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Sources of spatial data

 Survey Data

Concepts and Terminologies:
Ground Survey: This is the direct measurement of features on the Earth using instruments such as total stations, theodolites, and modern Global Navigation Satellite Systems (GNSS, e.g., GPS).
Control Points: Fixed locations measured with high accuracy; these serve as reference points (or benchmarks) to georeference and tie together spatial datasets.
Coordinate Geometry (COGO): Techniques for calculating distances and angles from measured points, often used in legal and cadastral surveys.

Examples:
• A cadastral survey for establishing property boundaries typically involves collecting precise GNSS coordinates at the corners of parcels.
• Engineering projects rely on survey data to create high-accuracy maps where the relative positions of roads, utilities, and buildings must be known within decimeter or even centimeter accuracy.

Survey data is fundamental in creating the framework for maps and digital elevation models (DEMs) because it ensures that subsequent aerial or remote sensing data can be accurately aligned (georeferenced) with real-world coordinates.


2. Air Photos (Aerial Photography)

Concepts and Terminologies:
Aerial Photography: The process of capturing images from an airborne platform (aircraft, drones, or even kites/balloons).
Vertical vs. Oblique Imagery:
 – Vertical photographs are taken with the camera lens pointed straight down, minimizing distortion and ideal for mapping and photogrammetry.
 – Oblique photographs are taken at an angle, offering a perspective view useful for understanding terrain or structures, though they require additional correction to be used for accurate mapping.
Photogrammetry: The science of extracting 3D measurements from 2D images. This is commonly used to generate digital elevation models (DEMs) and to produce ortho-rectified images (orthophotos) that have been corrected for lens distortion and terrain relief.

Examples:
• Urban planners often use vertical aerial photographs to create up-to-date base maps of a city.
• Archaeologists may use oblique aerial photos to detect subtle crop marks or soil disturbances that reveal hidden archaeological sites.

Air photos provide high-resolution images that are excellent for detailed local mapping and are frequently used as a background in Geographic Information Systems (GIS) for further analysis.


3. Satellite Images

Concepts and Terminologies:
Remote Sensing: The process of collecting information about the Earth from a distance using sensors on satellites or aircraft.
Raster Data: Satellite images are typically stored as raster data (a grid of pixels), where each pixel carries a value representing the reflectance in one or more spectral bands.
Resolution Types:
 – Spatial Resolution: The size of the area each pixel covers on the ground (e.g., 10 m, 30 m).
 – Spectral Resolution: The ability to resolve wavelengths across the electromagnetic spectrum (e.g., multispectral vs. hyperspectral sensors).
 – Temporal Resolution: How frequently a satellite revisits the same location (e.g., every 5 days for Sentinel-2).
 – Radiometric Resolution: The sensor's ability to distinguish differences in energy (often expressed in bits, such as 8-bit or 12-bit).

Examples:
• The Landsat series provides imagery dating back decades at 30 m spatial resolution, making it invaluable for monitoring land use changes over time.
• Sentinel-2 satellites deliver 10 m resolution data in visible and near-infrared bands, suitable for precision agriculture and environmental monitoring.
• High-resolution commercial satellites (like those operated by Maxar) can provide sub-meter imagery useful for urban planning and disaster response.

Satellite images allow for large-area coverage and are indispensable for global monitoring of environmental changes, urban expansion, and natural disasters.


4. Field Data

Concepts and Terminologies:
In-Situ (Field) Data: Direct observations or measurements made on the ground. This includes everything from soil samples and vegetation surveys to geotagged photographs.
Ground Truthing: The process of validating remote sensing data with on-the-ground observations to improve the accuracy of classifications or measurements made from imagery.
Mobile GIS: The use of smartphones, tablets, or specialized devices that collect and sometimes process spatial data in real time during field surveys.

Examples:
• Environmental scientists may collect soil moisture, temperature, and nutrient data from specific sampling sites to validate satellite-derived indices (such as the Normalized Difference Vegetation Index, NDVI).
• Field crews using mobile GIS apps can quickly capture locations and attributes of features (like road conditions or infrastructure status) and update digital maps in real time.

Field data is crucial for both calibrating and validating spatial datasets from other sources. It provides the "ground truth" that ensures remote sensing images, aerial photos, and survey data accurately reflect the conditions on the ground.


Integration in a GIS

A modern GIS often integrates all these sources:
Survey Data provides the high-accuracy framework and control points.
Aerial Photos supply detailed, up-to-date visuals for a specific region.
Satellite Images deliver broad coverage and multi-temporal analysis capabilities.
Field Data offers direct measurements and verification for remote observations.


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