This report presents selected results of a representative survey in rural areas. It was conducted in municipalities with less than 50,000 inhabitants in autumn 2016, in Germany. The net sample comprised 1,717 people aged 18 and over. The survey was embedded in the pilot project "Monitoring Rural Areas", which focused on living conditions in rural areas from the perspective of official statistics and from the perspective of the population. In the pilot project, four types of rural areas were defined on the basis of the dimensions "(objective) rurality" and "socio-economic situation". A subsample was drawn for each type of rural area. Three new survey instruments were developed for the survey on living conditions in rural areas – firstly: a definition of an area within a radius of ten kilometres around an apartment/house as a (social) space whose assessment provides useful information on living conditions in rural areas; secondly: the operationalisation of this assessment through two open questions on the good and not so good aspects of an area, with the hint for respondents to also think about their private everyday life and, if applicable, their gainful employment when answering; thirdly: respondents’ subjective assessment of how rural or urban the area within a five-kilometre radius of their apartment/house was, using a seven-point scale. As a new instrument of data analysis, the overall evaluation (attitude) towards the area was constructed from the positive and negative individual evaluations, taking into account the possible ambivalence of the attitude. The individual evaluations were analysed from the answers to the two open questions using a very differentiated coding scheme. The development of the new instruments and their foundations are a focus of the report. The analysis of the data collected on the basis of the new instruments is the second focus. Among the more than 8,000 coded utterances, 28 percent are negative and 72 percent positive. One major reason for the significantly higher number of positive evaluations: almost one third of the respondents did not express any negative evaluation, the attitude towards their area is more affective than cognitive. On average, the overall rating of the area exhibits a two-peak distribution: Respondents tend to have a very positive or average attitude towards their area. Only a very small proportion expressed a clearly negative view of their area. In a regression analysis, the individual factors "life satisfaction", "age" and the spatial factor "number of existing facilities in an area" have a comparatively greater influence on attitudes towards the area than the socio-economic situation in the district and the subjective rurality. The latter two seem to be useful as rough indicators of living conditions. The objective rurality determined at the district level as very rural and rather rural does not exert any influence on the attitude towards the area in the analysis. As a further analytical tool, a contrast group analysis is applied and attachment to an area is discussed as a possible attitudinal factor. Whether, on average, the assessment of certain issues influences attitudes could only be analysed for respondents who expressed both positive and negative opinions about their area. It can be seen that the frequency of statements on a topic does not directly indicate its influence on the attitude towards the area. A relatively greater influence on attitudes was exerted by evaluations on the topics of health care, educational facilities and leisure/culture. Using 128 categories of the category scheme the specific aspects under which an area was assessed are captured. The highlighted specific considerations that the interviewees made to evaluate their area relate to their practical private and working life: "local supply/shops", "commute to work"; to symbolically charged nature-related phenomena: "landscape", "nature" and the context of their personal/social and natural environment: "tranquillity", "rural". The coding categories were grouped into analysis categories according to topic: first into 39 categories on the so-called 2nd level and then into 16 categories on the 1st level. The grouping of coding categories into analysis categories can also be done somewhat differently, depending on the aspect of analysis. This is shown, among other things, by means of analysis results that are oriented towards the structuring of the Third Report of the Federal Government on the Development of Rural Areas (BMEL 2020)