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Abstrak :
ABSTRACT
A Line object extraction from satellite imagery is presented in this thesis. The extraction technique can be significant to both application and development of digital remote sensing methodology the analysis proceeds from satellite imagery to the detailed analysis of specific regions. Smoothing, Laplacian Transform, Line detection and Threshold techniques are used to extract a line object from satellite imagery.

This extraction technique may eventually be extended to recognize different patterns for examples, rivers, runway or highway because there are many kind of linear feature. The algorithms for locating linear features are of general interest. A data from National Institute for Aeronautic and Space (LAPAN) was used which cover portions of Cengkareng and Jakarta Area. Its found that result will always contain a significant amount of noise and we can get information about the object early.

Abstrak :
The atmospheric effects reduction in this study which covers path radiance effect decrement and ground reflectivity extraction of Landsat MSS Data.

When radiation travels through the atmosphere, energy is attenuated through scattering and absorption, an enhanced due to atmospheric emission and path radiance. Ground reflected radiance, from which information is extracted for remote sensing application, is altered by the atmosphere when it reaches the satellite. Besides that, radiance reflected by the background area surrounding the target may also reach the satellite. Therefore, the effects of atmosphere on Landsat data must be reduced, before data processing for any purposes.

The effective reflectivity which is observed from the satellite can be computed as a function of ground reflectivity. Relation between the effective reflectivity and ground reflectivity is linear approximately.

Land cover classification which is processed by Maximum Likelihood method is used in this study, in order to evaluate the atmospheric effects reduction method.