LiDaR Remote Sensing

LiDAR Remote Sensing: A Primer

LiDAR (Light Detection and Ranging) is a remote sensing technology that uses light in the form of a pulsed laser beam to measure ranges to the Earth's surface and various objects. This technology is incredibly versatile and has applications in a wide range of fields, including:

Cartography and mapping: Creating highly accurate 3D maps of the Earth's surface, including topography, vegetation, and buildings.
Forestry: Measuring forest height, density, and biomass.
Geology: Studying geological formations and identifying potential natural hazards.
Archaeology: Discovering and mapping ancient sites.
Environmental monitoring: Assessing changes in land cover, coastal erosion, and climate-related impacts.

Key Terminologies and Concepts

Laser: A device that emits an intense beam of coherent light. LiDAR systems use lasers to emit pulses of light.
Pulse: A short burst of laser energy.
Time of Flight: The time it takes for a laser pulse to travel to a target and return to the sensor. This is used to calculate the distance to the target.
Point Cloud: A collection of individual points, each representing a specific location on the Earth's surface. LiDAR data is often processed to create point clouds.
Digital Surface Model (DSM): A 3D representation of the Earth's surface, including the tops of buildings, trees, and other objects.
Digital Terrain Model (DTM): A 3D representation of the Earth's surface, excluding vegetation and other objects.
Intensity: A measure of the strength of the laser return signal. This can be used to infer information about the properties of the target.
Footprint: The area on the ground that is illuminated by a laser pulse.
Accuracy: The degree to which LiDAR measurements agree with true values.
Precision: The degree to which LiDAR measurements are consistent with each other.

Facts and Applications

High Accuracy: LiDAR can provide centimeter-level accuracy in measurements.
Versatility: LiDAR can be used to measure a wide range of objects, from small plants to large buildings.
Penetration: LiDAR can penetrate vegetation and other materials to measure underlying surfaces.
Real-Time Data: Some LiDAR systems can provide real-time data, allowing for immediate analysis and decision-making.

Comments

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...

Supervised Classification

Image Classification in Remote Sensing Image classification in remote sensing involves categorizing pixels in an image into thematic classes to produce a map. This process is essential for land use and land cover mapping, environmental studies, and resource management. The two primary methods for classification are Supervised and Unsupervised Classification . Here's a breakdown of these methods and the key stages of image classification. 1. Types of Classification Supervised Classification In supervised classification, the analyst manually defines classes of interest (known as information classes ), such as "water," "urban," or "vegetation," and identifies training areas —sections of the image that are representative of these classes. Using these training areas, the algorithm learns the spectral characteristics of each class and applies them to classify the entire image. When to Use Supervised Classification: - You have prior knowledge about the c...

Accuracy Assessment

Accuracy assessment is the process of checking how correct your classified satellite image is . 👉 After supervised classification, the satellite image is divided into classes like: Water Forest Agriculture Built-up land Barren land But classification is done using computer algorithms, so some areas may be wrongly classified . 👉 Accuracy assessment helps to answer this question: ✔ "How much of my classified map is correct compared to real ground conditions?" Goal The main goal is to: Measure reliability of classified maps Identify classification errors Improve classification results Provide scientific validity to research 👉 Without accuracy assessment, a classified map is not considered scientifically reliable . Reference Data (Ground Truth Data) Reference data is real-world information used to check classification accuracy. It can be collected from: ✔ Field survey using GPS ✔ High-resolution satellite images (Google Earth etc.) ✔ Existing maps or survey reports 🧭 Exampl...

Representation of Spatial and Temporal Relationships

In GIS, spatial and temporal relationships allow the integration of location (the "where") and time (the "when") to analyze phenomena across space and time. This combination is fundamental to studying dynamic processes such as urban growth, land-use changes, or natural disasters. Key Concepts and Terminologies Geographic Coordinates : Define the position of features on Earth using latitude, longitude, or other coordinate systems. Example: A building's location can be represented as (11.6994° N, 76.0773° E). Timestamp : Represents the temporal aspect of data, such as the date or time a phenomenon was observed. Example: A landslide occurrence recorded on 30/07/2024 . Spatial and Temporal Relationships : Describes how features relate in space and time. These relationships can be: Spatial : Topological (e.g., "intersects"), directional (e.g., "north of"), or proximity-based (e.g., "near"). Temporal : Sequential (e....

GIS: Real World and Representations - Modeling and Maps

Geographic Information Systems (GIS) serve as a bridge between the real world and digital representations of geographic phenomena. These representations allow users to store, analyze, and visualize spatial data for informed decision-making. Two key aspects of GIS in this context are modeling and maps , both of which are used to represent real-world geographic features and phenomena in a structured, analyzable format. Let's delve into these concepts, terminologies, and examples in detail. 1. Real World and Representations in GIS Concept: The real world comprises physical, tangible phenomena, such as landforms, rivers, cities, and infrastructure, as well as more abstract elements like weather patterns, population densities, and traffic flow. GIS allows us to represent these real-world phenomena digitally, enabling spatial analysis, decision-making, and visualization. The representation of the real world in GIS is achieved through various models and maps , which simplify...

Vineesh V, Geography

Search This Blog