Landscapes with a deep history of land use are the legacy of millennial interactions between ecological, social and cultural elements, which can be investigated to obtain new knowledge about our present-day ecosystems. This paper presents the application of a supervised contextual post-classification technique to extract, from a single orthoimage, geospatial objects (classes) representing different temporalities of the same land use in a historical landscape. With a rural area of Sicily as case study and its century-old olive trees as geospatial ‘control points’, we analyse the degree of category similarity between historica lly contingent classes of the same land use. We map and interpret from present space their dynamics of change and persistence over time, cross-validating our results with evidence from local plant microfossils (phytoliths) analysis. We demonstrate how Earth observation products and contextual geospatial analysis are multidimensional sources of information enriching our understanding of past-present landscapes and their biocultural heritage.

Current environmental crises call for an integrated knowledge of landscapes and their ecosystems in a broader sense. This article presents a pedagogical framework for cross-disciplinary landscape research at postgraduate level. The framework is grounded in the use of geospatial epistemic discomfort as a creative force to develop and enhance inquiry skills able to cross and merge disciplinary boundaries. Developed within the Erasmus+ KA2 project “CROSSLAND”, the pedagogical framework is based on the scaffolding of epistemic discomfort through four key didactic elements: 1) cross-disciplinary group work and open-ended assignment, 2) in-field inquiry as pre-training on space-time, 3) replacement of traditional lectures by student-led seminars, 4) GIS labs centred on the exploration of cross-disciplinary portfolios of geospatial approaches and methods given as worked-out examples. Main results from the evaluation of the framework implementation in a Summer School show how learning cross-disciplinarity happened thanks to a scaffolding that allowed, first and foremost, the socialisation of different conceptualisations of space. While students felt at ease with geospatial epistemic discomfort, we can conclude that spatial cognitive processes are powerful in improving abilities beyond the spatial domain. 

The qualitative dimensions of visible features in space can be captured by connecting spatial configurations arranged in a variety of different ways to diverse conceptual spaces. By conceptual spaces, we intend mental concepts describing specific spatial configurations present in a geographical area, defined by the contextual relationships among their constitutive elements. This paper presents a new supervised post-classification method allowing the extraction of semantically complex spatial objects from a single image of the Earth as, for instance, diverse conceptual spaces referring to multiple dimensions of land use (temporal, cultural, social, etc.). Computationally, our method is operationalised by CONTEXTS.py (CS.py), a plugin written in Python for QGIS. CS.py relies on training areas, defined by the user at diverse scales, to identify and extract in the input image conceptual spaces whose spatial contexts have the same spatial features present in the training areas. Applied to a case study on the island of Sicily, where millennial land use dynamics have resulted in a mosaic landscape, CS.py could detect from an orthophoto diverse conceptual spaces of land use in an area ordinarily classified as one land cover, thus expanding the capabilities of geospatial analysis to reach additional qualitative dimensions of information from image data. • CS.py simplifies a supervised contextual post-classification routine in an easy-to-use, practical and accessible QGIS plugin; • CS.py joins a family of tools for supervised object-based classification (e.g. OTB, GRASS), providing, additionally, the possibility to include contextual information as spatial criteria to train the classification routine. • CS.py has broad applications in different disciplines investigating landscape from quantitative and qualitative perspectives, allowing both, as in multiple environments.

The organisation of fields and fences in agriculture that emerged during the Middle Ages and the early modern period was a complex system that combined individual ownership of and communal practices in arable land, meadows and pastures. It was adapted for small and mid-size family-based farming and was a different way to organise agriculture than the medieval estates (demesnes) and the larger coherent fields of the eighteenth century and onwards. The past decade of research in historical geography and economic history has highlighted the origin of this system, which is often referred to as the open-field system; it was open in the sense that it promoted communal farming of primarily arable land. This pre-modern farming system was, however, in many areas a physically closed landscape – a landscape where fences stood out as significant elements. This article investigates the use of fences in a part of early modern western Sweden. The empirical base is a reconstruction of fence-organisations from detailed large-scale maps dating from the mid-seventeenth century. Using historical maps, this study focuses on the collaboration and interaction among farms and settlements. We argue that the open-field system cannot be fully understood without regard to an in-depth analysis of the fences and the institutions holding the complex collaboration together. The occurrence or absence of fences in relation to open-fields involves several questions: What are the characteristics of the fences in the farming systems known as open-field? What can be said about the spatial distributions and connections between the settlements sharing the same open-field? Can agrarian landscapes where fences were prominent elements be considered open-field? The results show that fences appear to be a key factor in understanding settlement patterns and open-fields in Scandinavian regions. A large number of fences created small fenced open-fields. Moreover, the divisions of the arable plots had less importance in the creation of open-fields, which included arable land, meadows and pastures. Instead, cross-settlement collaborations and arrangements are central for the open-fields in the study region. The regional differences within the open-field system provide an understanding of the preconditions and organisation of mixed farming, which combined small-scale arable land cultivation and large-scale pastures.

The livelihoods approach has become dominant for understanding poverty issues and advising on development policies. Spatial perspectives have been increasingly recognised to be important for understanding the increasing complexity and dynamics of livelihoods with regional development, urbanisation and close rural-urban interactions. This study further develops this perspective by highlighting the concepts of geographical context, location and urban hierarchy and adopts a multi-scalar analytical approach. The study examines the rural poor's livelihood strategies in Jilin Province of China based on two surveys conducted with about 3000 households in total and multiple logistic regression analysis. Our results demonstrate that half of the rural poor depend on incomes and livelihood strategies without labour input. From a macro-spatial view, the rural poor living in the Western and Eastern Areas, which have more challenging geographical contexts, are more dependent on subsidy income. From a micro-spatial view, rural livelihoods change, with spatial patterns depending on distance to urban areas and the type of these areas; small and medium-sized urban areas are more important for the rural poor's livelihoods. Geographical context makes these urban effects on rural livelihoods spatially more heterogeneous. Spatial understandings of livelihoods research help to better target and tailor poverty alleviation policies.

This paper investigates the drivers and mechanisms behind the zero lease phenomenon in Sweden, which is characterised by no monetary transfer between landowners and land users, and has been captured in agricultural statistics since the late 1990s. The phenomenon is examined through a theoretical framework which combines rent theory with geographical and historically contextualised views of farming and farmland tenure. We use rent statistics but focus on exploring the geographical dimensions of zero lease farmland in Sweden, mapping spatial variations of rents, the scale of free-leased fields and the geographical location of these fields both at the farm and regional level. Our results show how the zero lease is related to geographical space and ongoing transformation processes in agriculture and rural spaces over time. The paper concludes that the zero lease creates a temporal flexibility for landowners, preserves non-monetary landscape values, and creates opportunities for future farming by preserving landesque capital. This Swedish example illustrates well how, when globally integrated markets force farmers to either restructure, intensify or extensify, and old farming models do not fit the global agri-food systems, farmers find ways to adjust through spatial and temporal means. Seeing the zero lease through farm geographies may suggest opportunities and solutions for making an alternative food and farming future.

Farmers' poverty has long been of global concern, mainly in poor rather than affluent areas. The goal of this paper is to better understand the range of poverty in the context of regional differentiation and to enrich knowledge on farmers' poverty in affluent areas and areas with good natural conditions. A questionnaire survey of poor farmers in the major grain-producing area of Changchun, Northeast China was conducted. Farmers' poverty was studied from income poverty and multidimensional poverty by intertwining qualitative and quantitative methods. The results indicate that low education levels and poor physical health were most prevalent in poor farmers, followed by income poverty and low living standards. Governmental policies and the macroeconomic situation in the agricultural sector, non-agricultural employment, aging, cultivated land, and family size correlated closely with farmers' poverty. The macro changes in policies and global trade liberalization in the agricultural sector impacted farmers' income through the prices of agricultural products and subsidies and influenced the effect of cultivated land. For poor farmers, the effect of employment opportunities in villages was more significant than in urban areas. Aging remains a challenge for farmers' poverty now and in the future.

This paper presents a new geographical analytical model for studies on agricultural landscape change. The model builds on the idea presented by Torsten Hägerstrand that neighbourhood configurations act as filters in change processes. The proposed approach operationalizes this idea of filtering into a geographical interpretation model that combines three different strands of research: ontologies of land use in geographical information science; local spatial contextual analysis of remote sensing data; and agency- and actor-sensitive functional time-space analysis of farming. This approach includes the use of satellite images and makes it possible to infer land-use changes as reactions to long-term policy changes, thus demonstrating how landscape configuration and land use are changing. The model is assessed by applying it to a case study in western Östergötland in central Sweden.

Unlike modern maps, geometric maps lack a coordinate system and contain unsystematic geometric inaccuracies. This paper illuminates four aspects concerning the problem of uniting geographical information technology with old geometric maps. These are as follows: first, the origin of and geometric qualities in the representation of objects in geometric maps; second, the distortions originating from measurement techniques; third, the assumption that it is possible to find points that are the same over time for rectification in Geographic Information System (GIS); and, fourth, the extrapolation of unsystematic geometric distortions when using GIS techniques without any knowledge of the present unsystematic distortions in a map. The article presents the background of Swedish geometric maps and a hypothetical example is used to present the principle problems of using GIS techniques to rectify geometric maps. The conclusion of the paper is that systematic and unsystematic geometric distortions need to be identified and handled separately.