Remote Sensing Satellites
A satellite with remote sensors to observe the earth is called a remote-sensing satellite, or earth observation satellite. Remote-Sensing Satellites are characterised by their altitude, orbit and sensor.
IRS( Indian Remote Sensing Satellite)
India has launched several satellite includes IRS 1A, IRS 1B, IRS 1C, IRS 1D, IRS P 2,IRS P 3, IRS P 4 for different applications.
Landsat
It is established at an altitude of 700 kms is a polar orbit and is used mainly for land area observation.
Other remote sensing satellite series in operations are: SPOT, MOS, JERS, ESR, RADARSAT, IKONOS etc.
Basic Concept of LiDAR Mapping
The accuracy and functionality of many GIS projects rely to a large extent on the accuracy of topographic data and the speed with which it can be collected. The recently emerged technique of airborne altimetric LiDAR has gained considerable acceptance in both scientific and commercial communities as a tool for topographic measurement.
The LiDAR instrument transmits the laser pulses while scanning a part of terrain, usually centred on and co-linear with, the flight path of the aircraft in which the instrument is mounted. The round trip travel times of the laser pulses from the aircraft to the ground are measured with a precise interval timer. The time intervals are converted into range measurements, i.e. the distance of LiDAR instrument from the ground point struck by the laser pulse, employing the velocity of light. The position of aircraft at the instance of firing the pulse is determined by Differential Global Positioning System (DGPS). During the movement of aircraft experience lot of distortions in altitude, lateral movements so on but these warps are taken care by the instrument to yield accurate coordinates of points on the surface of the terrain. Laser mappers acquire digital elevation data with accuracies equivalent to those of GPS, but thousands times faster.
Basics of Digital Image Processing
Remote sensing images are recorded in digital form and then processed by the computers to produce images for interpretation purposes.
Images are available in two forms - photographic film form and digital form. Variations in the scene characteristics are represented as variations in brightness on photographic films. A particular part of scene reflecting more energy will appear bright while a different part of the same scene that reflecting less energy will appear black.
Digital image consists of discrete picture elements called pixels. Associated with each pixel is a number represented as DN (Digital Number), that depicts the average radiance of relatively small area within a scene. The size of this area effects the reproduction of details within the scene. As the pixel size is reduced more scene detail is preserved in digital representation.
Digital image processing is a collection of techniques for the manipulation of digital images by computers. Digital image processing encompasses the operations such as noise removal, geometric and radiometric corrections, enhancement of images, information extraction and image data manipulation and management.
Image Processing Methods
Image processing methods may be grouped into three functional categories:
Geometric and Radiometric Corrections
The correction of errors, noise and geometric distortions introduced during scanning, recording and playback operations. However, the data supplied by NRSA-Hydrabad is corrected for these errors. Hence, we are restricted to the enhancement techniques and information extraction.
Image Enhancement
- Linear Contrast Enhancement: Very few scenes have a brightness range that utilises the full sensitivity range of the detectors. To produce an image with the optimum contrast ratio, the entire brightness range of the display medium, should be utilised. In linear contrast we have to assign the low end as 0 (zero) and the high end as 1(One) and the other values in between are linearly stretched. The linear stretch improves the contrast for most of the original brightness values.
- Spatial Filtering: Spatial Filtering is a pixel by pixel transformation of an image, which depends on the grey-level of the pixels concerned as well as the greylevel of the neighbourhood pixels. It is a procedure in which greylevel of a pixel is altered according to its relationship with respect to the greylevel of the neighbouring pixels.
Information Extraction
In the case of information extraction processes the computer makes decisions to identify and extract specific pieces of information.