By Ian P. Williamson, Abbas Rajabifard, Mary-Ellen F. Feeney
content material: Pt. 1. creation and heritage --
1. SDIs --
environment the Scene --
2. Spatial info Infrastructures: idea, Nature and SDI Hierarchy --
Pt. 2. From international SDI to neighborhood SDI --
three. international tasks --
four. neighborhood SDIs --
five. SDI Diffusion --
A neighborhood Case examine with Relevance to different Levels
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Additional resources for Developing spatial data infrastructures : from concept to reality
A. 2001. Monitoring salinity from remote sensing data. In: Proceedings of the 1st Workshop of the EARSeL Special Interest Group on Remote Sensing for Developing Countries, Eds. R. M. De Vliegher. Ghent University, Belgium, pp. 359–368. A. and C. Suárez. 1972. Condiciones de salinidad y alcalinidad en la depresión de Quibor, Estado Lara. Revista Agronomía Tropical XXII (4):405–428. 2008 10:54am Compositor Name: VAmoudavally Spectral Behavior of Salt Types Graciela Metternicht and J. 2 Introduction ..........................................................................................................................
2001. Assessing temporal and spatial changes of salinity using fuzzy logic, remote sensing and GIS: Foundations of an expert system. Ecological Modelling 144:163–177. I. A. 1996. Modelling salinity–alkalinity classes for mapping salt-affected topsoils in the semi-arid valleys of Cochabamba (Bolivia). ITC Journal 2:125–135. I. A. 1997. Spatial discrimination of salt- and sodium-affected soil surfaces. International Journal of Remote Sensing 18:2571–2586. I. A. 2003. Remote sensing of soil salinity: Potentials and constraints.
1 CRISP CLASSIFICATIONS The most common approaches to identify and classify salt-affected soils are based on strict information classes with crisp boundaries, drawn either from soil properties such as soil reaction (pH), electrical conductivity (EC), exchangeable sodium percentage (ESP), and sodium adsorption ratio (SAR), or from the ratios of anions present in the soil saturation extract (Metternicht and Zinck, 2003). S. 1. Basic thresholds commonly accepted are >4 dS mÀ1 EC to discriminate saline soils, >15% ESP to discriminate alkaline soils, and a combination of the former values to discriminate saline–alkaline soils.
Developing spatial data infrastructures : from concept to reality by Ian P. Williamson, Abbas Rajabifard, Mary-Ellen F. Feeney