Land cover mapping at sub-pixel scales using remote sensing imagery

One of the great challenges of land cover mapping from remotely sensed images is the mixed pixel problem. Much research has focused on attempting to extract land cover types at sub-pixel scale, while little research has been conducted concerning the spatial allocation of land cover types within a pi...

Full description

Saved in:
Bibliographic Details
Published inProceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05 Vol. 1; p. 3 pp.
Main Authors Makido, Y., Jiaguo Qi
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Earth
Geography
Image resolution
Image sensors
Iterative algorithms
Pixel
Predictive models
Remote sensing
Satellites
Spatial resolution
Online AccessGet full text

Cover

More Information
Summary:One of the great challenges of land cover mapping from remotely sensed images is the mixed pixel problem. Much research has focused on attempting to extract land cover types at sub-pixel scale, while little research has been conducted concerning the spatial allocation of land cover types within a pixel. The "pixel-swapping" optimization algorithm was examined for predicting land cover distribution using remote sensory imagery at a sub-pixel level. Optimum parameters were derived through the experiment.
ISBN:0780390504
9780780390508
ISSN:2153-6996
2153-7003
DOI:10.1109/IGARSS.2005.1526224