A B S T R A C TWe are increasingly confronted with severe social and economic impacts of environmental degradation all over the world. From a valuation perspective, environmental problems and conflicts originate from trade-offs http://dx.Ecosystem Services (xxxx) xxxx-xxxx 2212-0416/ Ecosystem services Intrinsic value Benefits of nature Quality of life Participation Social and environmental justice Decision supportbetween values. The urgency and importance to integrate nature's diverse values in decisions and actions stand out more than ever.Valuation, in its broad sense of 'assigning importance', is inherently part of most decisions on natural resource and land use. Scholars from different traditions -while moving from heuristic interdisciplinary debate to applied transdisciplinary science-now acknowledge the need for combining multiple disciplines and methods to represent the diverse set of values of nature. This growing group of scientists and practitioners share the ambition to explore how combinations of ecological, socio-cultural and economic valuation tools can support real-life resource and land use decision-making.The current sustainability challenges and the ineffectiveness of single-value approaches to offer relief demonstrate that continuing along a single path is no option. We advocate for the adherence of a plural valuation culture and its establishment as a common practice, by contesting and complementing ineffective and discriminatory single-value approaches. In policy and decision contexts with a willingness to improve sustainability, integrated valuation approaches can be blended in existing processes, whereas in contexts of power asymmetries or environmental conflicts, integrated valuation can promote the inclusion of diverse values through action research and support the struggle for social and environmental justice.The special issue and this editorial synthesis paper bring together lessons from pioneer case studies and research papers, synthesizing main challenges and setting out priorities for the years to come for the field of integrated valuation.

Abstract:The expansion of cities entails the abandonment of forest and agricultural lands, and these lands' conversion into urban areas, which results in substantial impacts on ecosystems. Monitoring these changes and planning urban development can be successfully achieved using multitemporal remotely sensed data, spatial metrics, and modeling. In this paper, urban land use change analysis and modeling was carried out for the Concelhos of Setúbal and Sesimbra in Portugal. An existing land cover map for the year 1990, together with two derived land cover maps from multispectral satellite images for the years 2000 and 2006, were utilized using an object-oriented classification approach. Classification accuracy assessment revealed satisfactory results that fulfilled minimum standard accuracy levels. Urban land use dynamics, in terms of both patterns and quantities, were studied using selected landscape metrics and the Shannon Entropy index. Results show that urban areas increased by 91.11% between 1990 and 2006. In contrast, the change was only 6.34% between 2000 and 2006. The entropy value was 0.73 for both municipalities in 1990, indicating a high rate of urban sprawl in the area. In 2006, this value, for both Sesimbra and Setúbal, reached almost 0.90. This is demonstrative of a tendency toward intensive urban sprawl. Urban land use change for the year 2020 was modeled using a Cellular Automata based approach. The predictive power of the model was successfully validated using Kappa variations. Projected land cover changes show a growing tendency in urban land use, which might threaten areas that are currently reserved for natural parks and agricultural lands.

This study modeled the urban growth in the Greater Cairo Region (GCR), one of the fastest growing mega cities in the world, using remote sensing data and ancillary data. Three land use land cover (LULC) maps (1984, 2003 and 2014) were produced from satellite images by using Support Vector Machines (SVM). Then, land cover changes were detected by applying a high level mapping technique that combines binary maps (change/no-change) and post classification comparison technique. The spatial and temporal urban growth patterns were analyzed using selected statistical metrics developed in the FRAGSTATS software. Major transitions to urban were modeled to predict the future scenarios for year 2025 using Land Change Modeler (LCM) embedded in the IDRISI software. The model results, after validation, indicated that 14% of the vegetation and 4% of the desert in 2014 will be urbanized in 2025. The urban areas within a 5-km buffer around: the Great Pyramids, Islamic Cairo and Al-Baron Palace were calculated, highlighting an intense urbanization especially around the Pyramids; 28% in 2014 up to 40% in 2025. Knowing the current and estimated urbanization situation in GCR will help decision makers to adjust and develop new plans to achieve a sustainable development of urban areas and to protect the historical locations.

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Abstract:The extension of urban perimeter markedly cuts available productive land. Hence, studies in urban sprawl analysis and modeling play an important role to ensure sustainable urban development. The urbanization pattern of the Greater Asmara Area (GAA), the capital of Eritrea, was studied. Satellite images and geospatial tools were employed to analyze the spatiotemporal urban landuse changes. Object-Based Image Analysis (OBIA), Landuse Cover Change (LUCC) analysis and urban sprawl analysis using Shannon Entropy were carried out. The Land Change Modeler (LCM) was used to develop a model of urban growth. The Multi-layer Perceptron Neural Network was employed to model the transition potential maps with an accuracy of 85.9% and these were used as an input for the 'actual' urban modeling with Markov chains. Model validation was assessed and a scenario of urban land use change of the GAA up to year 2020 was presented. The result of the study indicated that the built-up area has tripled in size (increased by 4,441 ha) between 1989 and 2009. Specially, after year 2000 urban sprawl in GAA caused large scale encroachment on high potential agricultural lands and plantation cover. The scenario for year 2020 shows an increase of the built-up areas by 1,484 ha (25%) which may cause further loss. The study indicated that the land allocation system in the GAA overrode the landuse plan, which caused the loss of agricultural land and plantation cover. The recommended policy options might support decision makers to resolve further loss of agricultural land and plantation cover and to achieve sustainable urban development planning in the GAA. OPEN ACCESSRemote Sens. 2011, 3 2149

BackgroundAccess to healthcare services has an essential role in promoting health equity and quality of life. Knowing where the places are and how much of the population is covered by the existing healthcare network is important information that can be extracted from Geographical Information Systems (GIS) and used in effective healthcare planning. The aim of this study is to measure the geographic accessibility of population to existing Healthcare Centers (HC), and to estimate the number of persons served by the health network of Mozambique.MethodsHealth facilities’ locations together with population, elevation, and ancillary data were used to model accessibility to HC using GIS. Two travel time scenarios used by population to attend HC were considered: (1) Driving and; and (2) Walking. Estimates of the number of villages and people located in the region served, i.e. within 60 min from an HC, and underserved area, i.e. outside 60 min from an HC, are provided at national and province level.ResultsThe findings from this study highlight accessibility problems, especially in the walking scenario, in which 90.2 % of Mozambique was considered an underserved area. In this scenario, Maputo City (69.8 %) is the province with the greatest coverage of HC. On the other hand, Tete (93.4 %), Cabo Delgado (93 %) and Gaza (92.8 %) are the provinces with the most underserved areas. The driving scenario was less problematic, with about 66.9 % of Mozambique being considered a served area. We also found considerable regional disparities at the province level for this scenario, ranging from 100 % coverage in Maputo City to 48.3 % in Cabo Delgado. In terms of population coverage we found that the problem of accessibility is more acute in the walking scenario, in which about 67.3 % of the Mozambican population is located in underserved areas. For the driving scenario, only 6 % of population is located in underserved areas.ConclusionsThis study highlights critical areas in Mozambique in which HC are lacking when assessed by walking and driving travel time distance. The majority of Mozambicans are located in underserved areas in the walking scenario. The mapped outputs may have policy implications and can be used for future decision making processes and analysis.Trial registrationNot applicable.

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