Evaluation of ERTS-1 imagery for land use/resource inventory information

This investigation was to develop a low cost, manual technique for enhancing ERTS-1 imagery and preparing it in suitable format for use by users with wide and varied interests related to land use and natural resources information. The goals were: to develop enhancement techniques based on concepts and practices extant in photographic sciences, to provide a means of allowing productive interpretation of the imagery by manual means, to produce a product at low cost, to provide a product that would have wide applications, and one compatible with existing information systems. Cost of preparation of the photographically enhanced, enlarged negatives and positives and the diazo materials is about 1 cent per square mile. Cost of creating and mapping a land use classification of twelve use types at a scale of 1:250,000 is only $1 per square mile. The product is understood by users, is economical, and is compatible with existing information systems

Evaluation of Skylab imagery as an information service for investigating land use and natural resources

There are no author-identified significant results in this report

Enhancement and evaluation of Skylab photography for potential land use inventories, part 1

The author has identified the following significant results. Three sites were evaluated for land use inventory: Finger Lakes - Tompkins County, Lower Hudson Valley - Newburgh, and Suffolk County - Long Island. Special photo enhancement processes were developed to standardize the density range and contrast among S190A negatives. Enhanced black and white enlargements were converted to color by contact printing onto diazo film. A color prediction model related the density values on each spectral band for each category of land use to the spectral properties of the various diazo dyes. The S190A multispectral system proved to be almost as effective as the S190B high resolution camera for inventorying land use. Aggregate error for Level 1 averaged about 12% while Level 2 aggregate error averaged about 25%. The S190A system proved to be much superior to LANDSAT in inventorying land use, primarily because of increased resolution

Deriving Spectral and Spatial Features to Establish a Hierarchical Classification System

Automatic processing of remotely sensed data has to date been constrained to using training sets to classify a small number of categories within the context of a limited geographical area. In order to promote a more flexible user-oriented data processing system, a hierarchical taxonomic structure is proposed. This structure incorporates data inputs from several different sensors together with a priori information on the characteristics of different materials of interest to facilitate efficient design of feature sets to classify those materials. A Boolean approach may be used to assign these feature sets including both spectral and spatial criteria to different hierarchical levels