A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach |
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Affiliation: | 1. Istanbul Okan University, Institute of Science, Land Management and Land Use Program, 34959, Tuzla, Istanbul, Turkey;2. Istanbul Okan University, Geomatics Engineering Department, 34959, Tuzla, Istanbul, Turkey;1. Department of Economics and Statistics “Cognetti de Martiis”, University of Turin, Italy;2. Department of Agriculture, Forest and Food Sciences, University of Turin, Italy;3. Research Centre for Rural Development of Hilly Areas, University of Turin, Italy;1. Geothermal and Renewal Energy Institute of the High-Temperature Joint Institute of the Russian Academy of Sciences, Makhachkala, Dagestan, Russia Federation;2. Dagestan State University, Makhachkala, Dagestan, Russian Federation;3. Azerbaijan Technical University, Department of Industrial Ecology and Industrial Safety Properties of Aqueous Systems, Baku, Azerbaijan |
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Abstract: | A Spatial Data Infrastructure (SDI) enables the effective spatial data flow between providers and users for their prospective land use analyses. The need for an SDI providing soil and land use inventories is crucial in order to optimize sustainable management of agricultural, meadow and forest lands. In an SDI where datasets are static, it is not possible to make quick decisions about land use. Therefore, SDIs must be enhanced with online data flow and the capabilities to store big volumes of data. This necessity brings the concepts of the Internet of Things (IoT) and Big Data (BD) into the discussion.Turkey needs to establish an SDI to monitor and manage its rural lands. Even though Turkish decision-makers and scientists have constructed a solid national SDI standardization, a conceptual model for rural areas has not been developed yet. In accordance with the international agreements, this model should adopt the INSPIRE Directive and Land Parcel Identification System (LPIS) standards. In order to manage rural lands in Turkey, there are several legislations which characterize the land use planning, land classification and restrictions. Especially, the Soil Protection and Land Use Law (SPLUL) enforces to use a lot and a variety of land use parameters that should be available in a big rural SDI. Moreover, this model should be enhanced with IoT, which enables to use of smart sensors to collect data for monitoring natural occurrences and other parameters that may help to classify lands.This study focuses on a conceptual model of a Turkish big rural SDI design that combines the sensor usage and attribute datasets for all sorts of rural lands. The article initially reviews Turkish rural reforms, current enterprises to a national SDI and sensor-driven agricultural monitoring. The suggested model integrates rural land use types, such as agricultural lands, meadowlands and forest lands. During the design process, available data sets and current legislation for Turkish rural lands are taken into consideration. This schema is associated with food security databases (organic and good farming practices), non-agricultural land use applications and local/European subsidies in order to monitor the agricultural parcels on which these practices are implemented. To provide a standard visualization of this conceptual schema, the Unified Modeling Language (UML) class diagrams are used and a supplementary data dictionary is prepared to make clear definitions of the attributes, data types and code lists used in the model.This conceptual model supports the LPIS, ISO 19156 International Standard (Geographic Information: Observations and Measurements) catalogue and INSPIRE data theme specifications due to the fact that Turkey is negotiating the accession to EU; however, it also provides a local understanding that enables to manage rural lands holistically for sustainable development goals. It suggests an expansion for the sensor variety of Turkish agricultural monitoring project (TARBIL) and it specifies a rural theme for Turkish National SDI (TUCBS). |
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Keywords: | Spatial data infrastructures Big data Internet of things Rural land use INSPIRE LPIS |
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