Information Systems

Technology & Applications

GEOGRAPHIC INFORMATION SYSTEMS GIS

GIS is a computer-based system that provides the following foursets of capabilities to handle geo-referenced data: input, data management, manipulation-analysis, and output. (Aronoff, 1989)

DBMS

DataBase Management Systems

GLOBEs

Handling the geo-referenced maps and various spatial data.

SOFTWARE

Coding is the essential part of GIS apps

Information Systems & Technology & Applications

GIS is a relatively new field — it started in the 1970’s. It used to be that computerised GIS was only available to companies and universities that had expensive computer equipment. These days, anyone with a personal computer or laptop can use GIS software. Over time GIS Applications have also become easier to use –– it used to require a lot of training to use a GIS Application, but now it is much easier to get started in GIS even for amateurs and casual users. As we described above, GIS is more than just software, it refers to all aspects of managing and using digital geographical data. In the tutorials that follow we will be focusing on GIS Software. (https://qgis.org/en/docs/index.html)

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Topology

Topology expresses the spatial relationships between connecting or adjacent vector features (points, polylines and polygons) in a GIS. Topological or topology-based data are useful for detecting and correcting digitising errors (e.g. two lines in a roads vector layer that do not meet perfectly at an intersection). Topology is necessary for carrying out some types of spatial analysis, such as network analysis.

Computer Networking

A computer network is a digital telecommunications network which allows nodes to share resources. In computer networks, computing devices exchange data with each other using connections (data links) between nodes. These data links are established over cable media such as wires or optic cables, or wireless media such as Wi-Fi.

Dijkstra's Algorithms

Dijkstra’s algorithm (the link-state routing algorithm) is iterative and has the property that after the kth iteration of the algorithm, the least-cost paths are known to k destination nodes, and among the least-cost paths to all destination nodes, these k paths will have the k smallest costs.In the LS algorithm, each node talks with all other nodes (via broadcast), but it tells them only the costs of its directly connected links. The global routing algorithm consists of an initialization step followed by a loop. The number of times the loop is executed is equal to the number of nodes in the network.

Distance Vector Algorithms

The Distance Vector (DV) algorithm is iterative, asynchronous, and distributed. It is distributed in that each node receives some information from one or more of its directly attached neighbors, performs a calculation, and then distributes the results of its calculation back to its neighbors. It is iterative in that this process continues on until no more  information is exchanged between neighbors. The least costs are related by the celebrated Bellman-Ford equation. In the DV algorithm, each node talks to only its directly connected  neighbors, but it provides its neighbors with least-cost estimates from itself to all the nodes (that it knows about) in the network.

Data Structures

In computer science, a data structure is a data organization, management, and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.

 Data structures provide a means to manage large amounts of data efficiently for uses such as large databases and internet indexing services. Usually, efficient data structures are key to designing efficient algorithms. Some formal design methods and programming languages emphasize data structures, rather than algorithms, as the key organizing factor in software design. Data structures can be used to organize the storage and retrieval of information stored in both main memory and secondary memory.
 Data structures are generally based on the ability of a computer to fetch and store data at any place in its memory, specified by a pointer—a bit string, representing a memory address, that can be itself stored in memory and manipulated by the program. Thus, the array and record data structures are based on computing the addresses of data items with arithmetic operations, while the linked data structures are based on storing addresses of data items within the structure itself.
 

Object Oriented Programming
(OOP)

The programming paradigm based on the concept of “objects“, which can contain data, in the form of fields (often known as attributes or properties), and code, in the form of procedures (often known as methods). A feature of objects is an object’s procedures that can access and often modify the data fields of the object with which they are associated (objects have a notion of “this” or “self”). In OOP, computer programs are designed by making them out of objects that interact with one another.[1][2] OOP languages are diverse, but the most popular ones are class-based, meaning that objects are instances of classes, which also determine their types.

Many of the most widely used programming languages (such as C++, Java, Python, etc.) are multi-paradigm and they support object-oriented programming to a greater or lesser degree, typically in combination with imperativeprocedural programming. Significant object-oriented languages include JavaC++C#PythonPHPJavaScriptRubyPerlObject PascalObjective-CDartSwiftScalaCommon LispMATLAB, and Smalltalk.

Vector Data

Vector data provide a way to represent real world features within the GIS environment. A feature is anything you can see on the landscape. Imagine you are standing on the top of a hill. Looking down you can see houses, roads, trees, rivers, and so on. Each one of these things would be a feature when we represent them in a GIS Application. Vector features have attributes, which consist of text or numerical information that describe the features.

Raster Data

In the previous topics we have taken a closer look at vector data. While vector features use geometry (points, polylines and polygons) to represent the real world, raster data takes a different approach. Rasters are made up of a matrix of pixels (also called cells), each containing a value that represents the conditions for the area covered by that cell . In this topic we are going to take a closer look at raster data, when it is useful and when it makes more sense to use vector data.

Data Science

The multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is the same concept as data mining and big data: “use the most powerful hardware, the most powerful programming systems, and the most efficient algorithms to solve problems”.

Data Visualizations

The graphic representation of data. It involves producing images that communicate relationships among the represented data to viewers of the images. This communication is achieved through the use of a systematic mapping between graphic marks and data values in the creation of the visualization. Mapping establishes how data values will be represented visually, determining how and to what extent a property of a graphic mark.

Data Visualizations Examples

Data Visualizations Examples

Common GIS Apps

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