Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology professionals.
All knowledge begins as uncommon—unrecognized, undervalued, and sometimes unaccepted. But with the right perspective, the uncommon can become the exceptional.
That’s why Elsevier is dedicated to making uncommon knowledge, common—through validation, integration, and connection. Between our carefully-curated information databases, smart social networks, intelligent search tools, and thousands of scholarly books and journals, we have a great responsibility and relentless passion for making information actionable.
Members:
Resources
Displaying 501 - 505 of 1605Addressing the complexity in non-linear evolution of vegetation phenological change with time-series of remote sensing images
Earth observation based monitoring of change in vegetation phenology and productivity is an important and widely used approach to quantify degradation of ecosystems due to climatic or human influences. Most satellite based studies apply linear or polynomial regression methods for trend detections. In this paper it is argued that natural systems hardly react to human or natural influences in a linear or a polynomial manner. At shorter time-scales of few decades natural systems fluctuate to a certain extent in a non-systematic manner without necessarily changing equilibrium.
Effectiveness 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.
Identification of environmental anomaly hot spots in West Africa from time series of NDVI and rainfall
Studies of the impact of human activity on vegetation dynamics of the Sahelian belt of Africa have been recently re-invigorated by new scientific findings that highlighted the primary role of climate in the drought crises of the 1970s–1980s. Time series of satellite observations revealed a re-greening of the Sahelian belt that indicates no noteworthy human effect on vegetation dynamics at sub continental scale from the 1980s to late 1990s.