GIS & REMOTE SENSING
Remote sensing (RS) is an art and science of obtaining information about physical characteristics of an area by measuring its reflected and emitted radiation at a distance to help of Satellite or Aircraft.
In below list of Remote sensing Analysis Tutorial.
Summary: –The Electromagnetic spectrum is the complete range of electromagnetic waves arranged by their frequency and wavelength. It includes, in order from longest wavelength to shortest: radio waves, microwaves, infrared, visible light, ultraviolet, X-rays, and gamma rays. Each type of wave has unique characteristics and uses. Electromagnetic Spectrum (EMS) Unveiling the Invisible: The world of […]
Satellite Imagery Satellite Imagery/images are Data collected by Satellites to Earth’s Surface and Ocean. Satellite imagery is used for Weather analysis and forecasting, and also Satellite image analysis Land cover/ use. Sources of Satellite Imagery Download Free Satellite Imagery Data Sources. Satellite Image by Google Worldwide satellite imagery, 3D buildings, and terrain on the Earth.
Change Detection in Remote Sensing using Erdas Imagine In this Tutorial, Learn Change Detection in Remote Sensing using Erdas Imagine Software. What is Change Detection? Change Detection is a process that measures a particular area that has changed between two or more periods. It has been widely used to evaluate shifting agriculture, deforestation, urban growth,
Flood Simulation Model A Flood Simulation Model is a computational tool used to simulate, predict, and analyze flood behavior in a given area. It uses terrain, rainfall, hydrology, and hydraulic data to understand how water flows and accumulates, enabling informed decision-making for flood risk management. Types of Flood Models: Model Type Tools/Examples Description 1D Models
Unsupervised Classification using Erdas Imagine Software Unsupervised Classification is called clustering because it is based on the natural groupings of pixels in image data when they are plotted in feature space. Unsupervised Training The Unsupervised training is more computer-automated. You can specify some parameters that the computer uses to uncover statistical patterns that are inherent in