Data Management Techniques in GIS

The ability to efficiently store and quickly access spatial and attribute information is a critical issue for GIS. Database management systems (DBMS) have long been concerned with storage and access issues, but the added complication of managing information in terms of spatial location and proximity has been challenging. There are two fundamental data models used in GIS: raster and vector. They are, in fact, conceptual and organizational approaches to spatial information management that are fundamentally different.

Raster Data Organization in GIS

The raster data model organizes space by tessellation, which is typically a regular square cell (or pixel), though others are possible (e.g., triangle, parallelogram and hexagon). The raster layer is positioned by placing the cell in row 1, column 1. As a result, we require basic information about the cell's size (e.g., 30 × 30 m), orientation (e.g., north), and coordinates. Aside from that, the layer is based on a certain number of rows and columns of cells, so this must be provided as well. A raster representation of an area of interest is defined using this information. The raster structure is notable in that there is no need to store each cell boundary individually because there is spatial regularity. The spatial geometry of the raster model can be easily constructed by knowing the location of the initial cell and other supporting details such as cell size and the number of rows and columns. This enables significant storage efficiencies to be realized.

The raster representation is significant in that we know not only where each cell is located, but also the attribute value associated with each cell. The values of attributes can be a categorical, binary, integer, or real. The GIS must manage the values of each raster cell, which is where coordinated linkage with cell boundaries comes into play. There are several options for an attribute data structure for storing and managing raster data. Some are more cost-effective in terms of storage space than others in terms of access and processing speed.

A Scan order through the raster cells is used to store attribute data for a raster model. A simple scan order is a row by row, row 1, column 1. Attribute data is stored according to the scan order. Row by row, the attribute for row 1, and column 1 cell would be listed first, followed by the attribute for row 1, column 2 cell, row 1, column 3 cell, and so on.

The Morton order differs in the scan of the cells, beginning with row 1, column 1, then row 1, column 2, next to row 2, column 1, followed by row 2, column 2, etc. Alternative scan orders are important because some have greater data compression potential than others, reducing storage requirements. The attributes are then saved in a pairing format, with the first piece of information being an integer count and the second being the actual attribute value for those cells. As an example, the run-length encoded row by row scan order is interpreted as follows: 2 1 indicates that the first two cells have the attribute value 1; 2 3 denotes that the next two cells have the attribute value 3; 4 2 indicates that the next four cells have an attribute value of 2; and so on. Data compression is accomplished by reducing the number of attribute values stored. High compression rates (up to or exceeding a factor of 40) for a raster layer are not uncommon, depending on the scan order and encoding scheme.

Advantages of Raster Model

The raster data model is useful and important because it can accurately represent a study region because an attribute value is assigned to each location. Furthermore, it can do so efficiently by handling cell spatial location and geometry with minimal storage requirements. Other data management approaches for a raster layer, such as quadtrees and other hierarchical data structures, are also possible, offering potential storage and access efficiencies.

Vector Data Organization in GIS

There are several DBMS approaches, including relational, network, hierarchical, object, and object-relational. Relational DBMS has been the dominant data management approach in vector-based GIS, though this has arguably evolved to more of a hybrid object-relational DBMS. Efficient storage and quick access to information are critical for the success of any developed system. In fact, such issues have been responsible for the evolution of DBMS in GIS. In the following section, we will look at object-relational DBMS that can support vector feature spatial representation.

To begin, a relational DBMS organizes data using linked tables. For example, one table could contain information about the attributes of bus stops, another table could contain information about bus stop maintenance, and a third table would contain the positional coordinates (latitude and longitude) of the stops themselves. The need to track vector objects distinguishes object-relational DBMS. On the one hand, the database typically contains a large amount of attribute information, which makes sense to manage using well-developed relational DBMS functionality. Dealing with geographic space and spatial objects, on the other hand, complicates matters. The geometry of vector features varies, which is one of the reasons for this. A point, for example, is always identified by two pieces of information: latitude and longitude. A polyline, however, can be defined by just two points or by hundreds or even thousands of points. According to the line feature. Similar circumstances apply to polygons. Feature geometry and attribute data are now handled in unison by the object-relational DBMS methodology. The object-relational DBMS approach goes beyond storage considerations, though this is covered in more detail in the following section, as access to data and potential operations are its top priorities.

Advantages of Vector Model

• Need a small space or place for storage data (disc).
• One layer can be connected to numerous attributes to conserve storage space for data.
• Makes the link between topology and network very simple
• Display spatial data graphically closely, like a man-handed map;  
• Have a high spatial resolution.
• Easily for making projections and coordinating transformation.
• Very good in correction limits, apparent and clear for making administration maps and owned lands.

Data Acquisition Techniques in GIS

Spatial Data Acquisition Techniques in GIS

A potential GIS user quickly realizes that having needed spatial information in digital form is critical. Without supporting spatial data, it is nearly impossible to conduct any meaningful analysis. Public data repositories (or government agencies), private vendors, collecting and organizing it yourself, or paying (or hiring) someone to collect and organize it are all options for obtaining the spatial information required for any project or study.

Existing GIS Data Sources

There are numerous existing digital spatial information sources that can be used in a GIS. Some are free or easily accessible to the general public, whereas others must be purchased from a private vendor. Census data  is perhaps the most common source in the United States, summarizing population characteristics of the nation, states, counties, cities, and towns at varying scales. Government agencies also produce data such as 100-year floodplains, vegetation classifications, and transportation. GIS vendors frequently include some basic data with their system, such as political boundaries of nations and states. There are ongoing efforts, such as Project Alexandria  and Geospatial One-Stop, to bring together freely available spatial information sources in digital libraries.

There are also numerous commercial spatial data providers. Some specialize in transportation data, such as Tele Atlas  and NAVTEQ , while others, such as Claritas, focus on geodemographic and market research (www.claritas.com). Given the importance of digital spatial information in the use of GIS, it is not surprising to see the data provider and service industry emerge and thrive, with annual sales currently exceeding $5 billion and expected to grow significantly in the coming years. As a result, commercial data providers profit from the sale and distribution of digital spatial information to users. The point is that while spatial data exists, it may be expensive to obtain.

Semi Existing GIS Data Sources

By semi existing sources, we mean that the spatial information is not always in a digital format that is GIS-compatible. For example, one might have a map from the mid-1800s that shows where gold has been discovered in California. Technically, the information about where gold was discovered exists, but it is contained on a paper map rather than as digital data. A spreadsheet of addresses indicating the residential locations of customers who have purchased a specific product is another example. Again, the information exists, and in this case, it is in digital format, but it is not suitable for use in GIS for geographical evaluation. However, in both cases, this information can be processed to create a digital form that can be used in a GIS. We will now look at three fundamental approaches to processing semi-existing data sources: scanning, digitizing, and geocoding.

Scanning is the process of converting a hardcopy map into a digital image. Most people are probably familiar with scanners, which are used to convert text on a page into digital form. A similar process is used for maps, in which the scanner is used to detect the presence of information on the map pixel by pixel (or raster cell by raster cell). The resulting scanned image is a digital version of the map that can be accessed in some way by most GIS.

Digitizing; the process of capturing or creating vector objects from hardcopy maps or other geographic information sources is known as digitizing (e.g., photographs and images). Manual digitizing relies on a piece of equipment known as a digitizing table, to which a cursor or puck is attached to trace points, lines, or polygons of interest on the map. When the geographic information source is in digital form, such as an image or photograph, another approach is heads-up (or on screen) digitizing. As an example, given a scanned map image, one could import the image into GIS and then manually digitize vector objects in the image.

Geocoding; the process of converting a street address to a latitude and longitude on the earth's surface is known as geocoding. A database with records of street segments, the geometry of each street segment, and the address ranges on each side of the street segment is required. Because the centerline of streets represents the geometry of street segments, this is commonly referred to as a street centerline database. If a street and address are not found in the database, the associated latitude and longitude of the address cannot be determined. When a street is found in the database and the address location is estimated, the latitude and longitude of that address are successfully geocoded. A point on the earth's surface can be found using latitude and longitude, and it corresponds to the street address. Most commercial GIS packages include geocoding functionality, and there are commercial vendors who specialize in geocoding services. However, because successful geocoding is dependent on the street centerline database used, problems can arise if this database is out of date, inaccurate, or of poor quality.

Surveying and Airborne Approaches

Surveying and airborne approaches are the two final data acquisition approaches to be discussed. These are grouped together because they are becoming more interconnected and/or interdependent. The following fundamental approaches to generating spatial information are now discussed: surveying, GPS, aerial photography, and remote sensing.

Surveying is a method of generating vector-based spatial data (points, lines, and polygons) by measuring angles and distances from known positional locations. The importance of known positional locations or reference points here cannot be overstated. Traditional surveying methods use transits and theodolites to measure angles and measuring tapes to determine distance. This requires the cooperation of two people. Total stations are increasingly being used to measure angles and distances in surveying due to advances in technology. Surveying, in general, ensures high positional accuracy—even down to the millimeter level in some cases. It is, however, a time-consuming approach.

GPS (global positioning system) is a satellite navigation system run by the United States Department of Defense that was originally intended for military use. It is a satellite constellation that orbits the Earth at a distance of about 20,000 kilometers. The satellites contain atomic clocks that transmit highly accurate radio signals that handheld or mounted receivers can read. This allows for the determination of position on the earth's surface, as well as velocity and time, assuming that the receiver is in view of a sufficient number of satellites. Vector data can thus be generated. A receiver, for example, could be used to locate a bus stop (point), record the route of the vehicle (line), or demarcate the catchment area of a watershed (polygon). Signal errors can be corrected with differential GPS, and positional accuracy to the centimeter level is possible. This is accomplished by using ground reference stations to adjust GPS readings.

Aerial photography is done from above the earth's surface, possibly in a hot air balloon, plane, or helicopter. This results in a digital image (or possibly a photograph that is subsequently scanned into a digital image). A georeferenced digital image can be used to derive features or attributes on the earth's surface. Heads-up digitizing, for example, could be used to create vector objects such as roads, lakes, rivers, buildings, fields, or forests. Positional accuracy can often be achieved to the fraction of a meter.

Remote sensing is commonly used to generate raster-based spatial data. Sensors mounted on satellites specifically measure solar energy (electromagnetic radiation), though sensors can also be mounted on planes or helicopters. This allows for the deriving of physical, chemical, and biological properties on or near the earth's surface, but it necessitates the processing and interpretation of sensor readings. Spatial and temporal resolution can vary significantly, with some platforms producing measurements for a raster cell of a few meters or less in size and others producing measurements for a raster cell of up to 10 km or more in size for an individual cell.

 

Role of GIS

Location science and geographic information systems (GIS) have evolved almost independently. There are four reasons for this. First, early models in location science were simple and structured as geometric problems (such as those of Weber and/or Fermet). Second, many location science models incorporate elements of operations research (OR). This field entails modeling for decision making, with techniques applicable in both spatial and non-spatial domains. Since the 1940s, the field of OR has evolved, and many of the models discussed in this text are solved using OR-based techniques. Third, the field of GIS developed not to support location science, but rather to support a wide range of uses and services. Geographical information systems(GIS) were created to collect, manage, manipulate, display, and analyze spatial data. Such systems are intended to present spatial data in the form of a map (e.g., a thematic map) and to retrieve data in a format suitable for analysis. As a result, GIS was created to support a wide range of needs, from mapping to spatial queries, and from visualizing a terrain to supplying data to models and statistical tools. That is, the goals of developing GIS go beyond the specific needs of location science because the application domain is much broader. Finally, the number of professionals working in both fields has been relatively small, and work in one has been somewhat independent of work in the other until recently.

Spatial planning problems

Certain issues addressed in location science are actually spatial planning problems that can be solved in GIS without knowledge of operations research or location science. Furthermore, certain issues in location science can be addressed within a theoretical framework that does not involve actual data or specific operations research techniques. Many location problems, from retail store siting to biological reserve site design, involve the need to characterize an application domain complete with spatial data of considerable detail (e.g., road network, census tracts, population estimates, and so on), and rely on a combination of functionality, ranging from GIS to models and algorithms based on operations research.

Location modeling

As problem-solving applications become more sophisticated, the spatial data required in their applications must be supported in some way by GIS. As a result, the role of GIS in location modeling ranges from central to peripheral data support, recognizing the need for complex spatial manipulation, query, and computation. For example, locating cell-phone towers necessitates characterizing the terrain as well as surface clutter, which are elements that reflect, bend, or obscure cell-phone signals (e.g., buildings and vegetation).

Uses of GIS examples

Many GIS packages include terrain modeling, and keeping track of ground cover via data attributes aids in estimating clutter height. As a result, GIS keeps track of the information required to estimate the area coverage of a potential cell-phone site. Simply put, an antenna reception model can be easily integrated with a GIS data model to generate map coverages of potential sites, whereas such a model would necessitate extensive database development and data collection without the use of a general purpose GIS.

What we tried to show is that as these three modeling areas (GIS, OR, and location science) matured, there is a convergence and burgeoning overlap between these fields based on the demand for better and more accurate spatial data, the demand for better models characterizing real landscape problem domains, and the demand for better models characterizing real landscape problem domains, and the need to map and visualize solutions to support decision making at a variety of scales, ranging from the warehouse floor to harvest areas in a large forest plantation to the infrastructure of pipes and pumps, reservoirs, and tanks in a water supply system. Whether it's a water tower or a retail store, future applications are likely to be inextricably linked with GIS, relying on a wealth of spatial data and spatial operations and utilizing models that characterize the problem domain as accurately as possible. This is the future of not only business location decisions, but also location science applications in general. Looking beyond theoretical location constructs and focusing on actual siting problems will result in the development of new models, data structures, algorithms, and theoretical principles. 

 

 

GIS File Formats

Geographic information systems reflect the phenomena that exist at a certain location on the earth's surface through many files or what are known as layers. Each layer corresponds to a particular type of geographical phenomenon. For instance, when representing a certain city's neighborhood, we sketch roadways in one layer, residential structures in another, trees in a third, etc. If we display all these layers simultaneously on the screen, we have a representation of the actual reality in this region.

Two main models are used to represent data: (1) (linear or Vector Data) and (2) (network or cellular; Raster Data). Digital elevation models (DEM) and irregular triangular networks (TIN) are two more (sub) models used to represent 3D data.

Vector Shapefile

Vector linear data model is the representation of all phenomena within a layer as a sequence of coordinates, similar to a paper map. A point is x, y coordinates for a specific location and has no space or dimension, whereas a line is a succession of points given for coordinates and has a dimension (length) but no space and a polygon is a phenomena that expands in a certain space and is enclosed by a line. Thus, the linear data model comprises three forms of representations for phenomena: Point, Arc Line, and Polygon. The method of representing the same phenomenon may vary depending on the drawing scale used and the layer's area boundaries. When drawing a layer for the features of a city, for instance, each neighborhood will be represented as a polygon, whereas the entire city will be displayed as a point when portraying the country as a whole.

The Vector Data model has multiple advantages, the most significant of which are:

• Accuracy in representing the locations of phenomena.
• The size of data representation does not necessitate a large amount of computer storage space, either in RAM or on a Hard Disk.
• Calculations such as length, area, and perimeter are simple to perform.
• The possibility to rectify information entered in a timely manner.

On the other hand, it has two major flaws: data entry needs a great deal of effort and time, and good experience and high accuracy are required for whoever enters the data. Nonetheless, the Vector Data model remains the most prevalent in digital maps, particularly in cadastral and engineering applications.

Raster Data

The Raster grid data model is based on the idea of placing a grid of squares on a map so that if one of the squares applies to a specific sort of phenomenon, this square will carry a number that is identical in value to all of its counterparts from the squares that applied to the same phenomenon. However, if one of the grid squares corresponds to the second phenomenon on the map, this square will be assigned a second number (different from the number of the first phenomenon). This concept is comparable to the principle of photography, in which an image is composed of a large number of microscopic squares, each of which is assigned a certain color to represent a particular phenomenon; hence, the colors of the image vary depending on the phenomena depicted on it. The spatial resolution or resolution of a data file is determined by the limits of a single square (or pixel) in the file. The smaller the size of the square, the higher the clarity and the capacity to represent phenomena. The Raster (grid) model is characterized by its ability to represent continuous phenomena and the speed of data entry into a geographic information system, while its most significant drawbacks are its need for a large storage capacity and its relatively simple accuracy in spatial representation, which is dependent on the size of the square or cell (pixel). Also, its capacity for spatial analysis is inferior to that of the linear model. The Raster model is utilized in aerial pictures, satellite imagery, and simple scanners in general.

Through vectorization and specialist tools such as the (Vector to Raster) program and the On-Screen Digitizing procedure, the Raster model can be turned into a linear model.

Digital Elevation Model DEM 

Digital Elevation Model, or DEM, is a digital file that provides elevation data for a given geographical area. To depict the terrain or topography of the land surface in the area, the digital elevation model can be in the form of a vector (a set of lines consisting of the three coordinates x, y, z of each point) or a raster.

It is possible to obtain a Digital Elevation Model through a variety of sources or input data sources, such as:

• Measurements of the land area using scales, Total Station, or GPS devices, followed by the creation of a digital elevation model for the study region using computer applications.
• Contour maps (after numbering them on the computer).
• From Aerial Photographs.
• From Remote-Sensing Images.
• From free global digital elevation models.

In recent years, the latter type has become the most popular and widely used type of digital elevation model for various reasons.

• Easy to get (from the internet).
• Possibility to obtain it for free.
• They are global models that cover all parts of the Earth's land surface.

There are several global digital elevation models available for free, for example:

• GLOBE Model
• ETOPO2 Model
• ASTER Model
• SRTM Model

Triangular Irregular Networks TIN

Irregular Triangular Networks (or TIN) is one of the three-dimensional data representation methods in GIS, however, its use is currently less common than that of raster files. The concept of creating TIN is based on determining the locations of points and the value of non-spatial data (required to create the three-dimensional surface) and then connecting them with lines that represent a triangle between which the height can be calculated at any point on it, and from which a group or network of irregular triangles (in area and volume) are produced to form a triangle network or TIN between them. TIN cannot be considered an independent form of data representation methods because it consists of the linear model in representation (points, lines, and polygons). However, the method of storing TIN data differs slightly from the method of representing normal linear data, in that it is a semi-linear representation for data based-vector.

From point, line, or polygon layers, TIN files can be developed. For instance, a point’s file including elevation values for each point in its non-spatial database (Attribute Table) can be turned into a TIN file that reflects the topography of the Earth's surface. Also, any form of non-spatial data can be utilized to represent the surface; for instance, a TIN can be generated to represent the temperature distribution or the depths of groundwater, etc. Also, a lines layer can be converted to a TIN file (if it has the values of the third dimension required to draw the three-dimensional surface, whether they are elevation or any other value).

The method of representing data using the TIN model needs far less storage space (on the computer's hard disk) than the raster method, and is therefore recommended for large-area surface representation.

Irregular Triangular Networks files are utilized in three-dimensional spatial analysis techniques, such as converting TIN to equal lines (or contour lines in the case of elevations), computing slopes and inclinations, and producing solids for the study area.

Raster files can be converted to TIN files and vice versa.

Map Projection in GIS

A projection map is a mathematical process that allows us to convert three-dimensional coordinates on the earth's surface—whether the reference shape representing the earth is a sphere or an ellipsoid—to coordinates represented on a plane surface, which is the map two-Dimensional coordinates or Grid Coordinates. In other words, projection is the process that allows us to convert the latitude and longitude values of a location into the eastern and northern coordinates required to label this location on a map (the shape resulting from the projection process is also known as projection).

The process of converting the stereoscopic shape of the Earth into a flat form (a map) cannot be completed in its entirety, and any method of projecting maps will result in "Distortion." Different methods of map projection attempt to maintain one or more of the following characteristics between the actual target on the ground and its image on the map (some characteristics cannot be combined):

·        Match in spaces

·        Match in distances

·        Match in directions

·        Match in corners

·        Match in shapes

Types of map projections

There are projection types that preserve distances and are referred to as Equidistance Projections, projection types that preserve shapes and angles together, but in limited areas, and are referred to as Conformal Projections (which are most commonly used in cadastral applications), and projection types that preserve areas and are referred to as Equal-Area Projection.

There are four types of map projections:

·   Cylindrical Projections: result from the projection of the earth’s surface onto a cylinder, which either touches the earth vertically or cuts it or touches the earth transversely or diagonally.

·    Conical Projection:  arises from the projection of the earth's surface onto a cone, which either touches the earth vertically or cuts it.

·     Azimuthal Projection: They arise from the projection of the Earth's surface onto a plane that either touches the Earth vertically at a specific point or cuts it in a circle.

·      Other private projections.

Commonly the shape of the geographical area to be projected plays a crucial role in determining the most suitable projection method. For instance, if the shape of the area is semi-circular, we select a method for projecting its two features, a cylindrical projection method for semi-rectangular areas, and a conical projection method for semi-triangular areas.

Mercator map projection

A cylindrical projection satisfies the condition that lines of latitude and longitude intersect at perfectly right angles. The scale is true at the equator or at two Standard Parallels of latitude equidistant from the equator. This site is often used in nautical charts.

Transverse Mercator Projection

This projection is the result of the Earth being projected onto a cylinder that touches it at a Central Meridian. This projection is often used for areas whose north-south extension is greater than their east-west extension. The distortion (in scale, distance, and area) increases as we move away from the Central Meridian; therefore, when using this projection, we employ the concept of slices, where the width of one slice - in the direction of the east - is three or four degrees of longitude so that the amount of distortion is not excessive. The edges of the slice whose central longitude is located in the center. The Mercator projection is utilized on maps of numerous nations, including Egypt and the Britain.

Universal Transverse Mercator Projection

It is the most common type of map projection on a global level and its abbreviation is UTM. Because it is one of the projections used in GPS technology devices, its significance has also grown in recent years.

·   The UTM projection is dependent on finding a way to draw maps of the entire world by dividing the earth into 60 zones, each covering 6 degrees of longitude, so that each segment has a UTM projection with a Central Meridian centered on this segment.

·      The UTM projection segments extend from latitude 80 south to latitude 84 north.

·    The tranches are numbered from No. 1 to No. 60, beginning at 180º West longitude, so that the first tranche extends from 180º west to 174º west and has a central longitude of 177º west.

·        Every 8 degrees of latitude divides each longitudinal slice into squares.

·      There shall be a special letter - as a name - for each of these squares, and the letters start from the letter C in the south to the letter X in the north, with the exclusion of the letters I and O (because they are similar to the English numbers!).

·    The factor scale is equal to 0.9996 at the central longitude, so as we move away from the central longitude, the maximum value of the scale factor at the slice's edges is 1.00097 at the equator or 1.00029 at latitude 45º.

Sinusoidal Equal-Area Projection

In this space-preserving projection, the latitude circles are only perpendicular to the central meridian, whereas the rest of the longitude lines are curved in a manner similar to sin curves (hence the name of this projection: the sinusoidal projection). The scale of the drawing is only accurate at the central longitude and latitude, and this projection is used for areas that extend in a north-south direction.

Lambert Conformal Conic Projection 

This projection utilizes the cone (not the cylinder as in previous projections), in which the areas and shapes are identical at the two Parallels Standards, the distortion increases as we move away from them, and the directions are correct in a limited number of areas. In North America, this projection is used.

Lambert Azimuthal Equal-Area Projection

This planar projection (as opposed to a cylinder or cone) is often used to plot vast oceanic regions. With the exception of the central meridian, all other meridians are curved.

Orthographic Projection

Azimuth projection (i.e., the use of the plane in projection) is frequently employed to display a generalized image or perspective of the hemisphere. In it, both areas and shapes are distorted, while the distances on the equator and other latitude circles are accurate.

 

Geographic Coordinate Systems

Coordinates are the values used to express a precise position on the earth's surface or on a map. There are multiple coordinate systems based on the various reference surfaces used to represent locations. When using a plane as a reference surface (for example, a map), the coordinates can be planar, projected, or 2D. (Two-dimensional). The term “two-dimensionality" refers to how each point on a map, for example, requires two values to establish its location (x, y). We are dealing with spatial coordinates or three- dimensional (or 3D) coordinates when we use a sphere or an ellipsoid as a reference surface, in which the height of the point must be added from the reference surface as a third dimension to determine its exact location, that is, we need to know the three values (x, y, and Z) for each location. In the case of the sphere, the coordinates are called Spherical Coordinates, while in the case of the ellipsoid they are called Geodetic Coordinates, Geographic Coordinates, or Ellipsoidal Coordinates. There are also one-dimensional (or 1D) coordinates, which often just reflect the point's height from the surface of the reference form utilized. There are four-dimensional (or 4D) coordinates in high-precision geodetic and geophysical applications where the location is determined by the point at a specific time so that its coordinates are (x, y, z, t), where the fourth dimension "t" expresses the time of measuring these coordinates for this location.

Locating on the Sphere

Centuries ago, scientists developed a technique for representing the position of any point on the Earth's crust (assuming the Earth is spherical) by:

·        The horizontal baseline is that great circle (that is, the one that passes through the center of the Earth), which is located in the middle of the distance between the two poles and is called the equator.

·        The vertical baseline was taken to be the semi-circle that connects the North and South poles and passes through Greenwich, England.

·        The equator was divided into 360 equal sections, and 360 semi-circles (imaginary or conventional) were drawn on the earth's surface, connecting the two poles and passing through one of the equator's division points. Longitude is the name given to each semi-circle. Because 360 degrees correspond to 360 divisions, dividing two adjacent angles equals one degree. The Greenwich longitude was numbered zero, and the longitudes adjacent to it from the east side were 1 degree east, 2 degree east,... to 180 degree east, and the same for the lines west of Greenwich, 1 degree west to 180 degree west. The longitude angle is the angle located in the plane of the equator between two sides, one of which passes through the Greenwich longitude while the other passes through the longitude of the same point.

·        The main longitude (Greenwich) was divided into 180 equal sections, and imaginary minor circles were drawn on the ground parallel to the equator (the small circle is the one that does not pass through the center of the Earth), with each circle passing through one of the points dividing the Greenwich longitude. Thus, the angle in the center of the globe between two consecutive division points is equal to 1 degree because 180 degrees correspond to 180 divisions, and these circles were named latitude circles, including 90 circles north of the equator circle and 90 circles south of the equator circle. Similarly, the circle of the equator was numbered zero, and the circle of latitude adjacent to it from the north side was 1 degree north, then 2 degrees north … to 90 degrees north, and the circles located south of the equator circled from 1 degree south to 90 degrees south. The latitude angle is defined as an angle in the plane of a circle of longitude, with its vertex at the center of the circle and its primary side passing through the plane of the equator and the other side crossing through a circle of latitude.

Types of Geographic Coordinate System

For geographic data, there are two primary types of coordinate systems: geodetic coordinate systems based on map projections and geographic coordinate systems based on latitude and longitude. The fundamental distinction is that projected geodetic coordinates are Cartesian coordinates with two orthogonal axes that are equally sized. Distances and areas determined in these units are comparable around the world. Geographic coordinates, on the other hand, are polar coordinates defined by two angles and a distance (the radius of the Earth) (between a given location and the equator and between this location and the prime meridian). Because the spacing between longitude lines diminishes from the equator to the poles, they are ineffective for comparing distances or regions around the world. They are, nevertheless, helpful as a full global system free of the distortion difficulties associated with map projections.

Geographical or Geodetic Coordinates

One of the coordinate systems whose center is the Earth's center and whose axes revolve with the Earth is a geodetic coordinate system. As a result, it's known as an earth-centered earth-fixed system, or ECEF for short. The system's center is in the earth's center of gravity, and its vertical z-axis coincides with the axis of rotation. On Earth, the first horizontal x-axis is perpendicular to the Greenwich meridian, and the second horizontal y-axis is perpendicular to the x-axis.

Any point in this system is represented by three values or three coordinates, indicating that it is 3D:

·        Longitude is symbolized by the Latin symbol (ʎ), and it is the angle measured in the plane of the equator between the Greenwich meridian (which is the longitude that is internationally used to be the number zero) and the longitude of the required point.

·        Latitude is symbolized by the Latin symbol (ɸ), which is the angle in the vertical plane formed by the perpendicular direction passing through the required point with the plane of the equator (the vertical direction on the surface of the ellipsoid does not pass through the center of the ellipsoid, whereas the perpendicular to the surface of the sphere does).

·        The height above the surface of the ellipsoid is represented by the symbol h and is called the Geodetic or Ellipsoidal Height.

There are several systems of units used to express latitude and longitude, the most well-known of which is the sexagesimal system of units, in which the full circle is divided into 360 degrees (the degree symbol isº) and the degree is divided into 60 parts, each of which is called a minute (the minute symbol isʹ), and then the minute is divided into 60 parts, each of them is called a second (the second symbol is "). For example, a longitude of 30º 45ʹ 52.3ʺ means that the location of this point is at 30 degrees, 45 minutes, and 52.3 seconds. The longitude lines are either east of the Greenwich meridian (symbolized by adding the letter E) or west of Greenwich (symbolized by adding the letter W). As for the latitude circles, they are either north of the equator (symbolized by adding the letter N) or south of the equator (symbolized by adding the letter S).

Spherical Coordinates

The spherical coordinate system is similar to the geodetic or geographic coordinate system, with only one difference: the reference surface here is the sphere, not the ellipsoid. The vertical direction on the surface of the sphere passes through its center, as opposed to the ellipsoid, where the vertical direction does not pass through its center.

Cartesian Geodetic Coordinates

It is a coordinate system having the same definition as the geodetic coordinate system, except that its three coordinates are longitudinal (i.e. in meters or kilometers) rather than curved (in degrees), making it easier to deal with, especially in calculations. Descartes, a French scientist, devised it in the seventeenth century. The center of the earth is the origin point of the Geodetic Cartesian Coordinates system, and its first axis, X, is formed by the intersection of the meridian plane passing through Greenwich with the plane of the equator. Its second axis, Y, is perpendicular to the X axis, and its third (vertical) axis, Z, is the earth's rotating axis, passing through its center and both poles. Each point's location is represented by three coordinates: Z, Y, and X.