Skip to main content

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

🧭 Example

Suppose your classified map shows:

  • A location classified as forest

But ground survey shows:

  • The same location is actually agriculture land

👉 This is a classification error.

📊 Error Matrix (Confusion Matrix)

What is Error Matrix?

Error matrix is a table used to compare classified results with actual ground data.

It is the most important tool in accuracy assessment.

🧾 Example of Error Matrix

Reference DataForestAgricultureWaterTotal
Forest405045
Agriculture630238
Water031417
Total463816100

👉 Diagonal values show correct classification
👉 Other values show classification errors

📚 Important Terminologies

1️⃣ Overall Accuracy

It shows how many pixels are correctly classified in total.


✔ Example

Correct pixels = 40 + 30 + 14 = 84
Total pixels = 100

👉 Overall Accuracy = 84%

2️⃣ Producer's Accuracy

✔ Meaning

Shows how well real-world features are correctly classified.

👉 It measures error of omission.

❓ What is Omission Error?

When a real feature is missed in classification.

Example:

  • Real forest area classified as agriculture.


3️⃣ User's Accuracy

✔ Meaning

Shows the probability that a classified pixel actually represents that class on ground.

👉 It measures error of commission.

❓ What is Commission Error?

When a pixel is wrongly included in a class.

Example:

  • Agriculture land classified as forest.

 Steps in Accuracy Assessment

Step 1 – Sampling Design

Selecting sample points to check accuracy.

Methods include:

✔ Random sampling
✔ Stratified sampling
✔ Systematic sampling

Step 2 – Comparison

Compare:

  • Classified image results

  • Ground truth data

Step 3 – Accuracy Calculation

Create error matrix and calculate:

  • Overall Accuracy

  • Producer's Accuracy

  • User's Accuracy

  • Kappa coefficient


Comments

Post a Comment

Popular posts from this blog

Energy Interaction with Atmosphere and Earth Surface

In Remote Sensing , satellites record electromagnetic radiation (EMR) that is reflected or emitted from the Earth. Before reaching the sensor, radiation interacts with: The Atmosphere The Earth's Surface These interactions control how satellite images look and how we interpret them. I. Interaction of EMR with the Atmosphere When solar radiation travels from the Sun to the Earth, four main processes occur: 1. Absorption Definition: Absorption occurs when atmospheric gases absorb radiation at specific wavelengths and convert it into heat. Main absorbing gases: Ozone (O₃) → absorbs Ultraviolet (UV) Carbon dioxide (CO₂) → absorbs Thermal Infrared Water vapour (H₂O) → absorbs Infrared Concept: Atmospheric Windows These are wavelength regions where absorption is very low, allowing radiation to pass through the atmosphere. Remote sensing depends on these windows. For example, satellites like Landsat 8 use visible, near-infrared, and thermal bands located in atmospheric windows. 2. Trans...
Post a Comment
Read more

Types of Remote Sensing

Remote Sensing means collecting information about the Earth's surface without touching it , usually using satellites, aircraft, or drones . There are different types of remote sensing based on the energy source and the wavelength region used. 🛰️ 1. Active Remote Sensing 📘 Concept: In active remote sensing , the sensor sends out its own energy (like a signal or pulse) to the Earth's surface. The sensor then records the reflected or backscattered energy that comes back from the surface. ⚙️ Key Terminology: Transmitter: sends energy (like a radar pulse or laser beam). Receiver: detects the energy that bounces back. Backscatter: energy that is reflected back to the sensor. 📊 Examples of Active Sensors: RADAR (Radio Detection and Ranging): Uses microwave signals to detect surface roughness, soil moisture, or ocean waves. LiDAR (Light Detection and Ranging): Uses laser light (near-infrared) to measure elevation, vegetation...
Post a Comment
Read more

Model GIS object attribute entity

These concepts explain different ways of organizing, storing, and representing geographic information in a Geographic Information System (GIS) . They include database design models (ER model), data structure models (Object and Attribute models), and spatio-temporal representations that integrate location, entities, and time . Together, they help GIS manage both spatial data (where things are) and descriptive information (what they are and how they change over time) . 1. Object-Based Model (Object-Oriented Data Model) The Object-Based Model treats geographic features as independent objects that combine spatial geometry and descriptive attributes within a single structure. Core Concept: Each geographic feature (such as a building, road, or river ) is represented as a self-contained object that stores both: Geometry – location and shape (point, line, polygon) Attributes – descriptive properties (name, type, length, capacity) Unlike older georelational models , which stored spatial ...
Post a Comment
Read more

Platforms in Remote Sensing

In remote sensing, a platform is the physical structure or vehicle that carries a sensor (camera, scanner, radar, etc.) to observe and collect information about the Earth's surface. Platforms are classified mainly by their altitude and mobility : Ground-Based Platforms Definition : Sensors mounted on the Earth's surface or very close to it. Examples : Tripods, towers, ground vehicles, handheld instruments. Applications : Calibration and validation of satellite data Detailed local studies (e.g., soil properties, vegetation health, air quality) Strength : High spatial detail but limited coverage. Airborne Platforms Definition : Sensors carried by aircraft, balloons, or drones (UAVs). Altitude : A few hundred meters to ~20 km. Examples : Airplanes with multispectral scanners UAVs with high-resolution cameras or LiDAR High-altitude balloons (stratospheric platforms) Applications : Local-to-regional mapping ...
Post a Comment
Read more

Government of Kerala Initiatives for Water Management

Kerala, with its abundant rainfall and network of rivers, faces a dual challenge of water scarcity and excess —seasonal droughts and monsoon floods. The state government has implemented various policies and programs to address these challenges through sustainable water conservation, management, and distribution practices . Below is a detailed breakdown of the major water management initiatives in Kerala. 1. Jal Jeevan Mission (JJM) – Kerala Implementation Objective: To provide functional household tap connections (FHTC) to all rural households by 2024. Focuses on source sustainability and community-led water resource management. Key Features: Water Quality Monitoring & Surveillance: Ensures supply of safe drinking water through real-time monitoring. Decentralized Approach: Implementation through gram panchayats and local self-governments (LSGs) . Recharge & Conservation Measures: Rainwater harvesting, groundwater recharge, and watershed development inte...
Post a Comment
Read more