@article {Jensen:1978:1523-0406:121,
	author = "Jensen, John R.",
	title = "Digital Land Cover Mapping Using Layered Classification Logic and Physical Composition Attributes",
	journal = "Cartography and Geographic Information Science",
	volume = "5",
	number = "2",
	year = "1978",
	abstract = "Imagery created by satellite multispectral scanning systems have generated widespread interest for application to land cover mapping. The energy sensed in each spectral band can be interpreted visually, or it can be used as a feature in a machine-assisted pattern recognition process. Simultaneous visual interpretation of numerous multispectral images often becomes impractical, especially as the area studied increases; hence, great emphasis has been placed on computer techniques for improving the repeatability, accuracy, and timeliness of land cover mapping. In this light, a parallelepiped layered classification incorporating physical composition attributes was developed and tested against the traditional Boolean logic parallelepiped decision rule. LANDSAT digital picture elements (pixels) of Goleta, California, were interactively filtered through a series of decision layers (solid, liquid, organic, inorganic, mixture solid/liquid, and mixture organic/inorganic) prior to being assigned to land use classes. Evaluation of the layered classification versus the traditional parallelepiped classification revealed a statistically significant difference between errors of commission and no significant difference between errors of omission. Errors of commission create serious problems in traditional parallelepiped classifications, consequently the hybrid technique exhibits potential for improved land cover mapping.",
	pages = "121-132",
	url = "http://www.ingentaconnect.com/content/cagis/cagis/1978/00000005/00000002/art00003"
}