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Displaying 506 - 510 of 1605Effectiveness of collaborative map-based decision support tools: Results of an experiment
This article reports on the results of an empirical analysis of the effectiveness of a set of collaborative spatial decision support tools developed to support a land use allocation problem in a peat-meadow polder in the Netherlands. The tools feature spatial multicriteria analysis as the means to make spatially explicit trade-offs between stakeholder objectives in three different ways: as colors on multiple printed maps, qualitatively on a single digital map and quantitatively on a single digital map.
Assessing reference dataset representativeness through confidence metrics based on information density
Land cover maps obtained from classification of remotely sensed imagery provide valuable information in numerous environmental monitoring and modeling tasks. However, many uncertainties and errors can directly or indirectly affect the quality of derived maps. This work focuses on one key aspect of the supervised classification process of remotely sensed imagery: the quality of the reference dataset used to develop a classifier. More specifically, the representative power of the reference dataset is assessed by contrasting it with the full dataset (e.g. entire image) needing classification.
Integrating soil survey, land use management and political ecology: A case study in a border area between Peru and Ecuador
In Latin America countries, competition for access to natural resources among different groups has been a major reason for the outburst of violence over the last decades. One of the main aims of the political ecology concerns the understanding of the environmental conditions that can underlies the social conflict among people. Such understanding needs to be based on a detailed investigation of the natural resources of the landscape, mainly the soils.
Assessing land cover and soil quality by remote sensing and geographical information systems (GIS)
Precise soil quality assessment is critical for designing sustainable agriculture policies, restoring degraded soils, carbon (C) modeling, and improving environmental quality. Although the consequences of soil quality reduction are generally recognized, the spatial extent of soil degradation is difficult to determine, because no universal equation or soil quality prediction model exists that fits all ecoregions. Furthermore, existing soil organic C (SOC) models generate estimates with uncertainties that may exceed 50%.
LandCaRe DSS – An interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies
Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap.