7. Site/Association

Site refers to the topographic or geographic location of objects. It is an important clue in the identification of certain types of features (Figure 5.38). For example, certain tree species would occur on well-drained upland sites, whereas other tree species would occur on poorly drained lowland sites.

The term 'site' is significant in the context of remote sensing as it describes the geographic or topographical location of features in an image. Different species of trees, for example, have specific preferences for their growing conditions. Some trees thrive on upland sites that are well-drained, meaning they don’t retain water, while others prefer lowland sites that can hold moisture, which allows the trees to draw in necessary water for growth. This relationship helps in identifying tree species from remote images based on their location.

Think of a gardener who distinguishes between two types of plants. One type of plant grows best in sunny, elevated gardens (upland), while the other flourishes in damp, shady areas (lowland). Just like the gardener uses soil type and moisture to decide where to plant, remote sensing experts use site information to determine where certain species might be found in images.

Association refers to the presence of certain features in relation to others. It takes into account the relationship between the recognizable objects/features in proximity to the object to be identified. For example, the snow cover is related to higher elevation zones, commercial properties are associated with major transportation routes.

Association involves understanding how different features are related based on their spatial proximity. For instance, certain environmental conditions, like snow cover, commonly occur in regions at higher elevations. Similarly, commercial areas tend to be located near major roads and transportation routes to facilitate better access. By examining these associations in remote sensing data, analysts can deduce information about land use and the types of features present in an area.

Consider a shopping mall in your town. You’ll likely find it near major highways and streets because that location encourages customers to visit. Similarly, remote sensing analysts look at spatial associations to understand why certain features exist together—like snow in mountain areas or shops near busy roads.

--