Goals of the task
The aim of this task is to provide a data basis to the different partners of the RP consortium and the involved case cities by collecting, processing and providing significant, project-related information and data. The focus lies on human, economic and physical (geographic) data. Where necessary and as far as this is feasible, the information and data are prepared, edited and completed, analysed, interpreted and made available for further use. Another core task in the methodology oriented RP research approach is the development of new methods for data collecting. The availability and quality of per capita data in the cities are mostly restricted. To support cities in their planning processes a fast and easy to use capture of reliable data is necessary.
Work done to achieve the goals
The data and information were gathered using a variety of sources, a certain part of which could be obtained via the internet and from the available literature. Further specific information was collected with the help of the representatives of different departments in the case cities and through the knowledge of other partners working in the project consortium. In the individual cities investigated, vast differences relating to the amount of available information were noted. Since the available socio-economic data are not specific enough as required in any of the case cities, own empirical research had to be expanded and intensified.
Methodical approach and its use for empirical data gathering
Planning of supply and disposal infrastructure in a city requires a reliable data basis. Specific per capita data on energy and water consumption as well as on wastewater and waste generation are mostly neither available in sufficient quality nor quantity. Therefore the project developed a methodological approach for a fast and easy to use collection of socio-economic data and information on the household level. These data indicated different living standards of surveyed households. Regarding different living standards, it is possible to group several households into different lifestyle classes (LC). The different LCs represent typical patterns in the consumption of water, energy and food as well as in the generation of waste and wastewater. By now recording the inhabited building of the single household, and the classification of all buildings – previously defined within WP2 – one can link a specific building type to the related LC of its residents. The different building types are determiend in a manner that they are also identifiable by using remote sensing methods. As a result, reliable data on the consumption of water, energy and food and the generation of waste and wastewater for a specific area can be generated in a rapid manner.
The developed approach for empirical socio-economic data gathering as it was implemented in Kigali and Da Nang involves the following steps:
In a first step specific building types which represent the main residential areas were defined and these areas were investigated in order to determine appropriate testing areas for the subsequent data gathering activities. The building type definition and suggestions of different testing areas were provided by WP2. According to the criterion of that the buildings are as homogenous as possible the pre-selected areas were analysed and sharpened by the means of satellite images. The appropriateness of the different building types for the methodological approach was evaluated by on-site investigation. Especially with regard to different potential socio-economic classes the testing areas were finally determined.
In a next step, a meta questionnaire – previously developed by IUWA – for socio-economic surveys was adapted to the context of the relevant city. The meta questionnaire contains a large selection of different questions, depending on the cities respective regional context. It comprises the topics, housing and infrastructure, specific information on the households, specific items and devices, expenditures, food and buying habits as well as earnings of the households and additionally the assessment by the interviewer. The questionnaire was transposed into an Excel format that contains control commands for an app. In this format, an extra column can be added for each additional language desired. The free-of-charge survey app GeoODK was programmed and installed on Android tablet computers. The automatic geo-referencing via GPS chip and the possibility to directly take pictures of the buildings and their surroundings are an important advantage. The free-of-charge availability of the used app, the possibility of different – depending on the regional context – compositions of questions and the easy to implement translation, makes this tool simple applicable for every city.
The next step involved the actual implementation of the household surveys in the case cities. The surveys were conducted electronically by using the Android tablet computers. Previously a training was carried out for the local interviewers. Within this training each question of the questionnaire was explained and tested with respect to the meaningfulness and comprehensibility. Furthermore the final adaptation to the local conditions was undertaken, and the interviewers were technically trained in the application of the developed tool in order to implement the survey in the field.
In a final step the gathered data were evaluated in order to derive different socio-economic/ lifestyle classes. These classes then were correlated to the different building types.
Of great importance for the future users from different cities is not only the simplicity of the data collection but also of the data evaluation. If the complexity is too high, nobody will use the method and the tool. That is why a simplified technique to analyse the survey data was developed which consists of the following parts: A quality check of all answers with error-post-editing, the selection and analysis of eligible and comparable questions, and the use of a method for calculating LCs.
Collection of further basic and framework data
Regarding the provision and reuse of information, a data structure was developed and integrated into the IDGard. Through its design and organisation, it is easier to search for relevant documents.
Considerations by IUWA about the meaningful preparation and presentation of the varied city data resulted in a so-called city profile as a synthesis. In their development, the city profiles underwent several rounds of improvement before reaching their final form. They start with a short overview of the city in question, before providing additional background information on the context of the issues being investigated. Moreover, they also served as standardised documents of reference (regarding this information) that the partners in the RP project can draw on. Here, the data and information had been organised and prepared thematically under the topics: administrative and settlement structures; municipal environmental structure, in particular, supply and disposal; and general information, system boundaries and regional embedding. Furthermore, the city profiles provide data and information on economics and statements on demographic and socio-economic topics, as well as specific environmental information (physical data). In addition to the city profiles, a basic framework data file was developed, which contains raw and processed data from a variety of sources (such as statistical yearbooks). This statistical data can be used straightaway for analyses and modelling.
Results so far
All results below contain a reference to the number of the deliverable to which they apply. The complete description of the individual deliverables can be found in the WP summary.
Methodical approach for empirical data gathering
An applicable method was developed which allows all cities a simplified and accelerated reliable socio-economic data collection. The methodical approach will be implemented in the RP knowledge block system which can be used by all interested cities. As supportive element of the methodology approach several instruments were developed and made available. The meta-questionnaire provides a set of different questions in order to analyse different socio-economic aspects according to different regional contexts of interested cities. For on-site surveys, a digital version of the questionnaire was developed to be used electronically on Android devices. A simplified and concise evaluation method was developed for the electronic data especially with regard to derivation of different socio-economic/ lifestyle classes. The developed methodology was implemented within two socio-economic surveys in the cities of Kigali and Da Nang. In 11 investigated areas in Kigali 609 fully completed and geo-referenced questionnaires were collected; in Da Nang in 12 investigated areas 718 fully completed and geo-referenced questionnaires were collected.
The 609 questionnaires filled in within the socio-economic survey in Kigali were evaluated. In total 5 different socio-economic/ lifestyle classes could derived by summarising specific batteries of questions related to household items, household expenditures and official Rwandan social classification (“ubudehe classification system”) and correlating them. The different classes vary from 1 for a very low living standard/ lifestyle up to 5 for a very lavish lifestyle. The different lifestyle classes then were correlated to different building types so that now different building types are linked to the related socio-economic classes of their residents. The same procedure was implemented for the 718 questionnaires in Da Nang. Here 4 different lifestyle classes could be built by correlating data of the topic blocks total expenditures, total financial resources and the complete equipment of the households. The data generated within the socio-economic surveys as well as the derived results were made available for the project partners and the case cities and will be integrated in the data warehouse (WP5) for further processing and use. The results of the surveys, especially the determined testing areas with building types correlated to different lifestyle classes served as basis for the specific sector related data gathering on household level within WP3.
Exemplary some essential results of the Kigali survey are presented below. In Kigali, the investigations about building types showed that three of the five suggested (within WP2) main building types represent predominantly the residential areas of Kigali. The building types that are surveyed in the different testing areas, correlated to the different LCs of their residents, are shown in Tab. 1. In order to reach a more precise allocation of lifestyle classes to building types further analyses are being carried out: (a) further subdivision of the five building types by deeper evaluation of the gathered data (and pictures); (b) correlation of the building types with different UST to take spatial differences into account (e.g. proximity to infrastructure); (c) double-check and alignment with specific data from WP3 for clearer lifestyle class allocation.
Tab. 1: Building types (BT) of Kigali correlated with calculated LCs
The distribution of the single LCs in the surveyed testing areas in Kigali and the exemplary connection of two building types to the related LCs of their residents are illustrated in Fig. 16. (Worked on in Deliverables D-1.4, D-1.7)
Fig. 16: Overview of the testing areas in Kigali with different LCs of the interviewed households and the connection of a building type to the related LC
After applying the developed methodology in Kigali and Da Nang, the transferability to the case city of Assiut will be tested. Due to the unstable conditions in this region, the survey will be conducted by our regional RP partners in Assiut, trained and supported by the IUWA team. (Worked on in Deliverable D-1.4 and specified in WP11, Task 11.2)
Collection of further basic and framework data/ City Profiles
The developed documents as compact sources of information provide the RP partners with the most relevant data and information on the individual case cities and at the same time can be used as a reference to the data and information. (Deliverable D-1.3, D-1.4, D-1.5, D-1.6)
Presenting data and information
The developed basic framework data file contains more than 1,100 datasets. As well as using the data in the data warehouse, its lists of unprocessed data and calculated data provide the partners for a basis with which to conduct analyses and modelling. (Deliverables D-1.4, D-1.5, D-1.7)