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

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...

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...

Development and scope of Environmental Geography and Recent concepts in environmental Geography

Environmental Geography studies the relationship between humans and nature in a spatial (place-based) way. It combines Physical Geography (natural processes) and Human Geography (human activities). A. Early Stage 🔹 Environmental Determinism Concept: Nature controls human life. Meaning: Climate, landforms, and soil decide how people live. Example: People in deserts (like Sahara Desert) live differently from people in fertile river valleys. 🔹 Possibilism Concept: Humans can modify nature. Meaning: Environment gives options, but humans make choices. Example: In dry areas like Rajasthan, people use irrigation to grow crops. 👉 In this stage, geography was mostly descriptive (explaining what exists). B. Evolution Stage (Mid-20th Century) Environmental problems increased due to: Industrialization Urbanization Deforestation Pollution Geographers started studying: Environmental degradation Resource management Human impact on ecosystems The field became analytical and problem-solving...

Geographic phenomena fields objects boundaries.

In geography, geographic phenomena refer to features or processes that can be observed and studied on Earth's surface. These phenomena can be classified into three main categories: fields , objects , and boundaries . Each category has distinct characteristics, representations, and applications in Geographic Information Systems (GIS). 1. Fields A field represents continuous, spatially varying data where a value is present at every location within the study area. It describes conditions that exist across a geographic area. Characteristics : Continuity : Fields have no discrete boundaries; the data is continuous. Gradual Variability : The values of a field change gradually across space. Representation : Typically modeled using raster data in GIS, where a grid structure assigns a value (e.g., temperature or elevation) to each cell. Examples : Temperature Map : Shows temperature variation across a region. Rainfall Distribution : Displays rainfall levels over a large g...

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

Vineesh V, Geography

Search This Blog