
The application of remote sensing to the study of geography as spatially distributed phenomena began in the late 1800s when German foresters used photography taken from a balloon to produce forest maps. Since this early beginning researchers and professionals in government, industry, and educational institutions have become increasingly aware of the ability of remote sensing to provide geographic information. This is information on the spatial distribution and temporal dynamics of objects and processes in the world around us. Geographic applications of remotely sensed data typically take one of four explanatory forms and are aimed at one or more of three practical objectives. Explanatory forms include: 1) morphometric analysis, 2) cause and effect analysis, 3) temporal analysis, 4) functional and ecological systems analysis. Objectives include: 1) mapping, 2) monitoring, 3) modeling. As we have moved from using manual analysis techniques on black-and-white aerial photography for mapping distributions to machine-assisted analysis of multispectral satellite data in digital form for analyzing complex environmental processes, the techniques and procedures involved in the use of remotely sensed data have become more complex. Remote sensing does offer a tremendous potential to the community involved in geographic applications. To realize this potential will continue to require a balanced program of both basic and applied research.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
