Skip to main content

Raster Data Analysis. GIS

Raster data analysis is a fundamental aspect of GIS that involves working with data represented in a grid-based format known as raster data. Raster data consists of a series of cells or pixels, where each cell represents a value or attribute associated with a specific location on the Earth's surface.

In GIS, raster data analysis refers to the process of manipulating, extracting information, and deriving new insights from raster datasets. This type of analysis enables us to understand spatial patterns, perform calculations, and make informed decisions based on the values within the raster cells.

There are several tools and techniques available for raster data analysis in GIS software. Here are some commonly used ones:

1. Raster Calculator: This tool allows you to perform mathematical operations on raster datasets, such as addition, subtraction, multiplication, and division. It is useful for creating new raster layers by combining or transforming existing ones.

2. Zonal Statistics: Zonal statistics calculates statistics, such as mean, maximum, minimum, or standard deviation, for a specific zone or region defined in a raster dataset. It helps in analyzing and summarizing values within predefined areas of interest.

3. Slope and Aspect Analysis: These tools calculate the slope and aspect of the terrain from elevation raster data. Slope analysis measures the steepness of the land, while aspect analysis determines the orientation or direction of the slope.

4. Reclassification: Reclassification allows you to assign new values or categories to raster cells based on specified criteria. It is helpful in reclassifying continuous data into discrete classes or grouping data for thematic mapping.

5. Density Analysis: Density analysis helps to analyze the concentration or distribution of certain phenomena in a raster dataset. It calculates the density of occurrences within a given area, such as population density or density of crime incidents.

6. Cost Distance Analysis: This tool calculates the least-cost path or distance between locations, considering the cost or resistance values assigned to raster cells. It is commonly used for modeling movement or finding the optimal route based on factors like terrain, land cover, or infrastructure.

7. Suitability Analysis: Suitability analysis assesses the suitability of areas for specific activities or criteria. It involves overlaying multiple raster datasets, assigning weights to each layer, and generating a suitability map to identify areas that meet certain criteria.

These are just a few examples of the numerous raster analysis tools available in GIS software. Each tool serves specific purposes and can be combined to perform complex analyses and generate valuable insights from raster data.

Comments

Popular posts from this blog

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...

REMOTE SENSING INDICES

Remote sensing indices are band ratios designed to highlight specific surface features (vegetation, soil, water, urban areas, snow, burned areas, etc.) using the spectral reflectance properties of the Earth's surface. They improve classification accuracy and environmental monitoring. 1. Vegetation Indices NDVI – Normalized Difference Vegetation Index Formula: (NIR – RED) / (NIR + RED) Concept: Vegetation reflects strongly in NIR and absorbs in RED due to chlorophyll. Measures: Vegetation greenness & health Uses: Agriculture, drought monitoring, biomass estimation EVI – Enhanced Vegetation Index Formula: G × (NIR – RED) / (NIR + C1×RED – C2×BLUE + L) Concept: Corrects for soil and atmospheric noise. Measures: Vegetation vigor in dense canopies Uses: Tropical rainforest mapping, high biomass regions GNDVI – Green Normalized Difference Vegetation Index Formula: (NIR – GREEN) / (NIR + GREEN) Concept: Uses Green instead of Red ...

Landsat 8 Band designation and Band Combination.

Landsat 8 Band designation and Band Combination.  Landsat 8-9 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) Bands Wavelength (micrometers) Resolution (meters) Band 1 - Coastal aerosol 0.43-0.45 30 Band 2 - Blue 0.45-0.51 30 Band 3 - Green 0.53-0.59 30 Band 4 - Red 0.64-0.67 30 Band 5 - Near Infrared (NIR) 0.85-0.88 30 Band 6 - SWIR 1 1.57-1.65 30 Band 7 - SWIR 2 2.11-2.29 30 Band 8 - Panchromatic 0.50-0.68 15 Band 9 - Cirrus 1.36-1.38 30 Band 10 - Thermal Infrared (TIRS) 1 10.6-11.19 100 Band 11 - Thermal Infrared (TIRS) 2 11.50-12.51 100 Vineesh V Assistant Professor of Geography, Directorate of Education, Government of Kerala. https://www.facebook.com/Applied.Geography http://geogisgeo.blogspot.com

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...

Change Detection

Change detection is the process of finding differences on the Earth's surface over time by comparing satellite images of the same area taken on different dates . After supervised classification , two classified maps (e.g., Year-1 and Year-2) are compared to identify land use / land cover changes .  Goal To detect where , what , and how much change has occurred To monitor urban growth, deforestation, floods, agriculture, etc.  Basic Concept Forest → Forest = No change Forest → Urban = Change detected Key Terminologies Multi-temporal images : Images of the same area at different times Post-classification comparison : Comparing two classified maps Change matrix : Table showing class-to-class change Change / No-change : Whether land cover remains same or different Main Methods Post-classification comparison – Most common and easy Image differencing – Subtract pixel values Image ratioing – Divide pixel values Deep learning methods – Advanced AI-based detection Examples Agricult...