Spatial Filtering
Bibliographic Data
| ID | 23757366 |
|---|---|
| Authors | Victor Mesev (0000-0002-4190-7237, Florida State University, corresponding author) |
| Year | 2018 |
| Pages | 1-4 |
| Publication date | 2018-03-29 |
| Open Access | Yes |
| Type | CHAPTER |
| Venue | International Encyclopedia of Geography (SOURCE_BOOK) |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/9781118786352.wbieg0184.pub2 |
| OpenAlex | W4242145634 |
| ISBN | 9781118786352 |
| Language | EN |
| References cited | 6 |
Data values continuously change in response to the geographical features they represent. Smaller changes are indicative of more homogeneous features, while larger changes indicate heterogeneity. These changes in data values are termed “spatial frequencies,” and they dictate the level of visual contrast. Sometimes visual contrast is very low (because of very low spatial frequencies), which can make interpretation of geographical features difficult. Spatial filtering is a technique that alters the magnitude of spatial frequencies to create higher visual contrasts between geographical features. In remote sensing, linear and nonlinear spatial filters use cell‐based windows to reduce or enhance spatial frequencies, so that geographical features can be visually smoothed or sharpened. In general statistical analysis, spatial filters are used to isolate the underlying effects of geographical variables from the effects of temporal and spatial autocorrelation.
Contrast (vision) · Geography · Optics · Pattern recognition (psychology) · Physics · Remote sensing · Spatial analysis · Spatial ecology · Spatial filter · Spatial frequency · Artificial Intelligence · Computer Science · Land Use and Ecosystem Services · Remote Sensing in Agriculture · Remote-Sensing Image Classification
| Highly cited | No |
|---|