A minimum cross entropy model to generate disaggregated agricultural data at the local level

This work presents an entropy approach to disaggregate agricultural data at a local level. It comprises two different steps. In a first one, an information prior at disaggregated level based on experts’ opinions, available cartography of land use and biophysical data is created. In a second step, it’s used a minimum cross entropy process in order to manage these information inputs and to guaranty a solution compatible with all the different restrictions. The model was applied to the region of Algarve in the year of 1999, in order to disaggregate the data at the pixel and county level. Results show that the model was able to provide some satisfactory results since the estimated values obtained for the different areas revealed a good approximation to the true values. These results were then analyzed and provided a new insight about the policies’ consequences in the territory.Minimum cross entropy, data disaggregation, local level, Algarve, agricultural policies, Agricultural and Food Policy, C11, C81, Q15, R14,

Geographical downscaling of outputs provided by an economic farm model calibrated at the regional level

International audienceThere is a strong need for accurate and spatially referenced information regarding policy making and model linkage. This need has been expressed by land users, and policy and decision makers in order to estimate both spatially and locally the impacts of European policy (like the Common Agricultural Policy) and/or global changes on farm-groups. These entities are defined according to variables such as altitude, economic size and type of farming (referring to land uses). European farm-groups are provided through the Farm Accountancy Data Network (FADN) as statistical information delivered at regional level. The aim of the study is to map locally farm-group probabilities within each region. The mapping of the farm-groups is done in two steps: (1) by mapping locally the co-variables associated to the farm-groups, i.e. altitude and land uses; (2) by using regional FADN data as a priori knowledge for transforming land uses and altitude information into farm-groups location probabilities within each region. The downscaling process focuses on the land use mapping since land use data are originally point information located every 18 km. Interpolation of land use data is done at 100 m by using co-variables like land cover, altitude, climate and soil data which are continuous layers usually provided at fine resolution. Once the farm-groups are mapped, European Policy and global changes scenarios are run through an agro-economic model for assessing environmental impacts locally

Sustainable Development Data Availability on the Internet

Defining what Sustainability and Sustainable Development mean is a critical task, as they are global objectives, which cover different aspects of life often difficult to quantify and describe. Talking about sustainable development means dealing with the development and implementation of SD strategies at international as well as at local level. With this regard, SD information plays a key role in monitoring SD performances at different administration levels. The aim of this paper is to give an overview of sustainable data availability on the internet at international, European, national and regional level. The paper is novel in the fact that the attention of the whole analysis focused on internet, considered as the principal mean for accessing data. In fact, the web has become through the years a fundamental tool for exchanging information amongst people, organisations, institutes, governments, thanks to its easy accessibility for a wide knowledge exchange. Sustainable development data collected at different administrative levels are classified and processed according to different methods and procedures; they are gathered at different scales, in different periods and they have a different frequency of updating. Data accuracy and meta-information on available data considerably vary, too. Few organisations at the international and at the European level such as, for example, World Bank, United Nations, OECD, FAO, Eurostat, EEA committed themselves to process information belonging to different sources aiming at standardising and producing comparable data sets for several nations and regions. Following the above considerations, various international, European and national organisations’ databases were investigated in order to check the availability of data at different administrative levels, mostly focusing on those sectors considered as pillars for the definition and monitoring of the implementation of the EU Sustainable Development Strategy, as pointed out in the Communication of the EC SEC(2005) 161 final.Sustainability, Indicators, Regional Development, Internet, Database

Geoscience after IT: Part L. Adjusting the emerging information system to new technology

Coherent development depends on following widely used standards that respect our vast legacy of existing entries in the geoscience record. Middleware ensures that we see a coherent view from our desktops of diverse sources of information. Developments specific to managing the written word, map content, and structured data come together in shared metadata linking topics and information types

A population density grid for Spain

This is an author's accepted manuscript of an article published in "International Journal of Geographical Information Science"; Volume 27, Issue 12, 2013; copyright Taylor & Francis; available online at: http://www.tandfonline.com/doi/abs/10.1080/13658816.2013.799283This article describes a high-resolution land cover data set for Spain and its application to dasymetric population mapping (at census tract level). Eventually, this vector layer is transformed into a grid format. The work parallels the effort of the Joint Research Centre (JRC) of the European Commission, in collaboration with Eurostat and the European Environment Agency (EEA), in building a population density grid for the whole of Europe, combining CORINE Land Cover with population data per commune. We solve many of the problems due to the low resolution of CORINE Land Cover, which are especially visible with Spanish data. An accuracy assessment is carried out from a simple aggregation of georeferenced point population data for the region of Madrid. The bottom-up grid constructed in this way is compared to our top-down grid. We show a great improvement over what has been reported from commune data and CORINE Land Cover, but the improvements seem to come entirely from the higher resolution data sets and not from the statistical modeling in the downscaling exercise. This highlights the importance of providing the research community with more detailed land cover data sets, as well as more detailed population data. The dasymetric grid is available free of charge from the authors upon request.The authors acknowledge financial support from the BBVA Foundation-Ivie research programme and the first author also acknowledges support from the Spanish Ministry of Science and Technology, ECO2011-23248 project. Results mentioned, but not shown, are available from the authors upon request. The grid numbers are also available from the authors.Goerlich Sanchis, FJ.; Cantarino Martí, I. (2013). A population density grid for Spain. International Journal of Geographical Information Science. 27(12):1-17. https://doi.org/10.1080/13658816.2013.799283S117271

Land-use changes in the canary archipelago using the CORINE Data: a retrospective analysis

The relationships between territorial governance and the pursuit of sustainable development are evidenced to be critical. Exploratory tools, like Geographic Information Systems (GIS), enable us to comprehend the patterns, dynamics, and parameters of land-use changes over the years. The results from such studies could be used in the design of a sustainable territorial governance strategy. Contextually, a study has been conducted based on the changes that occurred in land uses in the Canary Archipelago in the years 1990, 2000, 2012, and 2018 using CORINE (Coordination of Information on the Environment) data. Even if most of the land uses have been stable over the analyzed period, the investigation shows a decrease in agricultural areas. By contrast, it is possible to verify an increase in semi-natural areas and urban agglomerations. Moreover, the authors believe that an assessment of the land-use changes on these ultra-peripheral areas will also enable us to disclose some obstacles and opportunities for sustained development.FCT—Foundation for Science and Technology to VALORIZAinfo:eu-repo/semantics/publishedVersio