a road can be represented as a line at a smaller scale or as a polygon at a larger scale. A real-world entity could be represented by different types of vector features depending on the map scale used in an application (e.g.
#RASTER DATA MODELS SERIES#
On the above figure, the real world is represented by a series of lines (roads and highway) and one polygon (the river). Polygons are closed areas that can be made up of a circuit of line segments. Lines are spatial objects made up of connected points (nodes) that have no width. The model maintains uniformity when it comes to size and shape due to matrix and multi-array like structure. This data form can be used to do various spatial analysis.
![raster data models raster data models](https://i.vimeocdn.com/video/366022803_1280x720.jpg)
Points are spatial objects with no area but can have attached attributes since they are a single set of coordinates (X and Y) in a coordinate space. Raster Datais the simplest form of data structures, and hence they are easy to use and understand by the Geographic Information Systems Workforce. A vector representation is composed of three main elements: points, lines and polygons. Attribute precision Good for polygon, point and line data not good for continuous data unless connected to TIN or similar technology. The concept assumes that space is continuous, rather than discrete, which gives an infinite (in theory) set of coordinates. So, this is the most important takeaway from these two lectures that we are going through thevector data model and the raster data model is you should know when to use what kind ofdata when you want to record or a given feature or an event or a phenomena you should knowwhat kind of data structure to use whether you should use the vector data. On the above figure, the real world (shown as an aerial photograph) is simplified as a grid where the color of each cell relates to an entity such as road, highway or river. For a large grid the resolution is fine, but at the expense of a much larger storage space. For a small grid, the resolution is coarse but the required storage space is limited. Resolution is an important concern in raster representations. triangles and hexagons), the square is the most commonly used. A raster representation also relies on tessellation: geometric shapes that can completely cover an area.
#RASTER DATA MODELS REGISTRATION#
This allows for registration with a geographic reference system. Semantic technologies have proven their relevance in facilitating the interpretation of Earth Observation (EO) data through formats such as RDF and reusable models, especially for the representation of space and time. To validate the raster-based data model, time series of. Features are divided into cellular arrays and a coordinate (X,Y) is assigned to each cell, as well as a value. The vector data are integrated into the raster-based GM method by the vector-to-raster conversions. Grid cells are the most common raster representation. Each unit is generally similar in size to another. Based on a cellular organization that divides space into a series of units. Two representational models are dominant raster (grid-based) and vector (line-based):
![raster data models raster data models](https://i.stack.imgur.com/yNbMp.png)
A GIS data model enables a computer to represent real geographical elements as graphical elements. Representing the “real world” in a data model has been a challenge for GIS since their inception in the 1960s.