**Data, information, knowledge**

Data: numbers, text, symbols, usually neutral and independent of context (raw measurements without interpretation)

**Information:** differentiated data as dedicated to a subject or subjected to some degree of interpretation

**Knowledge:** information interpreted in relation to a particular context, experience, or for a particular purpose

Data or information?

**Information:** differentiated data as dedicated to a subject or subjected to some degree of interpretation

**Data:** numbers, text, symbols, usually neutral and independent of context (raw measurements without interpretation)

How to understand and represent reality to deal with a computer?

universal vision or contextual vision?

How to define criteria description of reality without specific problem to begin with?

Precision, scale and description, modeling reality: the approach of the geographer.

data models

A data model is a set of rules to represent objects and behaviors of the real world in the logical framework of a computer.

There are four levels of abstraction of reality:

The real world (no abstraction)

The conceptual model (conceptual modeling of reality)

The logic model (organization model of computer-related)

The physical model (internal organization to the application)

*The geographic data*

Recording measurements taken at a certain place at a certain time in the real world

Combines location, time, and descriptive attributes

Difficult to handle in conventional systems data management, which are not equipped to higher dimensional data 1

*The spatial object*

An object in information theory is an encapsulated set of attributes and methods for describing the knowledge and behavior to contextual view of reality.

Spatial Object has three major components: location, description, behavior

The different types of attributes of a geographic object:

**Descriptive Information:**

conventional single data (finite, N, Z, R, etc.) and methods related to the natural order. Modality value.

**location information:**

**location data:** in two or three dimensions (R2 or R3), points, or set points (elements or sets).

The location attribute: new space definition, new methods, new measures, new details.

The modeling of the real world: the reality of geography

Description and location precision, methods, attributes, for the definition of a spatial object.

Links between descriptive attributes and accuracy of the location attribute for defining the spatial object. Example: cartographic generalization?

**The spatial object:** relation between semantic definition (descriptive attributes) and accuracy of the description of the geometry of the location.

The reality of geography: a conceptual model

Geography to geometry: map the location

The model of traditional cartographic mapping in areas, lines, points (in a continuous space, 2D or 3D). The card and its history.

**The pixel:** an area or point?

Geography to geometry: a conceptual model

The limits of cartographic model

The limits of geometry and cartographic model:

It is assumed that classical geometry to describe the positions of geographic objects. thus introduces discontinuities in reality using the mapping in the area, line, point to define geographic objects. The accuracy or uncertainty are not addressed by these descriptive models. The space is not treated continuously, the geographical definition of objects is discontinuous and greatly simplifies reality.

The geometric description in area, line, point it is enough to describe adequately the geographic objects?

cartographic and computing power model

**IT inputs:**

Geographical description to computer Description: Should the computer take the geometry of objects or question too reductive mapping of cartographic model? She will improve the modeling of space, while currently it only repeats existing patterns (the cartographic model)?

The treatments applied to spatial objects in GIS they are not too sophisticated compared to the validity of the mapping of reality?

**Geometry to data: Logic Model**

Raster representation

Simplifying the location of objects is total (all objects have the same size and shape). It defines only one geometry object (mesh) which is attached all descriptive attributes.

raster data fills all space

Precision is fixed once and for all, and generally degrade the accuracy of cartographic model in which information comes

The implementation of computer algorithms for analysis operations is easy, but the difficulty of spatial analysis remains intact

We must distinguish “raster representation” and information “raster”, such as satellite images or scanned photographs: accuracy depends on the sensor and does not degrade the original data.

**Geometry to data: Logic Model**

Vector representation

Areas and contours, lines and networks, points. It preserves the geometric definition of the cartographic model objects, but going from a mathematical description (in R2 or R3) to a single computer description in a discrete set (with a finite number of parameters):

Representation of a rainbow by a finite set of points. Representation of an area by a set of arcs. Graphs and Networks.

The objects of the conceptual model are not changed, the geometric accuracy is preserved, the chart-descriptive report is not disturbed

The storage space is low

The structure allows the two-dimensional indexing

Representation of pixels

Satellite images or scanned aerial photographs are different from raster representation: localization grid comes directly from the sensor. Information is the value of a cell, called pixels. This is not a logical model, but a conceptual model of reality description (model defined by the manufacturer of the sensor, which selects the resolution, wavelengths).

The main purpose of the remote sensing is spending pixel (and descriptive values it contains, radiometry or grayscale) to the location of objects defined by their descriptive content (land use, vegetation type, … ) by grouping pixels.

Another approach is the treatment of the pixel as an area type object. It all depends on the pixel size in relation to the definition of geographical object studied (can the pixel be likened to a point of mathematical space or should it be considered a zone?).

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