Skip to main content

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.


Comments

Popular posts from this blog

Remote Sensing Technology

Remote sensing is a rapidly evolving geospatial technology used to collect information about the Earth's surface and atmosphere without direct physical contact . It involves detecting and measuring electromagnetic radiation (EMR) reflected or emitted from objects using sensors mounted on satellites, aircraft, or drones. Remote sensing systems are fundamentally classified based on (1) the energy source used for illumination and (2) the region of the electromagnetic spectrum utilized for sensing . 1. Types of Remote Sensing Based on Energy Source Remote sensing systems are commonly categorized according to whether the sensor generates its own energy or relies on naturally available radiation . Passive Remote Sensing Principle: Passive remote sensing relies on natural sources of electromagnetic energy , primarily solar radiation reflected from the Earth's surface or thermal radiation emitted by objects. Operation: Most passive sensors operate during daylight when sunlight is av...

Spectral Signature vs. Spectral Reflectance Curve

Spectral Signature  A spectral signature is the unique pattern in which an object: absorbs energy reflects energy emits energy across different wavelengths of the electromagnetic spectrum. ✔ Key Points Every natural and man-made object on Earth interacts with sunlight differently. These interactions produce a distinct pattern , just like a "fingerprint". Sensors on satellites record these patterns as digital numbers (DN values) . These patterns help to identify and differentiate objects such as vegetation, soil, water, snow, buildings, minerals, etc. ✔ Examples of Spectral Signatures Healthy vegetation → High reflectance in NIR , strong absorption in red Water → Strong absorption in NIR and SWIR , low reflectance Dry soil → Gradual increase in reflectance from visible to NIR Snow → High reflectance in visible , low in SWIR ✔ Why Spectral Signature Matters It allows: Land cover classification Chan...

History of GIS

1. 1832 - Early Spatial Analysis in Epidemiology:    - Charles Picquet creates a map in Paris detailing cholera deaths per 1,000 inhabitants.    - Utilizes halftone color gradients for visual representation. 2. 1854 - John Snow's Cholera Outbreak Analysis:    - Epidemiologist John Snow identifies cholera outbreak source in London using spatial analysis.    - Maps casualties' residences and nearby water sources to pinpoint the outbreak's origin. 3. Early 20th Century - Photozincography and Layered Mapping:    - Photozincography development allows maps to be split into layers for vegetation, water, etc.    - Introduction of layers, later a key feature in GIS, for separate printing plates. 4. Mid-20th Century - Computer Facilitation of Cartography:    - Waldo Tobler's 1959 publication details using computers for cartography.    - Computer hardware development, driven by nuclear weapon research, leads to broader mapping applications by early 1960s. 5. 1960 - Canada Geograph...

Spatial Entity and Spatial Object

Concepts Spatial Entity : Refers to any real-world feature or phenomenon that exists in a specific location and can be identified in space. This emphasizes the actual physical or conceptual presence of the feature. Spatial Object : Represents the digital or computational representation of a spatial entity within a Geographic Information System (GIS). This includes its geometry (e.g., points, lines, polygons) and associated attributes. Key Distinction : While the terms are often interchangeable, spatial entity tends to focus on the real-world phenomenon, whereas spatial object highlights its representation in GIS. Key Terminologies Geographic Coordinates : Define the location of spatial entities using a coordinate system (e.g., latitude and longitude). Example: A building at 40.748817° N, 73.985428° W . Geometry Types : Point : Represents a single location (e.g., a well or a bus stop). Line : Represents linear features (e.g., roads, rivers). Polyg...

Raster Data Model

A raster data model represents geographic space as a grid of cells (called pixels ). Think of it like a chessboard covering the Earth. Each square = cell / pixel Each cell contains a value That value represents information about that location Example: Elevation = 245 meters Temperature = 32°C Land use = Forest The grid is arranged in: Rows Columns This structure is called a matrix . GRID Model (Cell-Based Matrix Model) 🔹 Concept The GRID model is the most common raster structure used in GIS for spatial analysis . It is mainly used for: Continuous data (data that changes gradually) Sometimes discrete/thematic data 🔹 Structure A 2D matrix (rows × columns) Each cell stores one numeric value Integer (whole number) Float (decimal number) 🔹 Key Terminologies Cell Resolution → Size of each pixel (e.g., 30m × 30m) Spatial Resolution → Level of detail DEM (Digital Elevation Model) → Elevation grid Raster Calculator → Tool for mathematical operations Overlay Analysis → Combining mu...