Data Acquisition Methods Flashcards

Which of the following best describes the fundamental difference between active and passive remote sensing data acquisition methods?

Answer: Passive sensors measure emitted or reflected energy from an external source, whereas active sensors provide their own energy source to illuminate the target.

The primary distinction between the two methods is the source of energy. Passive sensors (e.g., satellite imaging systems like Landsat) detect natural energy, such as reflected sunlight or emitted thermal radiation. Active sensors (e.g., LiDAR and RADAR) generate their own energy pulse and record the backscatter, allowing them to operate day or night and, in some cases, penetrate clouds.

A field technician is collecting high-precision coordinates for ground control points using a GNSS receiver. They notice significant, fluctuating positional errors despite having a clear view of the sky. The errors seem most pronounced during the early afternoon. Which of the following is the most likely source of this signal propagation error?

Answer: Ionospheric and tropospheric delay

Ionospheric and tropospheric delays are caused by the GNSS signal being refracted as it passes through charged particles in the ionosphere and water vapor in the troposphere. These atmospheric conditions can cause significant positional errors and are often most pronounced during the heat of the day. While multipath and poor geometry are also error sources, the description of fluctuating errors peaking in the afternoon strongly points to atmospheric effects. Selective Availability was discontinued in 2000.

In photogrammetry, what is the name of the process that uses tie points and ground control points across multiple overlapping aerial images to precisely determine the position and orientation of the camera at the moment of exposure for each image?

Answer: Aerotriangulation

Aerotriangulation is the critical process in photogrammetry that establishes a precise geometric relationship between the images, the camera, and the ground. It uses common points (tie points) visible in overlapping photos and known ground control points (GCPs) to solve for the camera's exterior orientation parameters for an entire block of photos simultaneously.

A GIS analyst receives a raw, unprocessed LiDAR point cloud dataset in LAS format. For each individual point, which set of attributes is most likely to be included as a standard part of the initial data collection?

Answer: X, Y, Z coordinates, intensity, and return number

A raw LiDAR point cloud fundamentally consists of georeferenced X, Y, and Z coordinates for each laser pulse return. Additionally, the intensity of the returned pulse and the return number (e.g., first, second, last) are standard attributes recorded by the sensor system. Feature classification and RGB values are typically added during post-processing steps.

A planning department needs to convert a highly detailed, legally authoritative paper map of historical property boundaries into a digital vector format for a cadastre project. Precision and geometric fidelity to the source map are the highest priorities. Which data acquisition method is most suitable for this task?

Answer: Heads-down digitizing using a high-precision digitizing tablet and puck

Heads-down digitizing with a tablet and puck is a manual method that provides the operator with a high degree of control, which is essential for achieving the high accuracy required for cadastral and legal boundary mapping from a paper source. Automated methods can introduce errors and may not accurately capture the nuanced linework of a legal document, while using the scan as a simple image does not create the required vector data.

A GIS team is tasked with acquiring data from multiple external agencies, each providing data in different formats (e.g., spreadsheets, CAD files, various database types). The data must be cleaned, restructured, projected, and loaded into a centralized enterprise geodatabase. Which industry-standard acronym best describes this overall data acquisition and integration workflow?

Answer: ETL (Extract, Transform, Load)

ETL (Extract, Transform, Load) is a standard data integration process. It involves extracting data from various sources, transforming it to fit operational needs (cleaning, reformatting, projecting), and loading it into a target database or system. This precisely describes the workflow required to integrate disparate data sources into a central GIS.