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 176 - 180 of 661Automatic land-cover update approach integrating iterative training sample selection and a Markov Random Field model
Land-cover updating from remote-sensing data is an effective means of obtaining timely land-cover information. An automatic approach integrating iterative training sample selection (ITSS) and a Markov Random Field (MRF) model is proposed in this study to overcome the land-cover update problem when no previous remote-sensing data corresponding to the land-cover data are available.
Assessing soil erosion in Europe based on data collected through a European network
The European Commission Directorate-General for the Environment (DG Environment) and the European Environmental Agency (EEA) have identified soil organic matter conservation and mitigation of soil loss by erosion as priorities for the collection of policy-relevant soil data at the European scale. In order to support European Union (EU) soil management policies, soil quality indicators are required that can be applied using harmonized data for the EU Member States.
Investigating syndromes of agricultural land degradation through past trajectories and future scenarios
In the last decades, due to climate changes, soil deterioration and land use/land cover (LULC) changes, land degradation (LD) has become one of the most important issues at the global, regional and local scale. In concrete terms, LD determines a reduction in the productivity of a territory and in its capacity of providing ecosystem goods and services. “Syndromes” of LD can be assessed in the past, and scenarios, conversely, can be developed for the future, as information baselines for sustainable land management strategies and interventions.
multi-scale accuracy assessment of the MODIS irrigated agriculture data-set (MIrAD) for the state of Nebraska, USA
Accurate and timely information about the geographic distribution of irrigated cropland is important for a range of applications including crop assessments, water resources management, drought monitoring, and environmental modeling.
Incorporating road and parcel data for object-based classification of detailed urban land covers from NAIP images
A map showing various urban features, such as buildings, roads, and vegetation, is useful for a variety of urban planning applications. The objective of this study was to incorporate road and parcel GIS data as well as relevant expert knowledge to classify different urban land covers from 1-meter, 4-band NAIP images. Based on a hybrid simultaneous-classification and one-by-one-classification approach, a total of 14 urban classes are classified.