Spatial variation analyses of Thematic Mapper data for the identification of linear features in agricultural landscapesA need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.
Document ID
19860035922
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Pelletier, R. E. (NASA Earth Resources Laboratory Bay St. Louis, MS, United States)