Computers, Environment and Urban Systems, Volume 35, Issue 4, July 2011, Pages 333-343
Peng Yue, Yaxing Wei, Liping Di, Lianlian He, Jianya Gong, and Liangpei Zhang
- Provenance improves the understanding of data products in the Web environment.
- Providing provenance using CSW brings interoperability with service-oriented GIS.
- The ebRIM facilitates the arrangement and discovery of provenance.
“One of the earliest investigations of provenance was inspired by applications in GIS in the early 1990’s. Provenance records the processing history of a data product. It provides an information context to help users determine the reliability of data products. Conventional provenance applications in GIS focus on provenance capture, representation, and usage in a stand-alone environment such as a desktop-based GIS software system. They cannot support wide sharing and open access of provenance in a distributed environment. The growth of service-oriented sharing and processing of geospatial data brings some new challenges in provenance-aware applications. One is how to share geospatial provenance in an interoperable way. This paper describes the development of provenance service for geospatial data products using the ebXML Registry Information Model (ebRIM) of a geospatial catalog service, which follows the interface specifications of the OGC Catalogue Services for the Web (CSW). This approach fits well the current service stack of the GIS domain and facilitates the management of geospatial data provenance in an open and distributed environment.”
Plant Pathology, Published online 15 August 2011
P. Spolti, R. M. Valdebenito-Sanhueza, F. F. Laranjeira, and E. M. Del Ponte
“The incidence of sooty blotch/flyspeck (SBFS) and bitter and bull’s eye rots were assessed in a Fuji apple orchard during two seasons. Using a regular sampling design, 252 trees were selected and 20 fruits per tree were sampled at harvest and scored for disease incidence. For bitter and bull’s eye rots, additional assessments were made on all symptomless fruit after a 30-day period of storage. Randomness in the spatial pattern was assessed using beta-binomial analysis of incidence data for three sampling scales (one, three or six adjacent trees as sampling units) and using Spatial Analysis by Distance Indices (sadie) for disease counts for the 3-tree sampling scale. sadie was also used for testing spatial associations between a pair of diseases, between years for the same disease or between rotted and latently infected fruit. Using a toroidal-shifts procedure, 360 maps of disease counts were created based on the observed data, which were further analysed using sadie. Most datasets showed an aggregated spatial pattern, which was more consistent for the two fruit rots than SBFS, which showed distinct patterns depending on the year or method of analysis. The two fruit rots were spatially associated in most situations but SBFS and bull’s eye rot were dissociated in one season. Results from virtual orchards showed that the patterns observed in the original maps may accurately represent those in similar apple-growing areas. Hypotheses regarding aspects of ecology and epidemiology of pathogens studied and potential efficacy of control measures in the region are discussed.”
Applied Geography, Volume 31, Issue 3, July 2011, Pages 881-890
Francesco Geri, Valerio Amici, Duccio Rocchini
- GEOMOD is a straightforward unidirectional linear change modelling tool.
- The model showed great changes with a marked increase in forest surface.
- The surface agreement of the GEOMOD simulation is high.
- The validation phase showed that the simulated spatial arrangement of forests leads to spatial bias.
- There is the need to properly calibrate and validate the model.
“Changes in land use and land cover can lead to irreversible changes in forests that result in overall reductions in biodiversity and loss of elements of high ecological and cultural value. Land use and cover change models can be an important resource for scientists to develop a sustainable land management program. This paper presents a method to assess the accuracy of a forestation predictive model built through GEOMOD. This model was applied to simulate the pattern of land-use change forward in time from 1933 to 2000, in a Mediterranean area, using topographic parameters as predictive variables. In Mediterranean areas, modeling landscape transformation by stressing the relationship between environmental variables and historical anthropogenic transformation, is crucial for many conservation and management practices. In order to analyze the goodness-of-fit of simulation, a cross-classification map was realized by overlaying the map produced by the simulation model and a reference map (CLC 2000). Then, a statistical validation procedure was carried out based on the kappa index of agreement. Results showed that: i) the study area has undergone great changes in the last decades with a marked increase in forest surface, and ii) GEOMOD represents a powerful model tool for land-use change prediction, but it is necessary to properly calibrate and validate the model in order to avoid misleading results.”