GIS & REMOTE SENSING
Erdas Imagine Software is world-class Remote Sensing as well as Satellite image processing software. The ERDAS IMAGINE provides true value, consolidating remote sensing, photogrammetry, LIDAR analysis, basic vector analysis, and radar processing into a single product.
Introducing ERDAS IMAGINE Software Erdas Imagine performs advanced remote sensing analysis and spatial modeling to create new information. In Erdas Imagine Software, you can visualize your results in 2D, 3D, movies, and on cartographic-quality map compositions. The core of the Erdas Imagine product suite is engineered to scale with your Geo-spatial data production needs. Erdas […]
Single Class Classification using Erdas Imagine One class or single class Classification in impotent of many applications for GIS and Remote Sensing. For example estimation of total vegetation cover or build-up area for any particular region. You can also calculate the exactly amount of area. There are many applications for which we do not require
Image Post Processing In this Tutorial perform Post Image Processing/ Image Classification Vectorization in Erdas Imagine Software. For many specialized applications, classifying data that have been merged, spectrally merged or enhanced with principal components, image algebra, or other transformations can produce very specific and meaningful results. However, without understanding the data and the enhancements used,
Exploring False Colour Composite (FCC): A Visual Revolution in Satellite Imagery A false color satellite image is one in which the Red (R), Green (G), and Blue (B) values do not correspond to the true colors of red, green and blue. A standard False Color Composite (FCC) blue is assigned to green radiations (0.5 to
Water Index Remote Sensing Water Remote Sensing studies the color, temperature, and quality of water through the observation of the spectrum of water leaving radiance. Satellite Remote Sensing or Earth Observation can be crucial in understanding the spatio-temporal dynamics of water quantity and quality, which can be used to simulate water resources management Data collected