Taylor & Francis Group publishes books for all levels of academic study and professional development, across a wide range of subjects and disciplines.
Taylor & Francis Group publishes quality peer-reviewed journals under the Routledge and Taylor & Francis imprints. The newest part of the group, Cogent OA, offers a purely open access program.
Note from Land Portal:
Taylor & Francis Online contains many publications related to land issues, though mostly at the charge of a fee.
Members:
Resources
Displaying 586 - 590 of 661Halland's forests during the last 300 years: a review of Malmström (1939)
Carl Malmström's historical forest maps of the province of Halland, in south-western Sweden, were published over 70 years ago, but are still important to science and conservation. They show the transformation of a seventeenth century landscape of temperate broadleaves to a landscape dominated by open land and heather (Calluna vulgaris) in the nineteenth century, and to a landscape of coniferous forest plantations in the twentieth century. This article summarizes and reviews the original research, first published in Swedish in 1939.
Organic Agriculture Supports Biodiversity and Sustainable Food Production
Biodiversity is vital to several important ecosystem services that ensure sustainability of food production. In organic agriculture, land management practices that promote biodiversity and soil quality are emphasized and the goal is to maintain a sustainable agricultural system. Soil quality or soil health is the foundation for all agriculture and natural plant communities and a primary indicator of sustainable land management. Soil quality is affected by farm management and land use decisions.
Object-based urban detailed land cover classification with high spatial resolution IKONOS imagery
Improvement in remote sensing techniques in spatial/spectral resolution strengthens their applicability for urban environmental study. Unfortunately, high spatial resolution imagery also increases internal variability in land cover units and can cause a ‘salt-and-pepper’ effect, resulting in decreased accuracy using pixel-based classification results. Region-based classification techniques, using an image object (IO) rather than a pixel as a classification unit, appear to hold promise as a method for overcoming this problem.
Boosted decision tree classifications of land cover over Turkey integrating MODIS, climate and topographic data
This study investigates the impact of using different combinations of Moderate Resolution Imaging Spectroradiometer (MODIS) and ancillary datasets on overall and per-class classification accuracies for nine land cover types modified from the classification system of the International Geosphere Biosphere Programme (IGBP).
Land-cover classification in a moist tropical region of Brazil with Landsat Thematic Mapper imagery
This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote-sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images and different classification algorithms, maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA) and object-based classification (OBC), were explored.