. 

The SDF method is carried out by a multi-disciplinary team, which works in coordination with an inter-sectoral technical committee including members from the concerned governmental institutions to ensure local ownership. Apart from the specific information collected for the MoF through simple questionnaires, the method uses data provided by the national bureaus of statistics.

The SDF method, step by step

Step A1

The spatial analysis starts with the preparation of baseline information through the collection and organization of existing spatial and non-spatial data, including approved plans, strategies and policies related with spatial development at the different levels (national, regional, local, etc.). As a result, the main spatial challenges and opportunities of the region are defined.

Step A2

The MoF for a given region helps to determine the functional hierarchy of settlements based on availability and diversity of their services, infrastructure and socio-economic activities. It identifies a network of settlements with their territorial influence (i.e. the geographical reach of different settlements’ functions in the surrounding territory) and the existing socio-economic linkages between them.

The analysis is based on data collected through a questionnaire filled by local government representatives at the basic administrative unit of reference, to check whether specific functions (e.g. primary school, police station, pharmacy, mechanic, lawyer, transport services, etc.) are available or not. The data collected is organized in a spread sheet and the weight of each function is obtained by summing the number of times it occurs (function’s frequency) divided by hundred. Hence basic functions which occur often will show a low weight while rare functions will weigh the most. 

Figure 1. Schematic representation of an ordered Matrix of Functions

In Figure 1, each black square shows the presence of a function. When the weights of all functions present in each administrative unit are summed, the centrality score emerges. The MoF is derived after sorting the settlements by function’s weight and centrality score, establishing a hierarchy of basic, intermediate and central settlements, each one with a set of functions that should be ideally covered. It's assumed that any hierarchical level higher than basic settlements should contain the set of functions of the precedent level(s), plus their own specific functions. Thus, the MoF identifies settlements where functions are missing or whether functions of higher levels are present. In addition, the geographical distribution of the different typologies of settlements helps to visualize how balanced the spatial development of the region is and already gives some indications where investments would be needed. Based on the MoF, an isopleth map is derived showing the levels of centrality from which the spatial structure of the region emerges. It visualizes the territorial linkages of each settlement and identifies clusters of settlements which are strongly interconnected and work cooperatively.

Step A3

Consultative workshops are organized in the region under study, involving national, regional, and local authorities, technical and financial partners, community representatives, and the private sector, among other stakeholders. During these sessions, while participants familiarize themselves with the SDF method, preliminary results are discussed. In particular, areas/settlements are ranked according to their specific development potential, and suggestions are made for their future development.

Step A4

The emerging spatial structure of the region results from the combination of the MoF and of the workshops’ findings. It includes three main elements: 

• Economic Development Areas (EDAs), i.e. clusters of settlements that support and complement each other in terms of socio-economic functions and connectivity, which are considered high priority areas for investment; 
• Development Corridors along the main (existing and proposed) transportation axes enabling connectivity between urban centres, nodal towns and/or EDAs, adjoining countries or regions, etc.;
• Nodal Towns that are urban settlements located strategically at border crossings (international/national gateways) or as nodes between EDAs to improve the performance of a Development Corridor.

Step A5

The SMCE is used to assess the performance of the emerging spatial structure based on a decision atlas on different themes that are relevant to guiding policy documents. Using a geographic information system (GIS), a criteria tree is defined, consisting of the overall objective and sub-objectives of the evaluation (aligned with existing policies), and criteria (according to national standards and norms) that are applied to indicator maps. Each choice in the criteria tree, whether it's the data used for indicators, the norms used for criteria, or the objectives defined, is made explicit in the criteria tree by reference to data sources, policy documents or discourse events so that it adapts to the policy discourse. The criteria tree and priorities of different objectives should be assessed and validated during the consultative workshops. Criteria are used to evaluate the performance of territorial units with respect to the objectives formulated. Indicator maps are standardized raster maps with the pixels’ value between zero (i.e. unsuitable for the objective they aim to measure) and one (i.e. suitable for that objective), aggregated by means of a weighted summation.

Step B1 

Based on the emerging spatial structure, strategic recommendations are formulated on where priority investments should be made. These recommendations form the basis for elaborating the spatial action plans, which should be ideally discussed with the concerned entities, taking into consideration on-going/planned interventions.

Step B2 

Finally, the SDF is politically validated through a workshop bringing together high-level representatives from government and interested partners, and then disseminated.

The Spatial Development Framework was developed in collaboration with UN Habitat.

This article is a teaser of a paper that was co-authored by Luc Boerboom. It provides additional in-depth information about the Spatial Development Framework method, its scientific background and implications, and its practical application in Sudan and Rwanda. You can view and/or download the paper here: The Spatial Development Framework to facilitate urban management in countries with weak planning systems.