Links
- The Publications Warehouse does not have links to digital versions of this publication at this time
- Download citation as: RIS | Dublin Core
Abstract
The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs.
The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example |
| Series title | Pecora VII Symposium |
| Year Published | 1981 |
| Language | English |
| Publisher | American Society of Photogrammetry |
| Publisher location | Falls Church, VA |
| Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
| Description | 13 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Pecora VII Symposium |
| First page | 442 |
| Last page | 454 |
| Country | United States |
| State | Oregon |
| City | Umatilla |
| Google Analytic Metrics | Metrics page |