Relational GIS and Remote Sensing Database System for Al-Salt Area, Jordan

Abstract

Due to the importance of database systems, integration between two Geomatics sciences, GIS and Remote Sensing has been made in order to support and serve various sectors in Jordan. GIS has been used to create layers that can show decision makers in a simple, easy and flexible manner. Remote Sensing will be used in creating images of how Jordan is seen from space, which will give the users more information and an overview about the study area. Satellite images could be converted into digital image maps, using digitizing procedures. The features viewed in the original scene could be studied by using different remotely sensed techniques. Landsat-7 (ETM+) and SPOT images were implemented, in order to extract the information needed for the topography of the region, land cover areas, boundaries, drainage patterns, road networks, man-used areas, vegetated areas and many other features in Al-Salt areas. The validity and the appropriateness of GIS and Remote Sensing techniques, particularly data fusion of images were evaluated in relation to visualization.

Creating a Geographical Information Systems-based Spatial Profile for Exploring Health Services Supply and Demand

“…This function is used by several applications to create points on a map from a table of addresses. For example, Fadda et al (2008) indicate that GIS can be used for Building a relational database system that includes GIS layers and RS image maps and managing them, for producing digital image maps for Jordan (Al-Salt) and for evaluating the validity and the appropriateness of data fusion in relation to visualization.…”

“…GIS plays an essential role in helping public health organizations understand population health and make decisions. GIS has been used to create layers that can show decision makers in a simple, easy and flexible manner (Fadda et al, 2008). With the powerful tools and solutions that GIS technology brings to the desktop, health planners can improve understanding of community health needs and design effective interventions.…”

Mathematical Genesis of the Spatio-Temporal Covariance Functions

“…The sensors are both in situ and remote and they generate spatially distributed data of many different kinds (Fadda et al, 2008;Saberioon et al, 2010). Producing a statistically optimal map, together with measures of map uncertainty, which is always uptodate, is a complicated task.…”

Normalized Relational Storage for Extensible Markup Language (XML) Schema

“…This is because Student nodes are located in different paths (under both Course and Faculty nodes). Even though the algorithm proposed in Chen et al (2003); Lv and Yan (2006); Xing et al (2007) and Kim and Peng (2011) tried to map XML to relational schema in the presence of functional dependencies by using redundancy reducing strategies, but they ignored the redundancy that cause by the redundant nodes as in Courses and Students. Also, the Student nodes by the value of "Adam" were stored twice in the trees; inability to detect these redundancies will caused redundancies to occur in the relational views.…”

“…On the other hand, dependencies naturally exist among data no matter what format the data is in. An array of researches has addressed the issues on storage strategy (Chen et al, 2003;Lv and Yan, 2006;Xing et al, 2007;Patel and Atay, 2007;Ferraggine et al, 2009;Kim and Peng, 2011;Huiling and Feng, 2010;Feng and Jingsheng, 2009) unfortunately the resulting relational applications do not offer the required guarantee for the preservation of data integrity and reduced data redundancy.…”