Chapter 12 Applications of Remote Sensing


12.1 Land Cover Classification

Land cover mapping is one of the most important and typical applications of remote sensing data. Land cover corresponds to the physical condition of the ground surface, for example, forest, grassland, concrete pavement etc., while land use reflects human activities such as the use of the land, for example, industrial zones, residential zones, agricultural fields etc.

Generally land cover does not coincide with land use. A land use class is composed of several land covers. Remote sensing data can provide land cover information rather than land use information.

Initially the land cover classification system should be established, which is usually defined as levels and classes. The level and class should be designed in consideration of the purpose of use (national, regional or local), the spatial and spectral resolution of the remote sensing data, user's request and so on.

The definition should be made as quantitatively clear as possible. Figure 12.1.1 shows an example of land cover classes for land cover mapping in the Sagami River Basin, Japan, for use with Landsat MSS data.

The classification was carried out as follows.

a. Geometric correction (see 9.4)
A geo-coded Landsat image was produced.

b. Collection of the ground truth data (see 6.7)
A ground investigation was made to identify each land cover class on the geo-code Landsat image as well as on topographic maps.

c. Classification by Maximum Likelihood Method (see 11.5 )
The Maximum Likelihood Method was adopted using the training samples obtained from the ground truth.

Figure 12.1.1 shows the classified land cover map.

Generally Landsat MSS imagery can provide about about ten land cover classes, depending upon the size and complexity of the classes.


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