Spatial Data Acquisition Methods

From all spatial data acquisition methods, ground surveying has the longest history. As mentioned in the chapter “History of Mapping”, first measurements of the Earth involved measuring distances between not so distant places. A groundbreaking measurement was done by Eratosthenes of Cyrene in the 3rd century BCE. Eratosthenes used only primitive tools available at that time: a gnomon and a wheel. Gnomon is a simple pole placed perpendicular to the earth surface. By measuring the revolutions of a wheel of Eratosthenes carriage and the length of a shadow casted by gnomon on two different places, Eratosthenes was able to calculate quite precisely the Earth’s circumference more than 2200 years ago. His approach inspired much later measurements in 16th century France.

When better and more precise instruments were invented, the measurements of earth also improved. Josef Liesgang in the 18th century used a telescope to measure angles between objects on an observable horizon. By also measuring a distance in several places, he was able to construct imaginary triangles of known sizes. Vertices of these triangles were well identified locations on hills or at build-up structures, like a cathedral tower. In principle, the same method is used up until today. An instrument named theodolite was a principal tool for measuring angles in the 19th and 20th century and is still used for simple tasks at construction works today. Theodolites were lately superseded by electronic total stations, an instrument capable of measuring both angles and distances at the same time. Nowadays total stations are robotic, meaning they can turn in a desired direction by a remote control. They are also often combined with GNSS aparatures in order to calculate the most accurate results in the field, without further post-processing, which is essential for smooth work on construction sites.

Global Navigation Satellite Systems (GNSS) work by determining the precise location of a receiver on Earth through the use of satellite signals. The basic principle behind GNSS relies on measuring the time it takes for a signal to travel from a satellite to a receiver. Each GNSS satellite continuously transmits signals that include the satellite’s position and the precise time the signal was sent. The receiver on the ground records the time at which the signal was received. By calculating the time difference between when the signal was emitted and when it was received, the receiver can determine its distance from that satellite.

Since the receiver only knows its distance from the satellite (and not the direction), it could be located anywhere on a sphere with that radius. To accurately pinpoint its location, the receiver needs signals from at least four satellites. When data from these satellites are combined, the receiver calculates its position through a process called trilateration. The intersection of spheres from multiple satellites allows the receiver to determine its exact position in three dimensions (latitude, longitude, and altitude). This process accounts for time discrepancies by solving for both the receiver's position and the receiver's clock error, making GNSS an accurate and reliable method for global positioning.

First GNSS system was an American military system NAVSTAR GPS or shortly just GPS. Its positional accuracy was initially obscured for civil usage and location with sub-metre accuracy was only available for military applications. Civil receivers were only able to determine its location with a precision of several metres. This obfuscation of NAVSTAR GPS was removed in 2000. With the evolution of GNSS receivers for public geodetic users, a positional accuracy of several centimetres is possible. This is thanks to the approach of using phase measurements of the GNSS carriage wave. As of 2024, four GNSS systems are fully operable worldwide. Beside the american-based NAVSTAR GPS, it is a russian system GLONASS, chinese system Beidou and european system Galileo. Japan is building a GNSS system specifically suited for the east Asian region. These GNSS systems not only vary in the country in which its operation centre resides and which government funds its operation, it also differs in the technical aspects like the frequency of the carriage wave, the number, height and angle (inclination) of the satellites on the Earth’s orbit, the speed in which the satellites orbit the Earth, number of waves they transmit and others.

Where the NAVSTAR GPS signal was not ideal or better precision was required, systems for local enhancement of GPS, named SBAS systems, were developed. From these systems, European EGNOS is notable, as the predecessor of EU’s own Galileo system.

Generally, an acquisition of spatial information from distance, without making a physical contact with the observed area, is called remote sensing. Collecting spatial data remotely involves aerial photography, satellite imagery or LiDAR (Light Detection and Ranging) techniques.

Taking photographs from aircrafts belongs to older remote sensing techniques. The process of acquisition of precise survey photographs is called photogrammetry. Aerial photography can provide images with a high resolution, but collecting data for a large area is slow and expensive. Satellite images usually provide worse resolution, but a wider area can be covered. Nowadays, satellite images cover a whole world and are often used as base-layers in popular online maps like Google Maps. Recently, unmanned aerial vehicles (UAVs) allowed to take very detailed photographs of a small area, while being cheap. Photographs acquired using these techniques can be processed into orthophotos, orthophoto maps and even 3D models of terrain.

Imagery from aerial, satellite and UAV photogrammetry does not have to capture visible spectrum of light like common cameras do. Information obtained from near-infrared, infrared and other parts of the spectrum are useful for applications in forestry, agronomy and elsewhere.

LiDAR technique is based on targeting an object or a surface with a laser. The time travelled by the reflected light back to the receiver is calculated to distance. As a laser can emit the light beam to thousands of points in a second, the output of LiDAR is usually a large set of distances between the laser device and the observed object. Consequently, the distances are transformed into points in locations where the laser beam has been reflected. The set of these points is called a point cloud. A process of collecting laser data is called laser scanning.