Weighted model-based clustering for remote sensing image analysis

2009 ◽  
Vol 14 (1) ◽  
pp. 125-136 ◽  
Author(s):  
Joseph W. Richards ◽  
Johanna Hardin ◽  
Eric B. Grosfils
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Remote Sensing Image ◽  
Model Based Clustering ◽  
Model Based ◽  
Weighted Model

scholarly journals Introduction to the Special Issue “Uncertainty in Remote Sensing Image Analysis”

2018 ◽  
Vol 10 (12) ◽  
pp. 1975
Author(s):  
Alfred Stein ◽  
Yong Ge ◽  
Inger Fabris-Rotelli
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Remote Sensing Image ◽  
Special Issue

Images obtained from satellites are of an increasing resolution. [...]

Airborne remote sensing in forestry: Sensors, analysis and applications

2000 ◽  
Vol 76 (6) ◽  
pp. 859-876 ◽  
Author(s):  
Douglas J. King
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Key Words ◽  
Analytical Techniques ◽  
Remote Sensing Image ◽  
Digital Cameras ◽  
Airborne Remote Sensing ◽  
Hyperspectral Sensors ◽  
Imaging Characteristics ◽  
Laser Remote Sensing

This paper discusses the aspects of airborne remote sensing that are critical to forestry applications, the imaging characteristics of the most common sensors currently available, and analytical techniques that make use of the great amount of information content in airborne imagery. As the first paper in the CIF technical meeting to which this issue of the Forestry Chronicle is devoted, the paper is intended to provide an overview and context for subsequent papers and not a presentation of specific research methods or results. Key words: airborne remote sensing, forestry, photography, digital cameras, hyperspectral sensors, radar, laser remote sensing, image analysis

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