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In order to satisfy the social demand for freely obtainable and usable soil information and resources, several national and international soil databases have already been available online for those who are interested. To establish a proper infrastructure for geospatial data with online sharing systems, it is essential that their information is auth...
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... Drought has been defined through different academic expertise reliant on the specific area of research interests, as a natural hazard phenomenon that can be resulted from an abnormally low amount of water at the landatmosphere interface due to the considerable scarcity of precipitation (meteorological drought) which influences all aspects of the water cycle and can spread to soil moisture (agricultural drought), stream flow, lake levels, and groundwater as it persists (hydrological drought) (Wilhite, 2000;Balla et al., 2016;Berg et al., 2018). However, different definitions have been developed to classify systems that define drought. ...
In this research, a climatic synthesis was built to assess the climatic parameters of the Oued Souf Valley through the meteorological data obtained from Guemar station (airport). It was revealed that the hydrological year of Oued Souf Valley is branded by the presence of a dry period and the total absence of a wet period over the year, even during January, when it was observed to have the lowest temperature and highest precipitation, which classified it as a Saharan climate (Hyper arid). The irregularity and the scarcity of precipitation, high temperatures and extremely high evapotranspiration had significant repercussions on surface runoff and infiltration which implies a high pressure on the water resources of Oued Souf valley and may disrupt the future socioeconomic project and increase the damage of natural drought and desertification.
... Researchers have been studying media generation for the visualization of flood disaster modelings to portray the impact of this type of natural disaster. For example, techniques that organize earth surface information in the form of 2D and 3D images or animations based on spatial data and non-spatial data [1]. Such visual representations are considered an efficient way to support decision making and collaborative thinking in the field of flood risk management [2]. ...
Many flood modelings use geovisualization techniques but are very complicated and can only be understood by researchers or practitioners. There is a need for modelings that are informative and can be understood by ordinary people for the purpose of disaster mitigation. This research analyzed a flood modeling geovisualization sample to find out the extent to which aesthetic values are used in that modeling. For breaking down the modeling, an analytical approach was used as well as physioplastic, ideoplastic, and judgment analyses. Then, the modeling was evaluated through a questionnaire that was distributed using Google Forms to 40 respondents with a background as visual communication design students. The questionnaire was presented using closed questions and a visual analogue scale. The aesthetic parameters used for measuring were: lighting, color, two-dimensional field, three-dimensional field, time/motion, and sound. The evaluation results showed that the flood modeling geovisualization sample did not use aesthetics effectively. Modeling representations need to be simplified into visualizations using a well-planned aesthetic concept to make them more informative. Hopefully, the result of this research will make flood modeling more impactful and easier to understand by ordinary people through the application of aesthetic values such as those addressed in the questionnaire.
Because of the increased demand for information, the scientific community have published their results on the Internet over the last 20 years, adapting to society requirements. Due to the development of web-based spatial information soil systems, access to data on various themes and of varying quality has become substantially easier. The focus of our paper is to demonstrate a freely accessible and usable web-based soil database and soil information system (Soil Information and Soil Classifier System), which is suitable for geovisualization uploaded soil data and for determining reference soil groups (RSGs) in accordance with the World Reference Base of Soil Resources (WRB; RSG). In order to achieve this, we algorithmized the diagnostic soil classification process of the WRB, then we created decision trees to correspond input soil data to the WRB system. In order to facilitate geovisualization of the spatial data, the Keyhole Markup Language file format supported by Google API was applied.
The demand for soil and agronomic data has been rapidly increasing for the past few decades. While the data of the global systems are mostly accessible, many of the regional soil databases have limited access provided to their users. Even the highly-restricted data thus obtained is available in a complex and scattered manner making mining and application of it very difficult. To satisfy this modern need for information, our main goal is to collect such data and provide them to the user in a GIS format. Since mobile applications have been recently sought out as information sources according to the modern trend, we aim to create an Android application to produce details related to the ground water level with respect to a particular land mass. This includes precipitation, soil profile and Total Potential Used (TPU) for that area. The data sets were obtained and stored in CSV a file format which was then segregated to form KML Files containing the markers based upon the locations and GeoJSON objects containing the information related to every location. These derived files were then linked to a custom map to build a layer representing that particular data set. Similar process was repeated for other data sets as well. The layers can be viewed and switched through a slide in menu with the locations in each layer highlighted based on a chosen attribute. A legend menu was provided to identify the basis of classification of markers. When a particular marker is clicked, information related to that location on that layer is provided. Based on the above four layers the ideal location to plant certain crops were identified and presented. The markers for each location in each layer were chosen through Decision Tree algorithm. Additional widgets were added to provide a better GUI. The application scope was aimed for Thanjavur district and can be expanded by obtaining and adding data sets of other districts.
