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Helle Skånes

Bio: Helle Skånes is an academic researcher from Stockholm University. The author has contributed to research in topics: Land use, land-use change and forestry & Digitization. The author has an hindex of 6, co-authored 11 publications receiving 3299 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors track some of the major myths on driving forces of land cover change and propose alternative pathways of change that are better supported by case study evidence, concluding that neither population nor poverty alone constitute the sole and major underlying causes of land-cover change worldwide.
Abstract: Common understanding of the causes of land-use and land-cover change is dominated by simplifications which, in turn, underlie many environment-development policies. This article tracks some of the major myths on driving forces of land-cover change and proposes alternative pathways of change that are better supported by case study evidence. Cases reviewed support the conclusion that neither population nor poverty alone constitute the sole and major underlying causes of land-cover change worldwide. Rather, peoples’ responses to economic opportunities, as mediated by institutional factors, drive land-cover changes. Opportunities and

3,330 citations

Journal ArticleDOI
TL;DR: In this article, the authors demonstrate the value of the multivariate method, Principal Components Analysis (PCA) on data relating to landscape elements, to determine the relative directions of change and illustrate landscape dynamics.

95 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a methodological synthesis of two congruent approaches into a common landscape change trajectory analysis and the assessment of landscape dynamics and sustainability, focusing on the retrospective relationship between the past and the present-day landscape patterns and associated key biotopes.

77 citations

Journal ArticleDOI
TL;DR: In this article, the influence of environmental factors on the present distribution, age and abundance of oaks in a unique forest site in south-western Finland was studied using Landscape Change Trajectory Analysis (LCTA) approach.

32 citations

Journal ArticleDOI
TL;DR: In this paper, the authors combine historical maps and satellite derived data to reconstruct the development of a Swedish boreal landscape over the past 300 years, and analyze landscape development in cross-tabulation matrixes, building change trajectories.

23 citations


Cited by
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Journal ArticleDOI
28 Nov 2003
TL;DR: In this article, the authors highlight the complexity of land-use/cover change and propose a framework for a more general understanding of the issue, with emphasis on tropical regions, and argue that a systematic analysis of local-scale land use change studies, conducted over a range of timescales, helps to uncover general principles that provide an explanation and prediction of new land use changes.
Abstract: We highlight the complexity of land-use/cover change and propose a framework for a more general understanding of the issue, with emphasis on tropical regions. The review summarizes recent estimates on changes in cropland, agricultural intensification, tropical deforestation, pasture expansion, and urbanization and identifies the still unmeasured land-cover changes. Climate-driven land-cover modifications interact with land-use changes. Land-use change is driven by synergetic factor combinations of resource scarcity leading to an increase in the pressure of production on resources, changing opportunities created by markets, outside policy intervention, loss of adaptive capacity, and changes in social organization and attitudes. The changes in ecosystem goods and services that result from land-use change feed back on the drivers of land-use change. A restricted set of dominant pathways of land-use change is identified. Land-use change can be understood using the concepts of complex adaptive systems and transitions. Integrated, place-based research on land-use/land-cover change requires a combination of the agent-based systems and narrative perspectives of understanding. We argue in this paper that a systematic analysis of local-scale land-use change studies, conducted over a range of timescales, helps to uncover general principles that provide an explanation and prediction of new land-use changes.

2,491 citations

Book
24 Nov 2003
TL;DR: The Millennium Ecosystem Assessment (MEA) as discussed by the authors is a conceptual framework for analysis and decision-making of ecosystems and human well-being that was developed through interactions among the experts involved in the MA as well as stakeholders who will use its findings.
Abstract: This first report of the Millennium Ecosystem Assessment describes the conceptual framework that is being used in the MA. It is not a formal assessment of the literature, but rather a scientifically informed presentation of the choices made by the assessment team in structuring the analysis and framing the issues. The conceptual framework elaborated in this report describes the approach and assumptions that will underlie the analysis conducted in the Millennium Ecosystem Assessment. The framework was developed through interactions among the experts involved in the MA as well as stakeholders who will use its findings. It represents one means of examining the linkages between ecosystems and human well-being that is both scientifically credible and relevant to decision-makers. This framework for analysis and decision-making should be of use to a wide array of individuals and institutions in government, the private sector, and civil society that seek to incorporate considerations of ecosystem services in their assessments, plans, and actions.

2,427 citations

Journal ArticleDOI
11 Oct 2012-Nature
TL;DR: A global-scale assessment of intensification prospects from closing ‘yield gaps’, the spatial patterns of agricultural management practices and yield limitation, and the management changes that may be necessary to achieve increased yields finds that global yield variability is heavily controlled by fertilizer use, irrigation and climate.
Abstract: In the coming decades, a crucial challenge for humanity will be meeting future food demands without undermining further the integrity of the Earth’s environmental systems1, 2, 3, 4, 5, 6. Agricultural systems are already major forces of global environmental degradation4, 7, but population growth and increasing consumption of calorie- and meat-intensive diets are expected to roughly double human food demand by 2050 (ref. 3). Responding to these pressures, there is increasing focus on ‘sustainable intensification’ as a means to increase yields on underperforming landscapes while simultaneously decreasing the environmental impacts of agricultural systems2, 3, 4, 8, 9, 10, 11. However, it is unclear what such efforts might entail for the future of global agricultural landscapes. Here we present a global-scale assessment of intensification prospects from closing ‘yield gaps’ (differences between observed yields and those attainable in a given region), the spatial patterns of agricultural management practices and yield limitation, and the management changes that may be necessary to achieve increased yields. We find that global yield variability is heavily controlled by fertilizer use, irrigation and climate. Large production increases (45% to 70% for most crops) are possible from closing yield gaps to 100% of attainable yields, and the changes to management practices that are needed to close yield gaps vary considerably by region and current intensity. Furthermore, we find that there are large opportunities to reduce the environmental impact of agriculture by eliminating nutrient overuse, while still allowing an approximately 30% increase in production of major cereals (maize, wheat and rice). Meeting the food security and sustainability challenges of the coming decades is possible, but will require considerable changes in nutrient and water management.

2,099 citations

Journal ArticleDOI
TL;DR: In this paper, the performance of the random forest classifier for land cover classification of a complex area is explored based on several criteria: mapping accuracy, sensitivity to data set size and noise.
Abstract: Land cover monitoring using remotely sensed data requires robust classification methods which allow for the accurate mapping of complex land cover and land use categories. Random forest (RF) is a powerful machine learning classifier that is relatively unknown in land remote sensing and has not been evaluated thoroughly by the remote sensing community compared to more conventional pattern recognition techniques. Key advantages of RF include: their non-parametric nature; high classification accuracy; and capability to determine variable importance. However, the split rules for classification are unknown, therefore RF can be considered to be black box type classifier. RF provides an algorithm for estimating missing values; and flexibility to perform several types of data analysis, including regression, classification, survival analysis, and unsupervised learning. In this paper, the performance of the RF classifier for land cover classification of a complex area is explored. Evaluation was based on several criteria: mapping accuracy, sensitivity to data set size and noise. Landsat-5 Thematic Mapper data captured in European spring and summer were used with auxiliary variables derived from a digital terrain model to classify 14 different land categories in the south of Spain. Results show that the RF algorithm yields accurate land cover classifications, with 92% overall accuracy and a Kappa index of 0.92. RF is robust to training data reduction and noise because significant differences in kappa values were only observed for data reduction and noise addition values greater than 50 and 20%, respectively. Additionally, variables that RF identified as most important for classifying land cover coincided with expectations. A McNemar test indicates an overall better performance of the random forest model over a single decision tree at the 0.00001 significance level.

1,901 citations

Journal ArticleDOI
TL;DR: In this paper, the authors presented the first characterization of terrestrial biomes based on global patterns of sustained, direct human interaction with ecosystems and identified the anthropogenic biomes through empirical analysis of global population, land use, and land cover.
Abstract: Humans have fundamentally altered global patterns of biodiversity and ecosystem processes. Surprisingly, existing systems for representing these global patterns, including biome classifications, either ignore humans altogether or simplify human influence into, at most, four categories. Here, we present the first characterization of terrestrial biomes based on global patterns of sustained, direct human interaction with ecosystems. Eighteen “anthropogenic biomes” were identified through empirical analysis of global population, land use, and land cover. More than 75% of Earth's ice-free land showed evidence of alteration as a result of human residence and land use, with less than a quarter remaining as wildlands, supporting just 11% of terrestrial net primary production. Anthropogenic biomes offer a new way forward by acknowledging human influence on global ecosystems and moving us toward models and investigations of the terrestrial biosphere that integrate human and ecological systems.

1,452 citations