Question

This is remote sensing course and we have use ENVI software.

1. Discuss the difference between Remotely Sensed imagery and an Image Map?

2. What is the process of creating "Burned-in" image, and why is it an important element in digital map production

Answer 1

ENVI development is providing tools and methods to extract information from images, and to then integrate these results with GIS databases. ENVI currently has many tools for these purposes, including workflows for common image processing tasks for GIS professionals, converting to and editing common vector data formats, and geodatabase support. Moreover.

a)Both map and satellite remote sensing images relate to a geographical place on earth’s surface; however, the satellite image is the RAW information, where from you can generate a map. A Map suppose to represent some information particular to your need. Like you have political map, bio-diversity map, land use and forest cover map etc. Depending on your need you collect data and you represent it in a spatial diagram. That’s what is the technical definition of a Map. However, the satellite data on other hand is simply a raw data, where you have to do geometric corrections, map the image pixels in a coordinate system of you preference, then choose exact information that you wish to extract from the image data.Such information extraction and correction are mostly done using remote sensing software tools. And after you’re done with the information extraction process, then the output you get is actually the MAP. The raw satellite image data is not a map in technical sense.

b)Satellite remote sensing has been widely employed for fire history reconstruction both at the local/regional/national .A prerequisite method of recreating the fire history of an area is the detection of fire scars and the accurate mapping of the burned areas is called burned-in images.

It an important element in digital map production,Along with the abundance of satellite data, numerous approaches and techniques have been developed for detection and mapping of burned areas including: vegetation index differencing , Principal Component Analysis (PCA) , Spectral Mixture Analysis (SMA) , logistic regression , supervised classification , and multitemporal image compositing . In addition, advanced image analysis techniques, such as neural networks and support vector machines , have also been employed.